Leveraging Pharmacoeconomics and Advance Market Commitments to Reduce Healthcare Expenditures

Summary

By establishing a self-sustaining fund to incentivize pharmaceutical companies to develop new and improved treatment protocols using low-cost, off-patent and unmonopolizable therapies, billions of dollars in cost savings could be realized by US government payers and health insurers in a financially “de-risked” manner while improving quality of care —truly a win/win opportunity.  

Currently, pharmaceutical companies do not develop medical therapies unless they can enforce a monopoly price using patents. As a result, thousands of low-cost therapies, such as repurposed generic drugs, nutraceuticals, plant medicines, medical diets, lifestyle interventions, and dose de-escalation protocols, lack private financial incentives for development. Clinically validating the safety and efficacy of these affordable treatments would help many patients while saving billions of dollars. Meanwhile, the largest pharmaceutical companies are earning trillions of dollars in revenue for new patented drugs that often provide limited or no added benefit to patients, while causing significant financial burden on patients and the taxpayer. 

We can solve these misaligned incentives using new payment models such as interventional pharmacoeconomic (IVPE) randomized controlled trials (RCTs) that result in cost savings for healthcare systems, even if RCTs fail, by comparing the efficacy of low-cost therapies to expensive patented drugs. Further, outcomes-based financing mechanisms known as Advance Market Commitments or Pay-For-Success (PFS) contracts, can incentivize the successful development of new low-cost therapies, entirely funded by payer costsavings from reduced reliance on monopoly-priced drugs. 

We propose that the National Institutes of Health (NIH), National Center for Advancing Translational Sciences (NCATS) work together with payers such as Centers for Medicare & Medicaid Services (CMS) and the United States Department of Veterans Affairs (VA) to transfer a fraction of their costsavings from IVPE RCTs and AMCs to create a self-sustaining “prize” fund for development of low-cost therapies under the 2010 America COMPETES Reauthorization Act

With these new payment models, it is possible to create a scalable and sustainable business for a sponsor to develop affordable therapies, while improving patient outcomes and saving significant costs. For example,  every 10,000 patients treated under an IVPE RCT + AMC contract comparing off-patent ketamine to patented esketamine, which could be more effective for treatment-resistant depression, would save payers at least $1.8 billion over 10 years until the expiry of the esketamine patent, part of which can be paid back into the fund. The IVPE + AMC contract can also provide revenues of at least $250 million to a sponsor of the clinical trials for development, FDA-approval, and post-approval (Phase IV) pharmacovigilance studies for ketamine (see Appendix). 

Challenge and Opportunity

Patients urgently need more effective treatments that are readily accessible and affordable. For many Americans, treatments are prohibitively scarce or expensive, with an estimated 42% of newly-diagnosed cancer patients losing all of their assets within 2 years. As national health expenditures continue to rise and drug R&D productivity continues to stagnate, it is crucial to rethink private-public alignment by implementing improved incentive design systems to support better health and economic outcomes.

Generic medicines have substantial potential for addressing healthcare costs and improving R&D productivity: low-cost generic drugs saved the U.S. healthcare system $1.67 trillion in the last decadeThousands of FDA-approved generic drugs—as well as 50,000+ nutraceuticals, plant medicines, diets, lifestyle interventions, and dose de-escalation regimens (collectively known as unmonopolizable therapies)—could be studied to treat diseases significantly cheaper and faster than developing new patented drugs. It costs an estimated $1 billion-plus and takes more than 10–15 years to get a newly patented drug to market, whereas it is significantly cheaper and faster to find new uses for existing drugs and other unmonopolizable therapies that have known safety profiles and mechanisms of action from their use over many years.

However, it is often not economically viable for pharmaceutical companies to pay for clinical trials assessing unmonopolizable therapies, which can be prescribed off-label at relatively low-cost. Generic-drug companies are protected by “skinny labeling” legislation, which makes it difficult or impossible to enforce patents for new uses of generic drugs. While pharmaceutical companies can reformulate generic drugs and re-patent them to charge a monopoly price, this might only be commercially viable if the reformulation is better than the original generic. And where a reformulation involves a combination of generic drugs, compounding pharmacies can prescribe the drug using the original low-cost generics. 

Due to this market failure, there is a lack of funding for large and robust clinical trials for such low-cost therapies; the chance of the original formulation of a generic drug obtaining FDA approval for a new use approaches zero when it goes generic. The same problem applies to funding large clinical trials for nutraceuticals, medical diets, lifestyle interventions, and novel dosing regimens, where it is almost impossible to stop doctors and patients accessing these therapies. Patients who desperately need more treatment options are unable to realize the benefits that existing off-patent, unmonopolizable, or low-cost therapies might offer, and there may be significant harm to the public due to such gaps in patent incentives

Increased direct grant funding for clinical trials can also create suboptimal outcomes. During the height of the COVID-19 pandemic in 2020, the Pepcid AC (famotidine) COVID-19 Study raised red flags weeks after a $21 million grant was awarded to study its effects as a potential therapy. Concerns over study integrity, outcome measures, and even administrative protocols were all brought to light. Ironically, such grant funding can lead to even more risk and wasted taxpayer funds, such as $150 million of federal funding on the dietary supplement curcumin studied in more than 120 clinical trials, with no tangible evidence that it is an effective treatment for any medical condition. Further, conservative estimates of publicly funded clinical trials for repurposing phospholipidosis-inducing CADs to treat COVID-19, including hydroxychloroquine, may be over $6 billion. Other than the large and pragmatic RECOVERY and TOGETHER trials initiated by the United Kingdom, which discovered that dexamethasone significantly reduced mortality in COVID patients on respiratory support, funding smaller, low-powered clinical trials did not lead to the development of significantly beneficial COVID therapies for patients. A risk-transferring market mechanism to fund large clinical trials would have been more efficient—or at least not have exposed taxpayers to the risk of failed clinical trials. IVPE RCTs are paid from cost savings, and AMC contracts only pay out when pre-specified requirements are met, so taxpayers and health insurers do not pay for any failures.

To quickly and affordably improve the lives of millions of patients, we propose that Congress should appropriate, and the Biden-Harris Administration should direct, the NIH, CMS, and VA with the support of the NCATS Repurposing Drugs program, to establish a self-sustaining fund utilizing IVPE RCTs and AMCs to fund clinical trials for affordable therapies generating cost savings (“IVPE + AMC Fund”), using their federal authorization to establish market rewards or “prizes” under the 2010 America Competes Reauthorization Act. Private health insurers are fragmented and have limited incentives to reduce the costs of the $4 trillion p/a US healthcare industry in order to justify the high premiums charged to their US customers, while providers earn more revenue by charging higher fees. However, there is some movement away from fee-for-service and towards PFS contracts and Value Based Pricing (VBP). There is also a significant risk of lawsuits (including personal liability for decisionmakers) under ERISA legislation and the Consolidated Appropriations Act of 2021, which impose a fiduciary duty on self-insured employers to reduce healthcare spend. Taxpayer-funded payers such as CMS, VA, United States Army and large self-insured employers can use IVPE RCTs and AMCs to incentivize development of low-cost therapies as a fiduciary and financial risk management mechanism. Their net cost savings would far exceed the cost of administering the IVPE + AMC Fund. 

In particular, IVPE RCTs compare equivalence or superiority of a low-cost repurposed generic drug to an expensive patented drug normally funded by a payer. For example, there was a recent proposal to establish a self-sustaining IVPE fund to determine the optimal minimum dose for expensive oncology drugs to save costs while reducing side-effects. The price difference between the low-cost and expensive intervention can far exceed the cost of running the RCT, which means it pays for itself in cost savings, even if the RCT fails. And if the RCT shows the low-cost treatment provides at least the same standard of care as the patented drug, this can save payers billions of dollars until the patent expires. If some of these cost savings are transferred back into an IVPE + AMC Fund, this will create a scalable business model for developing new low-cost therapies. 

The self-sustaining nature of the IVPE + AMC Fund could be demonstrated, for example, by providing market rewards up to $100 million (which can be pooled between federal agencies) to reimburse a sponsor recruiting patients into IVPE trials comparing low-cost and expensive therapies. The reimbursement amount should ideally be less than the cost of the expensive therapy and the resulting guaranteed payer cost savings from the low-cost therapy substituting the expensive therapy could be paid back to increase the size of the fund. The IVPE clinical trial would require ethics approval and provide valuable data to “de-risk” whether the low-cost therapy works, without requiring additional taxpayer support. AMCs then would act as a “pull” mechanism to reward sponsors of large Phase III Randomized Controlled Trials (RCTs) that result in FDA approval with higher reimbursement price for an otherwise low-cost therapy that would substitute the expensive therapy. For example, a sponsor can partner with a generic drug manufacturer to guarantee supply of a repurposed generic in return for sharing revenue under an AMC. The sponsor can then submit bioequivalence and efficacy RCT data under the 505(b)(2) pathway to obtain a new “label” for the new use, which also provides a 3-year period of data exclusivity. Alternatively, a sponsor can leverage the revenue from the AMC to develop a nominal reformulation (e.g. new mechanism of administration or dose) to disincentivize generic substitution and obtain a 5-year period of data exclusivity under the 505(b)(1) New Drug Application pathway. The sponsor can earn additional revenue from the sale of the repurposed generic or RCT data to other healthcare systems, with the payers backing the IVPE + AMC Fund receiving a lower price or royalties. Payer cost savings from substituting an expensive therapy with the lower-cost therapy can be paid back into the IVPE + AMC Fund to ensure long-term sustainability. 

AMC contracts are already implemented in various other contexts to address market failures. For example, so-called Social Impact Bonds (SIBs), a type of AMC contract, have been used to help fund projects preventing homelessness and prisoner recidivism, with over $700 million in SIBs raised to date. Operation Warp Speed used AMCs to incentivize vaccine development through FDA approval and lab-to-patient stages. Similar methodologies to IVPE RCTs have also been used to prove that a low  dose of bevacizumab (Avastin) could treat age-related macular degeneration rather than patented ranibizumab (Lucentis), which was estimated to save Medicare Part B $18 billion over 10 years

Therefore, an IVPE + AMC Fund can generate billions of dollars in revenue from payers due to cost savings through the development of new low-cost therapies that reduce reliance on expensive therapies. It can also address misaligned incentives under the patent system by encouraging pharmaceutical companies to (1) “de-link” profits from maximizing sales of a monopoly-priced drug, (2) ensure that patented drugs are value for money rather than pursuing “evergreening” strategies such as patenting slight modifications of generic drugs to extend the period of monopoly pricing, and (3) pursue the most effective therapies rather than the most patentable. AMCs can also be used to incentivize development of low-cost therapies to address unmet medical needs if an expensive comparator treatment is not available or otherwise, the IVPE methodology can compare usual care. 

A Market Failure Caused by a Tragedy of the Commons

Thousands of potentially safe and effective off-patent and low-cost therapies are currently ignored due to misaligned incentives under the patent system. Core to this tragedy is that the clinical trial data validating the safety and efficacy of treatment protocols is what is valuable to healthcare payers and patients, not whether the drug’s active ingredient is new. In essence, treatment protocols involving new uses for off-patent and unmonopolizable therapies are nonrivalrous and “highly non-excludable” public goods. The co-author Savva Kerdemelidis’s 2014 master’s thesis concluded that because the patent system provides inadequate incentives for the pharmaceutical industry to develop such “unmonopolizable therapies,” alternative “prize-like” incentives are needed. This allows payers to put a price on clinical trial data validating the efficacy of these new and more affordable treatment protocols.

Scaling the Development of Low-Cost Therapies with IVPE RCTs and AMCs

IVPE RCTs and AMCs (see definition in FAQ section) recognize that the value of a therapeutic intervention is not the cost of an active ingredient but the clinical trial data showing it is safe and effective in a particular patient population. To accelerate the development of unmonopolizable therapies through the clinical and regulatory pipeline, we propose that payers—specifically government agencies such as CMS and VA as well as health insurers responsible for pharmaceutical reimbursement (ideally a consortium of payers)—support IVPE RCT pilots to de-risk early-stage clinical research and the use of AMC contracts through the IVPE + AMC Fund. The AMC will incentivize a sponsor fund the Phase III studies need to obtain FDA approval and conduct post-approval (Phase IV) pharmacovigilance studies. It will be self-sustaining if a percentage of savings from the availability of low-cost therapies is paid back into the IVPE + AMC Fund.  

The total amount of outcome payments under an AMC drawn from the IVPE + AMC Fund can be calculated with reference to the level of clinical impact or Quality-Adjusted Life-Years (QALYs) generated, disability-adjusted life-years (DALYs) reduced, or even future cost savings from allowing a low-cost therapy to be substituted for an expensive one or reduce hospitalisation costs. For example, the number of QALYs resulting from an approved unmonopolizable therapy can be calculated in advance by a committee of pharmacoeconomic experts under a similar process to the United Kingdom National Health System’s Subscription-Style-Payment (SSP) model for incentivizing development of new antibiotics. Under an SSP, a fixed amount is paid annually according to the total QALY value of the new therapy, as assessed by an elected, independent Medical Evaluation Committee. Similarly, CMS in Louisiana implemented a “Netflix-subscription” model to guarantee supply of low-cost generic drugs to treat Hepatitis C by agreeing to a fixed annual payment in advance. Pay-for-performance and value-based-payment (VBP) contracts are similar to AMC contracts and often negotiated with payers to provide more cost-effective delivery of healthcare services, where rewards are based on certain conditions being met. Accordingly, using AMC contracts to reward successful RCTs is not a novel mechanism that will require a significant administrative burden for federal agencies to implement. It may only require changing a few sentences in an existing VBP contract to refer to a repurposed generic drug or low-cost therapy.  

The following example describes how the IVPE + AMC model works:

  1. A payer (e.g., CMS) agrees to an IVPE RCT with a sponsor comparing the equivalence or superiority of a repurposed generic drug or low-cost therapy to a patented drug (or expensive standard of care). The payer can reimburse the low-cost therapy at a higher price or per-patient price sufficient to cover the costs of the IVPE RCT. If the higher reimbursement is at a lower price than the patented drug or expensive treatment, it will guarantee cost savings for the payer, even if the RCT fails. If the IVPE RCT is successful, the payer agrees to a AMC worth, say, at least $100 million to purchase a  minimum quantity of the repurposed generic drug in advance or reimbursing the sponsor at the higher price, subject to a sponsor obtaining FDA approval and being responsible for post-approval pharmacovigilance. Notably, because the IVPE RCT is funded from immediate cost savings due to the price difference between the low-cost therapy and patented drug, both parties are financially de-risked. (See Appendix 1 for an example of the IVPE + AMC model using the example of generic ketamine vs. patented esketamine to treat depression.) 
  2. The sponsoring pharmaceutical company raises $50 million to conduct the clinical trials needed for FDA approval, on the basis of the agreement to transfer cost savings under the IVPE RCT and the $100 million AMC, subject to FDA approval and post-approval (Phase IV) pharmacovigilance studies showing continued safety and efficacy. 
  3. If the IVPE RCT is successful and the generic drug or low-cost therapy is shown to be equivalent to or better than the expensive patented drug, the AMC is triggered: sponsors are guaranteed minimum sales of $100M and also have a “branded” generic or low-cost therapy with new label and data exclusivity for three years by filing an abbreviated new drug application (ANDA) with the FDA. A new drug application (NDA) with five years of data exclusivity is possible if the generic or low-cost therapy contains a new active ingredient. They can also obtain a method of use patent on the optimal treatment protocol, which provides some commercial benefit and leverage to negotiate AMCs with other payers. A payer’s cost savings from updating their reimbursement guidelines to substitute a low-cost generic drug for the expensive patented drug will exceed the $100 million outcome payments under the AMC, which can be used to top-up the IVPE + AMC Fund to make it self-sustaining. In the case that clinical trials fail, the sponsor loses their investment, unless payers agree to transfer part of their cost savings for the duration of the IVPE RCTs to reimburse the sponsor. This is truly a win-win arrangement to fund new RCTs with very limited commercial risks compared to traditional drug development. The main task is finding repurposed generic drugs or low-cost interventions that could reduce reliance on expensive patented drugs by having at least the same safety and efficacy. There are many low-hanging fruits that are already medically “de-risked” (see generic drug repurposing use cases section below). 

Once the repurposed generic or low-cost therapy receives FDA approval and market authorization, the insurer can then market the approved therapy to prescribing medical doctors. Doctors in turn can prescribe the treatment protocol to their patients, who benefit from improved health. Moreover, this payment model that generates revenue from RCT data resulting in costsavings helps redress the conflict of interest and information asymmetry between government and healthcare payers and pharmaceutical companies, who are now incentivized to develop the most effective therapies for the lowest cost. 

Financial and Health Impact of the IVPE + AMC Fund

According to the Office of Management and Budget and the Office of Science and Technology Policy, prize competitions benefit the federal government by allowing federal agencies to:

  1. Pay only for success
  2. Establish ambitious goals and shift technological and other risks to prize participants 
  3. Increase the number and diversity of individuals, organizations, and teams tackling a problem, including those who have not previously received federal funding
  4. Increase cost effectiveness, stimulate private-sector investment, and maximize the return on taxpayer dollars
  5. Motivate and inspire the public to tackle scientific, technical, and societal problems

There are additional reasons why implementing a self-sustaining IVPE + AMC Fund as a prize-like “pull” incentive to reward development of low-cost therapies is more efficient and scalable than providing grant funding or “push” incentives (although the approaches can be complementary and push incentives can be superior when likely outcomes are known to the grantor). First, IVPE RCTs de-risk sponsors if the payer cost savings are shared by ensuring payer reimbursement of the low-cost therapy is sufficient to cover the costs of the RCT. Under an AMC contract, there is a transfer of risk from payers to the market: payers are not willing to take on the risk and expense of large RCTs, the responsibility of marketing to patients and doctors, and managing adverse events or product recalls. In turn, the market is comfortable taking on this risk and expense, as long as investors can obtain a standard rate of return (e.g., 10-20% p/a). Second, payers and government agencies are often not as well-qualified or equipped as the pharmaceutical industry, which has access to the most experienced staff and latest technological advances, including artificial intelligence. Third, grant programs have high administration costs, both for grantors and grantees, while the latter are not incentivized to deliver successful outcomes. By comparison, the markets are incentivized to fail fast and efficiently allocate capital to those best able to deliver results for the lowest cost. Lastly, repurposed off-patent and unmonopolizable therapies could outcompete patented drugs by providing improved health outcomes for a lower cost to payers. Pharmaceutical companies may also benefit from IVPE RCTs and AMC contracts versus developing novel molecules, due to decreased risk, costs, and time to market.  

The IVPE + AMC Fund creates a clinical trial data marketplace that incentivizes the funding of large-scale clinical trials of unmonopolizable therapies such as low-cost generic drugs that can result in billions, if not trillions, of dollars in healthcare savings for health insurers and governments and, moreover, provide better treatment options and outcomes for patients. Those cost savings can then be reinvested in additional IVPE + AMC Funds to incentivize further development of treatment protocols. Accordingly, the IVPE + AMC model not only incentivizes investment in unmonopolizable therapies, it can also be used to generate a sustainable and scalable business model for additional investment into low-cost therapies that also help improve access to healthcare in the Global South. 

Many Generic Drug Repurposing or Low-Cost Therapy Candidates Exist

Use Case 1: Metastatic Cancer

Hundreds of non-cancer generic drugs have already been tested by researchers and physicians in preclinical and clinical studies for cancer, some up to Phase II trials, and show promise. For example, repurposing the off-patent NSAID ketorolac as a prevention treatment resulting in 10% reduction in breast cancer recurrence would cost $5 million annually (100,000 cases at $50 per case for ketorolac and its administration). The savings could be over $1 billion annually (10,000 patients at approximately $100,000 per patient for the treatment of metastatic disease). These savings would be dwarfed by the cost savings available under an IVPE fund comparing low doses of expensive patented cancer drugs with their standard dose, which can result in fewer side-effects for patients, including nivolumab, abiraterone, trastuzumab, ibrutinib, paclitaxel, and pembrolizumab. The latter (Keytruda) is the top-selling blockbuster drug, with annual sales in excess of $15B; dosing Keytruda by weight could reduce use by 25% in approved indications such as lung cancers

Use Case 2: Major Depressive Disorder & Treatment-Resistant Depression

Depression is the leading cause of disability in the United States for people between the ages of 15 and 44. An estimated 12-month prevalence of medication-treated major depressive disorder (MDD) in the United States was 8.9 million adults, and 2.8 million had treatment-resistant depression (TRD). A growing body of evidence has shown that infusions of generic ketamine can be a viable and affordable therapy for both forms of depression, which cost the United States over $320 billion in 2018. Generic ketamine has been used as a general anesthetic since the Vietnam War and costs less than $2 per dose. However generic ketamine is not authorized to treat any form of depression. The patented and FDA-approved s-ketamine or esketamine, has a price at $850 per dose and is used for TRD and MDD with suicidal ideation. 

To date, many clinical trials show that generic ketamine is more effective. Moreover, a 2020 study indicated that esketamine is unlikely to be cost-effective for management of treatment-resistant depression in the United States unless its price falls by more than 40%. And recently, the UK payer NICE declined to reimburse esketamine. With approximately nine million American adults living with treatment-resistant depression, successfully repurposing generic ketamine using the self-sustaining IVPE + AMC Fund could save many lives through improved access and standard of care—and save healthcare payers hundreds of millions of dollars in monopoly prices.

Plan of Action

The IVPE + AMC Fund can be established through the America COMPETES Reauthorization Act of 2010 (P.L. 111-358), which encourages prize competitions by authorizing the head of any federal agency to carry out a competition that has the potential to stimulate innovation and advance the agency’s mission. In 2016, the 21st Century Cures Act (P.L. 114-255) directed the director of the NIH to support prize competitions that would realize significant advancements in biomedical science or improve health outcomes, especially as they relate to human diseases or conditions. IVPE + AMC contracts can act like a “prize-like” incentive that is designed to address market failures but also lower healthcare treatment costs for federal agencies  (e.g., CMS or VA)  by incentivizing the discovery and validation of evidence that low-cost interventions such as repurposed generic drugs may be equivalent to or more effective than expensive interventions such as patented drugs. 

In short, we propose that the IVPE + AMC Fund be established and operate as follows:

The IVPE + AMC Fund is established through the America COMPETES Reauthorization Act of 2010 (P.L. 111-358) to support backing of IVPE RCTs by payers as a self-funding mechanism and authorize outcome payments of up to $100 million under an AMC for successful clinical trials of a repurposed generic drug, nutraceutical, and/or other low-cost unmonopolizable therapy to treat a specific indication of high unmet medical need and cost burden (e.g. cancer, treatment resistant depression, glioblastoma, Crohn’s Disease, Alzheimer’s).

The IVPE + AMC Fund is furthermore supported by Section 2002 of The 21st Century Cures Act (Division A of P.L. 114-255), which requires the director of the NIH, under authorities in 15 U.S.C. §3719, to support prize competitions for one or both of the following goals:

  1. Identify and fund areas of biomedical science that could realize significant advancements through a prize competition; and 
  2. Improve health outcomes, particularly with respect to human diseases and conditions that are serious and represent a significant disease burden in the United States. The prize competition may also target human diseases and conditions for which public and private investment in research is disproportionately small relative to federal government expenditures for prevention and treatment activities and those diseases and conditions with potential for a significant return on investment via reduction in federal expenditures.

The director of the NIH elects a Medical Evaluation Board, which oversees and manages the prize purpose held by the IVPE + AMC Fund as follows:

  1. Determining the minimum reimbursement price to sponsors for patients receiving a low-cost therapy under an IVPE RCT which is less than the price of an expensive patented drug or intervention that it substitutes. Then determine the minimum purchase order or outcome payments under an AMC contract relative to total QALY / DALY improvement or cost savings, subject to large Phase 3 RCTs resulting in FDA-approval of the low-cost therapy, and further subject to ongoing safety and efficacy shown in Phase 4 pharmacovigilance studies. 
  2. The Medical Evaluation Board will be required to collect information on the effect of the IVPE + AMC Fund on advancing biomedical science or improving health outcomes and the effect of the innovations on federal expenditures.

Initially, we propose that Congress should fund the NIH with $2 million to establish a pilot IVPE + AMC Fund program in partnership with the NIH Office of Acquisition Management and Planning and NCATS. The focus of this would be to create a menu of “de-risked” low-cost therapies suitable for reimbursement under an IVPE + AMC Fund, and feasibility studies to show projected cost savings for payers such as CMS and VA and patient access benefits based on existing NCATS translational efforts, including generic drugs or dose de-escalation interventions by comparing them to expensive patented interventions under the IVPE model. For example, for treatment of age-related macular degeneration, generic drugs such as bevacizumab (Avastin) could save Medicare Part B $18 billion over 10 years compared with ranibizumab (Lucentis). Or compare the cost of prescribing the generic fluvoxamine to treat Covid at $6000 per QALY with molnupiravir at $55,000 per QALY, substituting sirolimus for nab-sirolumus to treat locally advanced unresectable or metastatic malignant perivascular epithelioid cell tumors (PEComa), or substituting sirolimus for everolimus in various cancers. Significant cost savings from IVPE RCT de-escalation studies comparing a lower dose of an expensive cancer drug to the standard treatment can fund the development of new unmonopolizable therapies. For example, this includes savings from low-dose nivolumab for head and neck cancer, low-dose abiraterone, and trastuzumab, ibrutinib, paclitaxel, and pembrolizumab for various other cancers, as noted above. The key to this pilot would be a sufficient evidence-based evaluation process to generate a menu of low-cost IVPE use cases. Ideally, at scale the IVPE + AMC Fund would cover a wide expanse of market failures, but we recommend the low-hanging fruit of repurposing generic drugs and dose de-escalation studies for specialist oncology drugs before expanding to other types of unmonopolizable therapies, including medical diets such as ketogenic diet, non-pharmaceutical, and lifestyle interventions that can reduce reliance on expensive therapies.

Conclusion

An IVPE + AMC Fund established under the America COMPETES Act can provide a more flexible, self-sustaining and cost-effective payment model for developing affordable and effective medical therapies, as opposed to the pharmaceutical industry’s traditional model of charging a monopoly price for new patented drugs. Establishing IVPE RCTs that compare low-cost treatments with expensive treatments generates immediate cost savings for payers from reduced reliance on monopoly-priced drugs as well as future cost savings if clinical guidelines are updated to recommend the low-cost treatment. AMC contracts incentivize FDA-approval and help correct misaligned incentives under the patent system by ensuring rewards are de-linked from maximizing the sales of a single monopoly-priced drug. 

If our proposed self-sustaining IVPE + AMC Fund can be implemented, this will create new incentives to leverage the biotech innovations of the last 40 years and optimize the efficient delivery of healthcare, including genetic engineering, personalized medicine (informed by blood tests and low-cost DNA sequencing), artificial intelligence, decentralized clinical trials, and telemedicine. The pharmaceutical industry is not to blame if they can only rely on the patent system to obtain a return on investment for funding medical innovation. New outcomes-based payment models are needed to develop more affordable and effective treatments that can pull the practice of medicine into the 21st century and address significant health inequities. 

Appendix

IVPE RCT + AMC Financial Model Example

This IVPE RCT + AMC financial model uses generic ketamine and patented esketamine as an example of how to leverage immediate and future cost savings by comparing a low-cost intervention to an expensive intervention to incentivize funding of RCTs for unmonopolizable therapies.

Current esketamine costs for treatment-resistant depression patients for payer, e.g. CMS

# of treatment-resistant depression patients in a year10000
x average dosage per patient in a year25
x pricing per esketamine dosage$850
Annual treatment costs to payer$212,500,000
Year of esketamine patent expiration2035
Total treatment costs for payer until esketamine patent expiration$2,762,500,000

Costs of IVPE RCT

Esketamine as control armKetamine as control arm
# of treatment-resistant depression patients in RCT for a year50005000
x average dosage perpatient in a year2525
X pricing per dosage$850$2
Total treatment costs to payer$106,250,000$250,000

Total savings from conducting the IVPE RCT (over 1 year)

Total savings from conducting the IVPE RCT (over 1 year)$106,000,000
Less: costs going to the sponsor for engaging with contract research organization to conduct the RCT100,000,000
Savings to payer from simply conducting the IVPE RCT$6,000,000
(1) Payer cost savings can be transferred to sponsor under IVPE RCT contract to help fund R&D to optimize treatment protocol and FDA approval
If IVPE RCT is successful and ketamine obtains FDA approval for treatment-resistant depression, AMC is triggered and total future savings to payers are as follows:
When ketamine is proved near-equivalent efficacy and is used
# of treatment-resistant depression patients in the U.S. a year10,000
x average dosage per patient in a year25
x pricing per dosage under AMC$100
Total annual treatment costs for payer$25,000,000
Annual future savings for payer$187,500,000
x remaining years of esketamine patent (assuming FDA approval in 2025)10
Total future savings for payer$1,875,000,000
(2) $100 pricing per dosage for FDA-approved ketamine represents pricing under AMC to purchase sponsor’s branded ketamine
Total 10-year revenues for sponsor for branded ketamine under AMC$250,000,000
Frequently Asked Questions
What is an advanced market commitment (AMC)?

Advanced market commitments are a type of pay-for-success contract that guarantees a viable market for a product once it is successfully developed. Harvard economist Michael Kremer was the first to propose AMCs to stimulate private sector investment in innovations undersupplied by the market. In 2005, global foundations supported the creation of a detailed proposal by the Center for Global Development that described how an AMC might be structured. In 2009, the first AMC was launched, with $1.5 billion in funding for vaccines for diseases primarily affecting people living in poverty. Three vaccines have since been developed and more than 150 million children immunized, saving an estimated 700,000 lives.

Would your proposal involve price negotiations with payers that are specific to an indication?

Drug pricing can stay uniform if differential pricing is not permitted. Outcome payments under an AMC can be in the nature of a fixed annual “Netflix” subscription-style payment for the RCT data showing that the repurposed generic is safe and effective for the indication, and can be “de-linked” from sales of a drug. Alternatively, if differential pricing is permitted under applicable regulations and policy, then the repurposed generic drug could be priced higher in the new indication under an AMC.

What are some examples of successfully repurposed generic drugs?

Some of the most widely used prominent repurposed drugs include the following (not exhaustive):


Drug nameOriginal indicationDisease name
AspirinAnalgesiaColorectal cancer
GemcitabineAntiviralCancer
RaloxifeneOsteoporosisBreast cancer
SildenafilAnginaErectile dysfunction
Could doctors just prescribe generic drugs off-label to treat disease?

Off-label drug use is when drugs are prescribed for a condition, a type of patient, or a dosage not officially approved by the FDA, which can be 20% of all prescriptions. Off-label drug use is generally not backed by the level of testing and data that allows FDA approvals, so patients do not have the guides and warnings that come from FDA-approved labels. Doctors and patients therefore do not always have enough information about the effects and dangers of the off-label use of the drug to make informed decisions. This can create a situation where patients are unknowingly at risk for dangerous, unexpected side effects. This validates the need for large Phase 3  RCTs to prove that drugs prescribed off-label can be prescribed for a new indication and granted a new label for that indication. In addition, health insurers often do not reimburse off-label use, which means patients are forced to pay out of pocket.

How will your AMC model work if a healthcare payer does not want to pay for cost savings or value generated by a repurposed generic drug, as opposed to the lowest market price for the active ingredient?

Large health insurers, particularly in the United States, often own hospitals and are not incentivized to reduce healthcare costs. This model will become unsustainable due to an aging baby boomer population and insurance premiums increasing faster than wages. To avoid this situation, payers have started to implement more outcomes-based contracts such as value-based pricing and bundled payments to incentivize innovation that reduces healthcare costs. Similarly, payers can agree to support IVPE RCTs to clinically validate a low-cost off-patent intervention by comparing it to an expensive patented intervention or paying an amount representing future cost savings or QALY gains for repurposing a generic drug under an AMC contract. Currently, payers do not put a price on the clinical trial data or treatment protocol information about which generic drug works in a new disease and the optimal dose, but only pay the marginal cost of the generic drug as a chemical. This is like only paying an electrician for the cost of a new $1 part, rather than for the knowledge of the specific part needed to fix an electrical fault, which is the valuable information that takes years of experience and would save your business thousands of dollars or more.

Why does repurposing generic drugs and nutraceuticals result in lower costs than making a novel patented drug?

Repurposed generic drugs and unmonopolizable therapies such as nutraceuticals are de-risked because they have years of efficacy and safety data from successful Phase 1 safety trials  and post-marketing Phase IV data in the case of generic drugs and being generally recognized as safe (GRAS) compounds in the case of nutraceuticals. IVPE RCTs de-risk early clinical trials, and an AMC would incentivize scale-up of supply of the repurposed generic drug and encourage sponsors to train doctors and patients to ensure more rapid uptake of this innovation.

Would some of the proposed schemes require the monitoring of uptake and/or patient outcomes, which imposes an administrative burden for payers?

Under an AMC, there can be a fixed annual payment or minimum sales commitment calculated with reference to determination of cost savings from substitution with expensive patented drugs and/or QALYs gained, similar to the subscription-style payment model for antibiotics in the NHS. The AMC means that the sponsor would also benefit from additional sales of the “branded” generic drug, so they would be incentivized to monitor its use and conduct standard Phase IV pharmacovigilance (and can also be liable for adverse events and recalls). Moreover, payer cost savings from the IVPE + AMC Fund program would far exceed the cost of monitoring or administrative burden.

What is the commercial incentive for a payer to back an AMC and a sponsor to fund RCTs for repurposing generic drugs and nutraceuticals if other payers can free ride on the knowledge by prescribing the generic drug off-label? Where is the business case?

Other than benefitting from immediate cost savings due to reduced reliance on expensive patented drugs, payers backing an AMC can negotiate a favorable price and guaranteed supply of the “branded” generic drug from the sponsor, whereas other payers would be forced to use an off-label version and expose doctors and patients to increased risk of liability. Sponsors would benefit from outcome payments under the AMC and additional sales of the “branded” generic. They can also leverage data exclusivity and traditional patent rights such as method-of-use patent for the optimal treatment protocol and reformulations to negotiate similar AMCs with other payers and also reduce the risk of generic off-label competition. The more payers backing the IVPE + AMC model, the more costsavings can be shared with free-riding. RCT data regarding optimal treatment protocols informed by genetic testing and other diagnostics can also be commercialized as a clinical decision support tool and trade secret. It is the intention of the authors to support the establishment of Public Good Pharma as a biotech company and clinical trial data marketplace owned by the charity Crowd Funded Cures, to carry out this business model.

Creating Auditing Tools for AI Equity

Summary

The unregulated use of algorithmic decision-making systems (ADS)—systems that crunch large amounts of personal data and derive relationships between data points—has negatively affected millions of Americans. These systems impact equitable access to educationhousingemployment, and healthcare, with life-altering effects. For example, commercial algorithms used to guide health decisions for approximately 200 million people in the United States each year were found to systematically discriminate against Black patients, reducing, by more than half, the number of Black patients who were identified as needing extra care.

One way to combat algorithmic harm is by conducting system audits, yet there are currently no standards for auditing AI systems at the scale necessary to ensure that they operate legally, safely, and in the public interest. According to one research study examining the ecosystem of AI audits, only one percent of AI auditors believe that current regulation is sufficient. 

To address this problem, the National Institute of Standards and Technology (NIST) should invest in the development of comprehensive AI auditing tools, and federal agencies with the charge of protecting civil rights and liberties should collaborate with NIST to develop these tools and push for comprehensive system audits. 

These auditing tools would help the enforcement arms of these federal agencies save time and money while fulfilling their statutory duties. Additionally, there is a pressing need to develop these tools now, with Executive Order 13985 instructing agencies to “focus their civil rights authorities and offices on emerging threats, such as algorithmic discrimination in automated technology.”

Challenge and Opportunity

The use of AI systems across all aspects of life has become commonplace as a way to improve decision-making and automate routine tasks. However, their unchecked use can perpetuate historical inequities, such as discrimination and bias, while also potentially violating American civil rights.

Algorithmic decision-making systems are often used in prioritization, classification, association, and filtering tasks in a way that is heavily automated. ADS become a threat when people uncritically rely on the outputs of a system, use them as a replacement for human decision-making, or use systems with no knowledge of how they were developed. These systems, while extremely useful and cost-saving in many circumstances, must be created in a way that is equitable and secure. 

Ensuring the legal and safe use of ADS begins with recognizing the challenges that the federal government faces. On the one hand, the government wants to avoid devoting excessive resources to managing these systems. With new AI system releases happening everyday, it is becoming unreasonable to oversee every system closely. On the other hand, we cannot blindly trust all developers and users to make appropriate choices with ADS.

This is where tools for the AI development lifecycle come into play, offering a third alternative between constant monitoring and blind trust. By implementing auditing tools and signatory practices, AI developers will be able to demonstrate compliance with preexisting and well-defined standards while enhancing the security and equity of their systems. 

Due to the extensive scope and diverse applications of AI systems, it would be difficult for the government to create a centralized body to oversee all systems or demand each agency develop solutions on its own. Instead, some responsibility should be shifted to AI developers and users, as they possess the specialized knowledge and motivation to maintain proper functioning systems. This allows the enforcement arms of federal agencies tasked with protecting the public to focus on what they do best, safeguarding citizens’ civil rights and liberties.

Plan of Action

To ensure security and verification throughout the AI development lifecycle, a suite of auditing tools is necessary. These tools should help enable outcomes we care about, fairness, equity, and legality. The results of these audits should be reported (for example, in an immutable ledger that is only accessible by authorized developers and enforcement bodies) or through a verifiable code-signing mechanism. We leave the specifics of the reporting and documenting the process to the stakeholders involved, as each agency may have different reporting structures and needs. Other possible options, such as manual audits or audits conducted without the use of tools, may not provide the same level of efficiency, scalability, transparency, accuracy, or security.

The federal government’s role is to provide the necessary tools and processes for self-regulatory practices. Heavy-handed regulations or excessive government oversight are not well-received in the tech industry, which argues that they tend to stifle innovation and competition. AI developers also have concerns about safeguarding their proprietary information and users’ personal data, particularly in light of data protection laws.

Auditing tools provide a solution to this challenge by enabling AI developers to share and report information in a transparent manner while still protecting sensitive information. This allows for a balance between transparency and privacy, providing the necessary trust for a self-regulating ecosystem.

Solution Technical Requirements

A general machine learning lifecycle. Examples of what system developers at each stage would be responsible for signing off on the use of the security and equity tools in the lifecycle. These developers represent companies, teams, or individuals.

The equity tool and process, funded and developed by government agencies such as NIST, would consist of a combination of (1) AI auditing tools for security and fairness (which could be based on or incorporate open source tools such as AI Fairness 360 and the Adversarial Robustness Toolbox), and (2) a standardized process and guidance for integrating these checks (which could be based on or incorperate guidance such as the U.S. Government Accountability Office’s  Artificial Intelligence: An Accountability Framework for Federal Agencies and Other Entities).1 

Dioptra, a recent effort between NIST and the National Cybersecurity Center of Excellence (NCCoE) to build machine learning testbeds for security and robustness, is an excellent example of the type of lifecycle management application that would ideally be developed. Failure to protect civil rights and ensure equitable outcomes must be treated as seriously as security flaws, as both impact our national security and quality of life. 

Equity considerations should be applied across the entire lifecycle; training data is not the only possible source of problems. Inappropriate data handling, model selection, algorithm design, and deployment, also contribute to unjust outcomes. This is why tools combined with specific guidance is essential. 

As some scholars note, “There is currently no available general and comparative guidance on which tool is useful or appropriate for which purpose or audience. This limits the accessibility and usability of the toolkits and results in a risk that a practitioner would select a sub-optimal or inappropriate tool for their use case, or simply use the first one found without being conscious of the approach they are selecting over others.”

Companies utilizing the various packaged tools on their ADS could sign off on the results using code signing. This would create a record that these organizations ran these audits along their development lifecycle and received satisfactory outcomes. 

We envision a suite of auditing tools, each tool applying to a specific agency and enforcement task. Precedents for this type of technology already exist. Much like security became a part of the software development lifecycle with guidance developed by NIST, equity and fairness should be integrated into the AI lifecycle as well. NIST could spearhead a government-wide initiative on auditing AI tools, leading guidance, distribution, and maintenance of such tools. NIST is an appropriate choice considering its history of evaluating technology and providing guidance around the development and use of specific AI applications such as the NIST-led Face Recognition Vendor Test (FRVT).

Areas of Impact & Agencies / Departments Involved


Security & Justice
The U.S. Department of Justice, Civil Rights Division, Special Litigation SectionDepartment of Homeland Security U.S. Customs and Border Protection U.S. Marshals Service 

Public & Social Sector
The U.S. Department of Housing and Urban Development’s Office of Fair Housing and Equal Opportunity

Education
The U.S. Department of Education

Environment
The U.S. Department of Agriculture, Office of the Assistant Secretary for Civil RightsThe Federal Energy Regulatory CommissionThe Environmental Protection Agency

Crisis Response
Federal Emergency Management Agency 

Health & Hunger
The U.S. Department of Health and Human Services, Office for Civil RightsCenter for Disease Control and PreventionThe Food and Drug Administration

Economic
The Equal Employment Opportunity Commission, The U.S. Department of Labor, Office of Federal Contract Compliance Programs

Infrastructure
The U.S. Department of Transportation, Office of Civil RightsThe Federal Aviation AdministrationThe Federal Highway Administration

Information Verification & Validation
The Federal Trade Commission, The Federal Communication Commission, The Securities and Exchange Commission.

Many of these tools are open source and free to the public. A first step could be combining these tools with agency-specific standards and plain language explanations of their implementation process.

Benefits

These tools would provide several benefits to federal agencies and developers alike. First, they allow organizations to protect their data and proprietary information while performing audits. Any audits, whether on the data, model, or overall outcomes, would be run and reported by the developers themselves. Developers of these systems are the best choice for this task since ADS applications vary widely, and the particular audits needed depend on the application. 

Second, while many developers may opt to use these tools voluntarily, standardizing and mandating their use would allow an evaluation of any system thought to be in violation of the law to be easily assesed. In this way, the federal government will be able to manage standards more efficiently and effectively.

Third, although this tool would be designed for the AI lifecycle that results in ADS, it can also be applied to traditional auditing processes. Metrics and evaluation criteria will need to be developed based on existing legal standards and evaluation processes; once these metrics are distilled for incorporation into a specific tool, this tool can be applied to non-ADS data as well, such as outcomes or final metrics from traditional audits.

Fourth, we believe that a strong signal from the government that equity considerations in ADS are important and easily enforceable will impact AI applications more broadly, normalizing these considerations.   

Example of Opportunity

An agency that might use this tool is the Department of Housing and Urban Development (HUD), whose purpose is to ensure that housing providers do not discriminate based on race, color, religion, national origin, sex, familial status, or disability.

To enforce these standards, HUD, which is responsible for 21,000 audits a year, investigates and audits housing providers to assess compliance with the Fair Housing Act, the Equal Credit Opportunity Act, and other related regulations. During these audits, HUD may review a provider’s policies, procedures, and records, as well as conduct on-site inspections and tests to determine compliance. 

Using an AI auditing tool could streamline and enhance HUD’s auditing processes. In cases where ADS were used and suspected of harm, HUD could ask for verification that an auditing process was completed and specific metrics were met, or require that such a process be undergone and reported to them. 

Noncompliance with legal standards of nondiscrimination would apply to ADS developers as well, and we envision the enforcement arms of protection agencies would apply the same penalties in these situations as they would in non-ADS cases.

R&D

To make this approach feasible, NIST will require funding and policy support to implement this plan. The recent CHIPS and Science Act has provisions to support NIST’s role in developing “trustworthy artificial intelligence and data science,” including the testbeds mentioned above. Research and development can be partially contracted out to universities and other national laboratories or through partnerships/contracts with private companies and organizations.

The first iterations will need to be developed in partnership with an agency interested in integrating an auditing tool into its processes. The specific tools and guidance developed by NIST must be applicable to each agency’s use case. 

The auditing process would include auditing data, models, and other information vital to understanding a system’s impact and use, informed by existing regulations/guidelines. If a system is found to be noncompliant, the enforcement agency has the authority to impose penalties or require changes to be made to the system.

Pilot program

NIST should develop a pilot program to test the feasibility of AI auditing. It should be conducted on a smaller group of systems to test the effectiveness of the AI auditing tools and guidance and to identify any potential issues or areas for improvement. NIST should use the results of the pilot program to inform the development of standards and guidelines for AI auditing moving forward.

Collaborative efforts

Achieving a self-regulating ecosystem requires collaboration. The federal government should work with industry experts and stakeholders to develop the necessary tools and practices for self-regulation.

A multistakeholder team from NIST, federal agency issue experts, and ADS developers should be established during the development and testing of the tools. Collaborative efforts will help delineate responsibilities, with AI creators and users responsible for implementing and maintaining compliance with the standards and guidelines, and agency enforcement arms agency responsible for ensuring continued compliance.

Regular monitoring and updates

The enforcement agencies will continuously monitor and update the standards and guidelines to keep them up to date with the latest advancements and to ensure that AI systems continue to meet the legal and ethical standards set forth by the government.

Transparency and record-keeping

Code-signing technology can be used to provide transparency and record-keeping for ADS. This can be used to store information on the auditing outcomes of the ADS, making reporting easy and verifiable and providing a level of accountability to users of these systems.

Conclusion

Creating auditing tools for ADS presents a significant opportunity to enhance equity, transparency, accountability, and compliance with legal and ethical standards. The federal government can play a crucial role in this effort by investing in the research and development of tools, developing guidelines, gathering stakeholders, and enforcing compliance. By taking these steps, the government can help ensure that ADS are developed and used in a manner that is safe, fair, and equitable.

WHAT IS AN ALGORITMIC DECISION-MAKING SYSTEM
An algorithmic decision-making system (ADS) is software that uses algorithms to make decisions or take actions based on data inputs, sometimes without human intervention. ADS are used in a wide range of applications, from customer service chatbots to screening job applications to medical diagnosis systems. ADS are designed to analyze data and make decisions or predictions based on that data, which can help automate routine or repetitive tasks, improve efficiency, and reduce errors. However, ADS can also raise ethical and legal concerns, particularly when it comes to bias and privacy.
WHAT IS AN ALGORITMIC AUDIT
An algorithmic audit is a process that examines automated decision-making systems and algorithms to ensure that they are fair, transparent, and accountable. Algorithmic audits are typically conducted by independent third-party auditors or specialized teams within organizations. These audits examine various aspects of the algorithm, such as the data inputs, the decision-making process, and the outcomes produced, to identify any biases or errors. The goal is to ensure that the system operates in a manner consistent with ethical and legal standards and to identify opportunities to improve the system’s accuracy and fairness.
WHAT IS CODE SIGNING, AND WHY IS IT INVOLVED?
Code signing is the process of digitally signing software and code to verify the integrity and authenticity of the code. It involves adding a digital signature to the code, which is a unique cryptographic hash that is generated using a private key held by the code signer. The signature is then embedded into the code along with other metadata.

Code signing is used to establish trust in code that is distributed over the internet or other networks. By digitally signing the code, the code signer is vouching for its identity and taking responsibility for its contents. When users download code that has been signed, their computer or device can verify that the code has not been tampered with and that it comes from a trusted source.

Code signing can be extended to all parts of the AI lifecycle as a means of verifying the authenticity, integrity, and function of a particular piece of code or a larger process. After each step in the auditing process, code signing enables developers to leave a well-documented trail for enforcement bodies/auditors to follow if a system were suspected of unfair discrimination or unsafe operation.

Code signing is not essential for this project’s success, and we believe that the specifics of the auditing process, including documentation, are best left to individual agencies and their needs. However, code signing could be a useful piece of any tools developed.
WHAT IS AN AI AUDITOR
An AI auditor is a professional who evaluates and ensures the fairness, transparency, and accountability of AI systems. AI auditors often have experience in risk management, IT or cybersecurity auditing, or engineering, and use frameworks such as IIA’s AI Framework, COSO ERM Framework, or the U.S. GAO’s Artificial Intelligence: An Accountability Framework for Federal Agencies and Other Entities. Much like other other IT auditors, they review and audit the development, deployment, and operation of systems to ensure that they align with business objectives and legal standards. AI auditors more than in other fields have also had a push to include consideration for sociotechnical issues as well. This includes analyzing the underlying algorithms and data used to develop the AI system, assessing its impact on various stakeholders, and recommending improvements to ensure that it is being used effectively.
WHY SHOULD THE FEDERAL GOVERNMENT BE THE ENTITY TO ACT RATHER THAN THE PRIVATE SECTOR OR STATE/LOCAL GOVERNMENT?
The federal government is uniquely positioned to take the lead on this issue because of its responsibility to protect civil rights and ensure compliance with federal laws and regulations. The federal government can provide the necessary resources, expertise, and implementation guidance to ensure that AI systems are audited in a fair, equitable, and transparent manner.
WHO IS LIKELY TO PUSH BACK ON THIS PROPOSAL AND HOW CAN THAT HURDLE BE OVERCOME?
Industry stakeholders may be resistant to these changes. They should be engaged in the development of tools and guidelines so their concerns can be addressed and effort should be made to clearly communicate the benefits of increased accountability and transparency for both the industry and the public. Collaboration and transparency are key to overcoming potential hurdles, as is making any tools produced user-friendly and accessible.

Additionally, there may be pushback on the tool design. It is important to remember that currently, engineers often use fairness tools at the end of a development process, as a last box to check, instead of as an integrated part of the AI development lifecycle. These concerns can be addressed by emphasizing the comprehensive approach taken and by developing the necessary guidance to accompany these tools—which does not currently exist.
WHAT ARE SOME OTHER EXAMPLES OF HOW AI HAS HARMED SOCIETY
Example #1: Healthcare

New York regulators are calling on a UnitedHealth Group to either stop using or prove there is no problem with a company-made algorithm that researchers say exhibited significant racial bias. This algorithm, which UnitedHealth Group sells to hospitals for assessing the health risks of patients, assigned similar risk scores to white patients and Black patients despite the Black patients being considerably sicker.

In this case, researchers found that changing just one parameter could generate “an 84% reduction in bias.” If we had specific information on the parameters going into the model and how they are weighted, we would have a record-keeping system to see how certain interventions affected the output of this model.

Bias in AI systems used in healthcare could potentially violate the Constitution’s Equal Protection Clause, which prohibits discrimination on the basis of race. If the algorithm is found to have a disproportionately negative impact on a certain racial group, this could be considered discrimination. It could also potentially violate the Due Process Clause, which protects against arbitrary or unfair treatment by the government or a government actor. If an algorithm used by hospitals, which are often funded by the government or regulated by government agencies, is found to exhibit significant racial bias, this could be considered unfair or arbitrary treatment.

Example #2: Policing

A UN panel on the Elimination of Racial Discrimination has raised concern over the increasing use of technologies like facial recognition in law enforcement and immigration, warning that it can exacerbate racism and xenophobia and potentially lead to human rights violations. The panel noted that while AI can enhance performance in some areas, it can also have the opposite effect as it reduces trust and cooperation from communities exposed to discriminatory law enforcement. Furthermore, the panel highlights the risk that these technologies could draw on biased data, creating a “vicious cycle” of overpolicing in certain areas and more arrests. It recommends more transparency in the design and implementation of algorithms used in profiling and the implementation of independent mechanisms for handling complaints.

A case study on the Chicago Police Department’s Strategic Subject List (SSL) discusses an algorithm-driven technology used by the department to identify individuals at high risk of being involved in gun violence and inform its policing strategies. However, a study by the RAND Corporation on an early version of the SSL found that it was not successful in reducing gun violence or reducing the likelihood of victimization, and that inclusion on the SSL only had a direct effect on arrests. The study also raised significant privacy and civil rights concerns. Additionally, findings reveal that more than one-third of individuals on the SSL, approximately 70% of that cohort, have never been arrested or been a victim of a crime yet received a high-risk score. Furthermore, 56% of Black men under the age of 30 in Chicago have a risk score on the SSL. This demographic has also been disproportionately affected by the CPD’s past discriminatory practices and issues, including torturing Black men between 1972 and 1994, performing unlawful stops and frisks disproportionately on Black residents, engaging in a pattern or practice of unconstitutional use of force, poor data collection, and systemic deficiencies in training and supervision, accountability systems, and conduct disproportionately affecting Black and Latino residents.

Predictive policing, which uses data and algorithms to try to predict where crimes are likely to occur, has been criticized for reproducing and reinforcing biases in the criminal justice system. This can lead to discriminatory practices and violations of the Fourth Amendment’s prohibition on unreasonable searches and seizures, as well as the Fourteenth Amendment’s guarantee of equal protection under the law. Additionally, bias in policing more generally can also violate these constitutional provisions, as well as potentially violating the Fourth Amendment’s prohibition on excessive force.

Example #3: Recruiting

ADS in recruiting crunch large amounts of personal data and, given some objective, derive relationships between data points. The aim is to use systems capable of processing more data than a human ever could to uncover hidden relationships and trends that will then provide insights for people making all types of difficult decisions.

Hiring managers across different industries use ADS every day to aid in the decision-making process. In fact, a 2020 study reported that 55% of human resources leaders in the United States use predictive algorithms across their business practices, including hiring decisions.

For example, employers use ADS to screen and assess candidates during the recruitment process and to identify best-fit candidates based on publicly available information. Some systems even analyze facial expressions during interviews to assess personalities. These systems promise organizations a faster, more efficient hiring process. ADS do theoretically have the potential to create a fairer, qualification-based hiring process that removes the effects of human bias. However, they also possess just as much potential to codify new and existing prejudice across the job application and hiring process.

The use of ADS in recruiting could potentially violate several constitutional laws, including discrimination laws such as Title VII of the Civil Rights Act of 1964 and the Americans with Disabilities Act. These laws prohibit discrimination on the basis of race, gender, and disability, among other protected characteristics, in the workplace. Additionally, the these systems could also potentially violate the right to privacy and the due process rights of job applicants. If the systems are found to be discriminatory or to violate these laws, they could result in legal action against the employers.
WHAT OPEN-SOURCE TOOLS COULD BE LEVERAGED FOR THIS PROJECT?
Aequitas, Accenture Algorithmic Fairness. Alibi Explain, AllenNLP, BlackBox Auditing, DebiasWE, DiCE, ErrorAnalysis, EthicalML xAI, Facebook DynaBoard, Fairlearn, FairSight, FairTest, FairVis, FoolBox, Google Explainable AI, Google KnowYourData, Google ML Fairness Gym, Google PAIR Facets, Google PAIR Language Interpretability Tool, Google PAIR Saliency, Google PAIR What-If Tool, IBM Adversarial Robustness Toolbox, IBM AI Fairness 360, IBM AI Explainability 360, Lime, MLI, ODI Data Ethics Canvas, Parity, PET Repository, PwC Responsible AI Toolkit, Pymetrics audit-AI, RAN-debias, REVISE, Saidot, SciKit Fairness, Skater, Spatial Equity Data Tool, TCAV, UnBias Fairness Toolkit

Supporting Historically Disadvantaged Workers through a National Bargaining in Good Faith Fund

Summary

Black, Indigenous, and other people of color (BIPOC) are underrepresented in labor unions. Further, people working in the gig economy, tech supply chain, and other automation-adjacent roles face a huge barrier to unionizing their workplaces. These roles, which are among the fastest-growing segments of the U.S. economy, are overwhelmingly filled by BIPOC workers. In the absence of safety nets for these workers, the racial wealth gap will continue to grow. The Biden-Harris Administration can promote racial equity and support low-wage BIPOC workers’ unionization efforts by creating a National Bargaining in Good Faith Fund.

As a whole, unions lift up workers to a better standard of living, but historically they have failed to protect workers of color. The emergence of labor unions in the early 20th century was propelled by the passing of the National Labor Relations Act (NLRA), also known as the Wagner Act of 1935. Although the NLRA was a beacon of light for many working Americans, affording them the benefits of union membership such as higher wages, job security, and better working conditions, which allowed many to transition into the middle class, the protections of the law were not applied to all working people equally. Labor unions in the 20th century were often segregated, and BIPOC workers were often excluded from the benefits of unionization. For example, the Wagner Act excluded domestic and agricultural workers and permitted labor unions to discriminate against workers of color in other industries, such as manufacturing. 

Today, in the aftermath of the COVID-19 pandemic and amid a renewed interest in a racial reckoning in the United States, BIPOC workers—notably young and women BIPOC workers—are leading efforts to organize their workplaces. In addition to demanding wage equity and fair treatment, they are also fighting for health and safety on the job. Unionized workers earn on average 11.2% more in wages than their nonunionized peers. Unionized Black workers earn 13.7% more and unionized Hispanic workers 20.1% more than their nonunionized peers. But every step of the way, tech giants and multinational corporations are opposing workers’ efforts and their legal right to organize, making organizing a risky undertaking.

A National Bargaining in Good Faith Fund would provide immediate and direct financial assistance to workers who have been retaliated against for attempting to unionize, especially those from historically disadvantaged groups in the United States. This fund offers a simple and effective solution to alleviate financial hardships, allowing affected workers to use the funds for pressing needs such as rent, food, or job training. It is crucial that we advance racial equity, and this fund is one step toward achieving that goal by providing temporary financial support to workers during their time of need. Policymakers should support this initiative as it offers direct payments to workers who have faced illegal retaliation, providing a lifeline for historically disadvantaged workers and promoting greater economic justice in our society.

Challenges and Opportunities

The United States faces several triangulating challenges. First is our rapidly evolving economy, which threatens to displace millions of already vulnerable low-wage workers due to technological advances and automation. The COVID-19 pandemic accelerated automation, which is a long-term strategy for the tech companies that underpin the gig economy. According to a report by an independent research group, self-driving taxis are likely to dominate the ride-hailing market by 2030, potentially displacing 8 million human drivers in the United States alone.

Second, we have a generation of workers who have not reaped the benefits associated with good-paying union jobs due to decades of anti-union activities. As of 2022, union membership has dropped from more than 30% of wage and salary workers in the private sector in the 1950s to just 6.3%. The declining percentage of workers represented by unions is associated with widespread and deep economic inequality, stagnant wages, and a shrinking middle class. Lower union membership rates have contributed to the widening of the pay gap for women and workers of color.

Third, historically disadvantaged groups are overrepresented in nonunionized, low-wage, app-based, and automation-adjacent work. This is due in large part to systemic racism. These structures adversely affect BIPOC workers’ ability to obtain quality education and training, create and pass on generational wealth, or follow through on the steps required to obtain union representation.

Workers face tremendous opposition to unionization efforts from companies that spend hundreds of millions of dollars and use retaliatory actions, disinformation, and other intimidating tactics to stop them from organizing a union. For example, in New York, Black organizer Chris Smalls led the first successful union drive in a U.S. Amazon facility after the company fired him for his activities and made him a target of a smear campaign against the union drive. Smalls’s story is just one illustration of how BIPOC workers are in the middle of the collision between automation and anti-unionization efforts. 

The recent surge of support for workers’ rights is a promising development, but BIPOC workers face challenges that extend beyond anti-union tactics. Employer retaliation is also a concern. Workers targeted for retaliation suffer from reduced hours or even job loss. For instance, a survey conducted at the beginning of the COVID-19 pandemic revealed that one in eight workers perceived possible retaliatory actions by their employers against colleagues who raised health and safety concerns. Furthermore, Black workers were more than twice as likely as white workers to experience such possible retaliation. This sobering statistic is a stark reminder of the added layers of discrimination and economic insecurity that BIPOC workers have to navigate when advocating for better working conditions and wages. 

The time to enact strong policy supporting historically disadvantaged workers is now. Advancing racial equity and racial justice is a focus for the Biden-Harris Administration, and the political and social will is evident. The day one Biden-Harris Administration Executive Order on Advancing Racial Equity and Support for Underserved Communities Through the Federal Government seeks to develop policies designed to advance equity for all, including people of color and others who have been historically underinvested in, marginalized, and adversely affected by persistent poverty and inequality. Additionally, the establishment of the White House  is a significant development. Led by Vice-President Kamala Harris and Secretary of Labor Marty Walsh, the Task Force aims to empower workers to organize and negotiate with their employers through federal government policies, programs, and practices. 

A key focus for the Task Force is to increase worker power in underserved communities by examining and addressing the challenges faced by workers in jurisdictions with restrictive labor laws, marginalized workers, and workers in certain industries. The Task Force is well-timed, given the increased support for workers’ rights demonstrated through the record-high number of petitions filed with the National Labor Relations Board and the rise in strikes over the past two years. The Task Force’s approach to empowering workers and supporting their ability to organize and negotiate through federal government policies and programs offers a promising opportunity to address the unique challenges faced by BIPOC workers in unionization efforts.

The National Bargaining in Good Faith Fund is a critical initiative that can help level the playing field by providing financial assistance to workers facing opposition from employers who refuse to engage in good-faith bargaining, thereby expanding access to unions for Black, Indigenous, and other people of color. In addition, the proposed initiative would reinforce Equal Employment Opportunity Commission (EEOC) and National Labor Relations Board (NLRB) policies regarding employer discrimination and retaliation. The Bargaining in Good Faith Fund will provide direct payments to workers whose employers have retaliated against them for engaging in union organizing activities. The initiative also includes monitoring cases where a violation has occurred against workers involved in union organization and connecting their bargaining unit with relevant resources to support their efforts. With the backing of the Task Force, the fund could make a significant difference in the lives of workers facing barriers to organizing.

Plan of Action

While the adoption of a policy like the Bargaining in Good Faith Fund is unprecedented at the federal level, we draw inspiration from successful state-level initiatives aimed at improving worker well-being. Two notable examples are initiatives enacted in California and New York, where state lawmakers provided temporary monetary assistance to workers affected by the COVID-19 pandemic. Taking a cue from these successful programs, we can develop federal policies that better support workers, especially those belonging to historically disadvantaged groups.

The successful implementation of worker-led, union-organized, and community-led strike assistance funds, as well as similar initiatives for low-wage, app-based, and automation-adjacent workers, indicates that the Bargaining in Good Faith Fund has strong potential for success. For example, the Coworker Solidarity Fund provides legal, financial, and strategic support for worker-activists organizing to improve their companies, while the fund invests in ecosystems that increase worker power and improve economic livelihoods and social conditions across the U.S. South.

New York state lawmakers have also set a precedent with their transformative Excluded Workers Fund, which provided direct financial support to workers left out of pandemic relief programs. The $2.1 billion Excluded Workers Fund, passed by the New York state legislature and governor in April 2021, was the first large-scale program of its kind in the country. By examining and building on these successes, we can develop federal policies that better support workers across the country.

A national program requires multiple funding methods, and several mechanisms have been identified to establish the National Bargaining in Good Faith Fund. First, existing policy needs to be strengthened, and companies violating labor laws should face financial consequences. The labor law violation tax, which could be a percentage of a company’s profits or revenue, would be directed to the Bargaining in Good Faith Fund. Additionally, penalties could be imposed on companies that engage in retaliatory behavior, and the funds generated could also be directed to the Bargaining in Good Faith Fund. New legislation from Congress is required to enforce existing federal policy.

Second, as natural allies in the fight to safeguard workers’ rights, labor unions should allocate a portion of their dues toward the fund. By pooling their resources, a portion of union dues could be directed to the federal fund.

Third, a portion of the fees paid into the federal unemployment insurance program should be redirected to Bargaining in Good Faith Fund. 

Fourth, existing funding for worker protections, currently siloed in agencies, should be reallocated to support the Bargaining in Good Faith Fund more effectively. To qualify for the fund, workers receiving food assistance and/or Temporary Assistance for Needy Families benefits should be automatically eligible once the NLRB and the EEOC recognize the instance of retaliation. Workers who are not eligible could apply directly to the Fund through a state-appointed agency. This targeted approach aims to support those who face significant barriers to accessing resources and protections that safeguard their rights and well-being due to historical labor exploitation and discrimination.

Several federal agencies could collaborate to oversee the Bargaining in Good Faith Fund, including the Department of Labor, the EEOC, the Department of Justice, and the NLRB. These agencies have the authority to safeguard workers’ welfare, enforce federal laws prohibiting employment discrimination, prosecute corporations that engage in criminal retaliation, and enforce workers’ rights to engage in concerted activities for protection, such as organizing a union.

Conclusion

The federal government has had a policy of supporting worker organizing and collective bargaining since the passage of the National Labor Relations Act in 1935. However, the federal government has not fully implemented its policy over the past 86 years, resulting in negative impacts on BIPOC workers, who face systemic racism in the unionization process and on the job. Additionally, rapid technological advances have resulted in the automation of tasks and changes in the labor market that disproportionately affect workers of color. Consequently, the United States is likely to see an increase in wealth inequality over the next two decades.

The Biden-Harris Administration can act now to promote racial equity by establishing a National Bargaining in Good Faith Fund to support historically disadvantaged workers in unionization efforts. Because this is a pressing issue, a feasible short-term solution is to initiate a pilot program over the next 18 months. It is imperative to establish a policy that acknowledges and addresses the historical disadvantage experienced by these workers and supports their efforts to attain economic equity.

How would the Fund identify, prove eligible, and verify the identity of workers who would have access to the Fund?
Any worker currently receiving food assistance and/or Temporary Assistance for Needy Families benefits would automatically become eligible once the instance of retaliation is recognized by NLRB and EEOC. If the worker is not enrolled or currently eligible, they may apply directly to the program.
Why is the focus only on providing direct cash payments?
Demonstrating eligibility for direct payments would depend on policy criteria. Evidence of discrimination could be required through documentation or a claims process where individuals provide testimony. The process could involve a combination of both methods, requiring both documentation and a claims process administered by a state agency.
Are there any examples of federal policies that provide direct payments to specific groups of people?
There are currently no federal policies that provide direct payments to individuals who have been disproportionately impacted by historical injustices, such as discrimination in housing, education, and employment. However, in recent years some local and state governments have implemented or proposed similar policies.

For example, in 2019, the city of Evanston, Illinois, established a fund to provide reparations to Black residents who can demonstrate that they or their ancestors have been affected by discrimination in housing, education, and employment. The fund is financed by a three percent tax on the sale of recreational marijuana and is intended to provide financial assistance for housing, education, and other needs.

Another example is the proposed H.R. 40 bill in the U.S. Congress that aims to establish a commission to study and develop proposals for reparations for African Americans who are descendants of slaves and who have been affected by slavery, discrimination, and exclusion from opportunities. The bill aims to study the impacts of slavery and discrimination and develop proposals for reparations that would address the lingering effects of these injustices, including the denial of education, housing, and other benefits.
Racial equity seems like a lightning rod in today’s political climate. Given that, are there any examples of federal policy concerning racial equity that have been challenged in court?
There have been several federal policies concerning racial equity that have been challenged in court throughout American history. Here are a few notable examples:

The Civil Rights Act of 1964, which banned discrimination on the basis of race, color, religion, sex, or national origin, was challenged in court but upheld by the Supreme Court in 1964.
The Voting Rights Act of 1965, which aimed to eliminate barriers to voting for minorities, was challenged in court several times over the years, with the Supreme Court upholding key provisions in 1966 and 2013, but striking down a key provision in 2013.
The Fair Housing Act of 1968, which banned discrimination in housing, was challenged in court and upheld by the Supreme Court in 1968.
The Affirmative Action policies, which aimed to increase the representation of minorities in education and the workforce, have been challenged in court multiple times over the years, with the Supreme Court upholding the use of race as a factor in college admissions in 2016.

Despite court challenges, policymakers must persist in bringing forth solutions to address racial equity as many complex federal policies aimed at promoting racial equity have been challenged in court over the years, not just on constitutional grounds.

Ensuring Racial Equity in Federal Procurement and Use of Artificial Intelligence

Summary

In pursuit of lower costs and improved decision-making, federal agencies have begun to adopt artificial intelligence (AI) to assist in government decision-making and public administration. As AI occupies a growing role within the federal government, algorithmic design and evaluation will increasingly become a key site of policy decisions. Yet a 2020 report found that almost half (47%) of all federal agency use of AI was externally sourced, with a third procured from private companies. In order to ensure that agency use of AI tools is legal, effective, and equitable, the Biden-Harris Administration should establish a Federal Artificial Intelligence Program to govern the procurement of algorithmic technology. Additionally, the AI Program should establish a strict data collection protocol around the collection of race data needed to identify and mitigate discrimination in these technologies.

Researchers who study and conduct algorithmic audits highlight the importance of race data for effective anti-discrimination interventions, the challenges of category misalignment between data sources, and the need for policy interventions to ensure accessible and high-quality data for audit purposes. However, inconsistencies in the collection and reporting of race data significantly limit the extent to which the government can identify and address racial discrimination in technical systems. Moreover, given significant flexibility in how their products are presented during the procurement process, technology companies can manipulate race categories in order to obscure discriminatory practices. 

To ensure that the AI Program can evaluate any inequities at the point of procurement, the Office of Science and Technology Policy (OSTP) National Science and Technology Council Subcommittee on Equitable Data should establish guidelines and best practices for the collection and reporting of race data. In particular, the Subcommittee should produce a report that identifies the minimum level of data private companies should be required to collect and in what format they should report such data during the procurement process. These guidelines will facilitate the enforcement of existing anti-discrimination laws and help the Biden-Harris Administration pursue their stated racial equity agenda. Furthermore, these guidelines can help to establish best practices for algorithm development and evaluation in the private sector. As technology plays an increasingly important role in public life and government administration, it is essential not only that government agencies are able to access race data for the purposes of anti-discrimination enforcement—but also that the race categories within this data are not determined on the basis of how favorable they are to the private companies responsible for their collection.

Challenge and Opportunity

Research suggests that governments often have little information about key design choices in the creation and implementation of the algorithmic technologies they procure. Often, these choices are not documented or are recorded by contractors but never provided to government clients during the procurement process. Existing regulation provides specific requirements for the procurement of information technology, for example, security and privacy risks, but these requirements do not account for the specific risks of AI—such as its propensity to encode structural biases. Under the Federal Acquisition Regulation, agencies can only evaluate vendor proposals based on the criteria specified in the associated solicitation. Therefore, written guidance is needed to ensure that these criteria include sufficient information to assess the fairness of AI systems acquired during procurement. 

The Office of Management and Budget (OMB) defines minimum standards for collecting race and ethnicity data in federal reporting. Racial and ethnic categories are separated into two questions with five minimum categories for race data (American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White) and one minimum category for ethnicity data (Hispanic or Latino). Despite these standards, guidelines for the use of racial categories vary across federal agencies and even across specific programs. For example, the Census Bureau classification scheme includes a “Some Other Race” option not used in other agencies’ data collection practices. Moreover, guidelines for collection and reporting of data are not always aligned. For example, the U.S. Department of Education recommends collecting race and ethnicity data separately without a “two or more races” category and allowing respondents to select all race categories that apply. However, during reporting, any individual who is ethnically Hispanic or Latino is reported as only Hispanic or Latino and not any other race. Meanwhile, any respondent who selected multiple race options is reported in a “two or more races” category rather than in any racial group with which they identified.

These inconsistencies are exacerbated in the private sector, where companies are not uniformly constrained by the same OMB standards but rather covered by piecemeal legislation. In the employment context, private companies are required to collect and report on demographic details of their workforce according to the OMB minimum standards. In the consumer lending setting, on the other hand, lenders are typically not allowed to collect data about protected classes such as race and gender. In cases where protected class data can be collected, these data are typically considered privileged information and cannot be accessed by the government. In the case of algorithmic technologies, companies are often able to discriminate on the basis of race without ever explicitly collecting race data by using features or sets of features that act as proxies for protected classes. Facebook’s advertising algorithms, for instance, can be used to target race and ethnicity without access to race data. 

Federal leadership can help create consistency in reporting to ensure that the government has sufficient information to evaluate whether privately developed AI is functioning as intended and working equitably. By reducing information asymmetries between private companies and agencies during the procurement process, new standards will bring policymakers back into the algorithmic governance process. This will ensure that democratic and technocratic norms of agency rule-making are respected even as privately developed algorithms take on a growing role in public administration.

Additionally, by establishing a program to oversee the procurement of artificial intelligence, the federal government can ensure that agencies have access to the necessary technical expertise to evaluate complex algorithmic systems. This expertise is crucial not only during the procurement stage but also—given the adaptable nature of AI—for ongoing oversight of algorithmic technologies used within government. 

Plan of Action

Recommendation 1. Establish a Federal Artificial Intelligence Program to oversee agency procurement of algorithmic technologies. 

The Biden-Harris Administration should create a Federal AI Program to create standards for information disclosure and enable evaluation of AI during the procurement process. Following the two-part test outlined in the AI Bill of Rights, the proposed Federal AI Program would oversee the procurement of any “(1) automated systems that (2) have the potential to meaningfully impact the American public’s rights, opportunities, or access to critical resources or services.”

The goals of this program will be to (1) establish and enforce quality standards for AI used in government, (2) enforce rigorous equity standards for AI used in government, (3) establish transparency practices that enable public participation and political accountability, and (4) provide guidelines for AI program development in the private sector.

Recommendation 2. Produce a report to establish what data are needed in order to evaluate the equity of algorithmic technologies during procurement.

To support the AI Program’s operations, the OSTP National Science and Technology Council Subcommittee on Equitable Data should produce a report to establish guidelines for the collection and reporting of race data that balances three goals: (1) high-quality data for enforcing existing anti-discrimination law, (2) consistency in race categories to reduce administrative burdens and curb possible manipulation, and (3) prioritizing the needs of groups most affected by discrimination. The report should include opportunities and recommendations for integrating its findings into policy. To ensure the recommendations and standards are instituted, the President should direct the General Services Administration (GSA) or OMB to issue guidance and request that agencies document how they will ensure new standards are integrated into future procurement vehicles. The report could also suggest opportunities to update or amend the Federal Acquisition Regulations. 

High-Quality Data

The new guidelines should make efforts to ensure the reliability of race data furnished during the procurement process. In particular:

  1. Self-identification should be used whenever possible to ascertain race. As of 2021, Food and Nutrition Service guidance recommends against the use of visual identification based on reliability, respect for respondents’ dignity, and feedback from Child and Adult Care Food Program) and Summer Food Service Program participants.
  2. The new guidelines should attempt to reduce missing data. People may be reluctant to share race information for many legitimate reasons, including uncertainty about how personal data will be used, fear of discrimination, and not identifying with predefined race categories. These concerns can severely impact data quality and should be addressed to the extent possible in the OMB guidelines. New York’s state health insurance marketplace saw a 20% increase in response rate for race by making several changes to the way they collect data. These changes included explaining how the data would be used and not allowing respondents to leave the question blank but instead allowing them to select “choose not to answer” or “don’t know.” Similarly, the Census Bureau found that a single combined race and ethnicity question improved data quality and consistency by reducing the rate of “some other race,” missing, and invalid responses as compared with two separate questions (one for race and one for ethnicity).
  3. The new guidelines should follow best practices established through rigorous research and feedback from a variety of stakeholders. In June 2022, the OMB announced a formal review process to revise Statistical Policy Directive No. 15: Standards for Maintaining, Collecting, and Presenting Federal Data on Race and Ethnicity. While this review process is intended for the revision of federal data requirements, its findings can help inform best practices for collection and reporting requirements for nongovernmental data as well.

Consistency in Data Reporting 

Whenever possible and contextually appropriate, the guidelines for data reporting should align with the OMB guidelines for federal data reporting to reduce administrative burdens. However, the report may find that other data is needed that goes beyond the OMB guidelines for the evaluation of privately developed AI.

Prioritizing the Needs of Affected Groups

In their Toolkit for Centering Racial Equity Throughout Data Integration, the Actionable Intelligence for Social Policy group at the University of Pennsylvania identifies best practices for ensuring that data collection serves the groups most affected by discrimination. In particular, this toolkit emphasizes the need for strong privacy protections and stakeholder engagement. In their final report, the Subcommittee on Equitable Data should establish protocols to secure data and for carefully considered role-based access to it. 

The final report should also engage community stakeholders in determining which data should be collected and establish a plan for ongoing review that engages with relevant stakeholders, prioritizing affected populations and racial equity advocacy groups. The report should evaluate the appropriate level of transparency in the AI procurement process, in particular, trade-offs between desired levels of transparency and privacy.

Conclusion

Under existing procurement law, the government cannot outsource “inherently governmental functions.” Yet key policy decisions are embedded within the design and implementation of algorithmic technology. Consequently, it is important that policymakers have the necessary resources and information throughout the acquisition and use of procured AI tools. A Federal Artificial Intelligence Program would provide expertise and authority within the federal government to assess these decisions during procurement and to monitor the use of AI in government. In particular, this would strengthen the Biden-Harris Administration’s ongoing efforts to advance racial equity. The proposed program can build on both long-standing and ongoing work within the federal government to develop best practices for data collection and reporting. These best practices will not only ensure that the public use of algorithms is governed by strong equity and transparency standards in the public sector but also provide a powerful avenue for shaping the development of AI in the private sector.

Scaling High-Impact Solutions with a Market-Shaping Mechanism for Global Health Supply Chains

Summary

Congress created the Development Finance Corporation (DFC) to finance private sector solutions to the most critical challenges facing the developing world. In parallel, the United States Agency for International Development (USAID) has committed to engaging the private sector and shifting more resources to local market providers to further the impact of U.S. foreign aid dollars. 

USAID is on the verge of awarding its largest-ever suite of foreign aid contracts, totaling $17 billion over the next ten years and comprising nine awards as part of the “NextGen Global Health Supply Chain” (GHSC) contracts. This is a continuation of previous global health supply chain contracts that date back to the 1960s that have grown exponentially in total value but have underperformed and not meaningfully transitioned responsibility for deployment to low- and middle-income country (LMIC) governments and LMIC-based organizations. 

Now is the time for USAID and the DFC to pilot new ways of working with the private sector that put countries on a path to high-impact, sustainable development that builds markets. 

We propose that USAID set aside $300 million of the overall $17 billion package – or less than 2 percent of the overall value – to create a Supply Chain Commercialization Fund to demonstrate a new way of working with the private sector and administering U.S. foreign aid. USAID and the DFC can deploy the Commercialization Fund to:

USAID and the DFC can pilot this new model in three countries where there are already thriving and well-established private markets, like Ghana, Kenya, and Nigeria. 

Challenge and Opportunity

The world is facing an unprecedented concurrence of crises: pandemics, war, rising food insecurity, and a rapidly warming climate. Low- and middle-income countries (LMICs) are deeply affected, with many having lost decades’ worth of gains made toward the Sustainable Development Goals in only a few short years. We now face the dual tasks of regaining lost ground while ensuring those gains are more durable and lasting than before. 

The Biden Administration recognizes this pivotal moment in its new U.S. Strategy Toward Sub-Saharan Africa. The Strategy acknowledges the continent’s growing importance to U.S. global priorities and lays out a 21st-century partnership to contribute to a strong and sustainable global economy, foster new technology and innovation, and ultimately support the long-envisioned transition from donor-driven to country-driven programs. This builds on past U.S. foreign aid initiatives led by administrations of both political parties, including Administrator Mark Green’s Journey to Self Reliance and Administrator Raj Shah’s USAID Forward initiatives. Rather than creating a new flagship program, the U.S. Strategy Toward Sub-Saharan Africa focuses on improved implementation and better integration of existing initiatives to supercharge results. Such aims were echoed repeatedly during the U.S.-Africa Leaders Summit in December 2022.

To realize a new vision for U.S.-Africa partnerships, the Biden Administration should more effectively fuse the work of USAID and the DFC. A key policy rationale for the DFC’s creation in 2018 was to counter China’s Belt and Road Initiative (BRI) and growing economic influence in frontier markets. By combining this investment arm with USAID’s programmatic work, Congress hoped to accelerate major development impact. However numerous mismatches between USAID and DFC priorities have limited and sometimes actively undermined Congress’ goals. In the worst cases, USAID dollars have been used to pay international aid contractors to perform work in places where existing market providers could. Rather than bolster markets, this can distort them.

This memo lays out a new approach to development rooted in better USAID-DFC collaboration, where the work of both agencies contributes to the commercialization of sectors ready to transition from aid-dependent models to commercial and trade-enabled ones. In these sectors, USAID should work to phase out its international aid contractor-led model and instead scale up the work of existing market participants, including by paying them for results. This set of recommendations also advances USAID priorities outlined in the Agency’s new Acquisition and Assistance Strategy and proposed implementation plan, as well as USAID’s policy framework, which each call for working more closely with the private sector and transitioning to more pay-for-performance models.

The global health supply chain is ideal for USAID and the DFC to test the concept of a commercialization fund because of the sector’s discrete metrics and robust existing logistics companies. Investing in cheaper, more efficient evidence-driven solutions in a competitive marketplace can improve aid effectiveness and better serve target populations with the health goods like PPE, vaccines, and medications they need. This sector receives USAID’s largest contracts, with the Agency spending more than $1B each year on procurement and logistics to get the right health products to the right place, at the right time, and in the right condition across dozens of countries. In the logistics space, only about 25%1 of USAID’s expenditure supports directly distributing commodities to health facilities in target nations; the other 75% is spent on fly-in contractors who oversee that work. Despite this premium, on-time and in-full distribution rates often miss their targets, and stockouts are still common, according to USAID’s reports and audits.2

A Commercialization Fund can directly address policy goals such as localization or private-sector engagement by building resilient health supply chains through a marketplace of providers that ensures patients and providers access the supplies they need on time. In addition to improving sustainability and results and cutting costs, a well-structured Commercialization Fund can improve global health donor coordination, crowd-in new investments from other funders and philanthropy that want to pay for outcomes, and hasten the transition from donor-led aid models to country-led ones.

Plan of Action

USAID should create the Global Health Supply Chain Commercialization Fund, a $300 million initiative to purchase commercial supply chain services directly from operators, based on performance or results. USAID should pilot using the Commercialization Fund to pay providers in three countries where there are already thriving and well-established private logistics markets, such as Kenya, Nigeria, and Ghana. In these countries, dozens of logistics and healthcare providers operate at scale, serving millions of people.

With an initial focus on health logistics, USAID should use $300 million from its yet-to-be-awarded suite of $17 billion NextGen Global Health Supply Chain contracts to provide initial funding for the Commercialization Fund. If successful, the Commercialization Fund will create an open playing field for competition and crowd-in high-impact technology, innovation, and more market-based actors in global health supply chains. This fund will build upon existing efforts across the Agency to identify, incubate, and catalyze innovations from the private sector. 

To quickly stand up this Commercialization Fund and select vendors, Administrator Power should utilize her “impairment authority.” Though typically applied to emergencies, the “impairment authority” has been used previously during global health events like the COVID-19 pandemic and the Ebola response and could be used to achieve a specific policy priority such as localization and/or transforming the way USAID administers its global health supply chains. (See FAQ for more information regarding this authority).

The creation of this Fund, which can be fully budget-neutral, requires the following steps:

Step 1. USAID and DFC take administrative action to design and capitalize the $300 million, five-year, cross-cutting, and disease-agnostic Supply Chain Commercialization Fund. A joint aid effectiveness “tiger team” within USAID and the DFC should:

  1. Spearhead the design and implementation framework for the Fund and stipulate clear, standardized key performance indicators (KPIs) to indicate significant improvements in health supply chain performance in countries where the Commercialization Fund operates.
  2. Select three countries to adopt the Commercialization Fund, chosen in coordination with overseas USAID Missions and the DFC. Countries should be selected and prioritized based on factors such as analyses of health systems’ needs, the existence of local supply chain service providers, and countries’ desire to manage more of their own health supply chains. As a follow-on to the U.S.-Africa Leaders Summit, we recommend USAID and the DFC direct initial Commercialization Fund funds to support activities in Africa where there are already thriving and well-established private markets such as Ghana, Kenya, and Nigeria.
  3. Set pricing for each KPI and product in each Commercialization Fund country market. For example, pay-for-performance indicators could include percent of on-time deliveries. USAID and the DFC should set high expectations for performance, such as 95+ percent on-time delivery, especially in geographies where existing market providers can already deliver against similarly rigorous targets in other sectors. USAID bureaus and missions, partner country governments, and in-country private sector healthcare and logistics leaders, as well as supply chain and innovative financing experts, should be consulted during this process. 
  4. Choose funding mechanisms that pay for results (see Step 2 for details).
  5. Provide blended financing to vendors that may need additional resources to scale their footprint and/or increase their capabilities.
  6. Select a third-party auditor(s) to audit the results upon which providers are paid.

Step 2: USAID structures financial instruments to pay service providers against results delivered in selected Commercialization Fund countries

USAID should pay Commercialization Fund providers to deliver results, consistent with the KPIs set in Step 1 by the joint aid effectiveness “tiger team.” Pay-for-performance contracts can also provide incentives and/or price assurances for service providers to build infrastructure and expand to areas they don’t traditionally serve.

Structuring pay-for-performance tools will favor providers that can demonstrate their ability to deliver superior and/or more cost-effective results relative to status quo alternatives. Preference should be given to providers that are operational in the target country where there is existing market demand for their services, as evidenced by factors such as whether the host country government, national health insurance program, or consumers already pay for the providers’ services. USAID should work with the host country government(s) to select vendors to ensure strong country buy-in.

To maximize performance and competition, USAID should explicitly not use cost-reimbursable payment models that reimburse for effort and optimize for compliance and reporting. The red tape associated with these awards is so cumbersome that non-traditional USAID service providers cannot compete.3

USAID should consider using the following pay-for-performance modalities:

Step 3: USAID and DFC should provide countries with additional technical assistance resources to create intentional pathways for selected countries to contribute to the design and management of program implementation. 

To ensure these initiatives support countries’ needs and facilitate country ownership and increase voice, USAID should also consider establishing a supra-agency advisory board to support the success of the Commercialization Fund modeled after DFC’s Africa Investment Advisor Program that seats a panel of experts that can continually advise both agencies on strategic priorities, key risks, and award structure, etc. It could also model elements of the Millennium Challenge Corporation’s compact model to ensure participating countries have a hand in the design of relevant aspects of the Commercialization Fund. 

USAID should additionally provide participating Commercialization Fund countries with Technical Assistance resources to ensure that host country governments can eventually take on larger management responsibilities regarding the administration of Commercialization Fund pay-for-performance contracts.

Step 4: As needed, USAID and the DFC should collaborate to provide sustainable pathways for blended financing that allows existing market providers to access working capital to scale their footprint. 

While the DFC and USAID have worked on blended finance deals in the past, the Biden Administration should explicitly direct the two agencies to work together to identify and scale the footprints and capabilities of logistics and healthcare providers in targeted Commercialization Fund countries.

Many of the existing healthcare and logistics providers that could potentially manage a greater share of global health supply chains could need additional financing to expand their operations, increase working capital, or grow their capabilities, but they often find themselves in a chicken or the egg problem to secure financing from financial institutions like the DFC. 

Traditional banks and DFC investment officers often consider these companies to be potentially risky investments because their revenue in health supply chains is not assured, especially because one of the largest healthcare payers in many LMICs is the U.S. Government, but USAID (and other global health donors) have historically funded international aid contractors to manage countries’ health supply chains, not local firms or alternative service providers. However, at the same time, USAID and other donors have not relied more on existing logistics service providers to manage health supply chains because many of these providers do not operate at the scale of larger international aid contractors.

To break this cycle, and to enable the DFC and other lenders to offer better financing terms to firms that need it to grow their capabilities or secure working capital, USAID could provide identified firms with more blended finance deals, including guaranteed eligibility to receive pay-for-performance revenue using the funding modalities described above. It could also provide unrestricted early-stage and/or phased funding to cover operational costs associated with working with the U.S. Government.

Increasing available credit to firms via the DFC and using a USAID pay-for-performance contract as collateral would also enhance firms’ overall ability to raise credit from other sources. This assurance, in turn, reduces the cost of capital for receiving firms, resulting in more significant, impactful investments from private capital in the construction of other supply chain infrastructure, including warehouses, IT systems, and shipping fleets.

Step 5: Pending success, USAID and the DFC should replicate the Commercialization Fund in additional countries. Congress should codify the Commercialization Fund into law and authorize larger-scale commercialization funds in additional geographies and sectors as part of the BUILD Act reauthorization in 2025.

While this initial Commercialization Fund will focus on building sustainable, high-performing global health supply chains in three LMICs, the same blueprint could be leveraged in other countries and in other sectors where there are robust private sectors, such as in food or power.

  1. Congress should require USAID and DFC to report overall Commercialization Fund performance every six months for a minimum of three years.
  2. If the Commercialization Fund proves successful after the first year, USAID and the DFC should proactively invite other countries to participate to expand this model to other geographies, where appropriate.
  3. If successful with healthcare supply chains, the Commercialization Fund should also be expanded to cover additional sectors and geographies and included in the BUILD Act 2025 reauthorization.

Conclusion

Continued reliance on traditional aid in commercial-ready sectors contributes to market failures, limits local agency, and minimizes the opportunity for sustainable impact.

As a team of researchers from the Carnegie Endowment’s Africa Program pointed out on the heels of the U.S.-Africa Leaders Summit, “A persistent humanitarian approach to Africa…creates pathologies of unhelpful dependency, insufficient focus on the drivers of inclusive growth, and perverse incentives for the continuation of the status quo by a small coterie of connected beneficiaries.” Those researchers identified 18 new initiatives announced at the Summit supported with public money in economic sectors that can facilitate trade, investments, entrepreneurship, and jobs creation, signaling an unprecedented readiness in this Administration to prioritize trade alongside aid. 

The Commercialization Fund outlined in this memo — a market-shaping mechanism designed to correct market failures that conventional aid models can perpetuate — has the potential to become a model for accelerating the transition of other key economic sectors away from the status quo and toward innovation, investment, impact, and long-term sustainability.

Frequently Asked Questions
Why focus on global health supply chains?

The global health supply chain is an ideal sector for USAID and the DFC to test the concept of a Commercialization Fund:


 


First, virtually every industry relies on robust supply chains to get goods around the world. There are dozens of African logistics companies that deliver goods to last-mile communities every day, including hard-to-transport items that require cold-chain storage like perishable goods and vaccines. These firms can deliver health commodities faster, cheaper, and more sustainably than traditional aid implementers, especially to last-mile communities.


Second, health supply chain performance metrics are relatively straightforward and easy to define and measure. As a result, USAID can facilitate managed competition that pays multiple logistics providers against rigorous, predetermined pay-for-performance indicators. To provide additional accountability to the taxpayer, it could withhold payment for factors such as health commodity spoilage.


Third, global health receives the largest share of USAID’s overall budget, but a significant share of those resources pay for contractor overhead and profit margin, so there is considerable opportunity to re-allocate those resources to create a pay-for-performance Supply Chain Commercialization Fund. Only about 25 percent of USAID’s in-country logistics expenditures pay for the actual work of distributing commodities to health facilities in target nations; the other 75 percent pays for larger aid contractors’ overhead, management, and other costs. Despite this premium, on-time and in-full distribution rates often miss their targets, and stockouts are still a common occurrence, according to USAID’s reports and audits.


Investing in cheaper, more efficient, and effective operators in a competitive marketplace can improve aid effectiveness and better serve target populations with essential healthcare. A Commercialization Fund can directly address policy goals of “progress over programs” by building resilient health supply chains that, once and for all, ensure patients and providers get the supplies they need on time. Since local providers can typically provide services faster, cheaper, and more sustainably than international aid contractors, transitioning to models that pay for results with fees set to prevailing local rates can also advance USAID’s localization priorities and bolster markets rather than distort them.

What is “impairment authority” and how could Administrator Power use it to create the Fund and ensure it supports outcomes-driven work regardless of organization size?

The administrator could activate her unique “impairment authority” to fashion the scope of procurement competitions at will. The fundamental concept is that if full and open competition for a contract or set of contracts—the normal process followed to fulfill the U.S. Government’s requirements—would impair foreign assistance objectives, then the administrator can divide procurements falling under the relevant category to advance an objective like localization. This authority, which is codified in USAID’s core authorizing legislation (the Foreign Assistance Act of 1961, as amended), along with a formal U.S. Government regulation, was previously used to quickly procure during Iraq reconstruction, Afghanistan humanitarian needs, and the Ebola and COVID-19 responses. While “impairment authority” may be an untested pathway for global health supply chains, it does offer the administrator a viable pathway to launch the Fund and ensure high-impact operators are receiving USAID contracts while continuing to consult with Congress to codify the Fund’s activities long-term. The administrator’s extraordinary “impairment authority” comes from 636(a)(3) of the Foreign Assistance Act and AIDAR (the USAID-specific Supplement to the FAR) Section 706.302-70 “Impairment of foreign aid programs.” See especially 706.302-70(a)(3)(ii).

How do we know countries want to work with next-generation and alternative supply chains, services, and companies, rather than traditional international aid contractors?

Many LMIC governments increasingly embrace technological solutions outside of traditional aid models because they know technology can lead to greater efficiencies, support job creation and economic development, and drive improved results for their populations. Sustaining a marketplace within a country or region is an advantage to supporting new entrants and existing firms in the sector. The impact of these companies’ services can also be scaled via pay-for-results models and domestic government spending, as the firms that deliver superior performance will rise to the top and continue to be demanded, and those that do not meet established metrics will not be contracted with again.

Who should be consulted outside of the federal government to ensure the Commercialization Fund is successful and focused on the right supply chains and technologies?

Supply chain and innovative financing experts who deeply understand the challenges plaguing global health supply chains should be consulted to design successful pay-for-results vehicles. These individuals should support the USAID/DFC tiger team to support the design and implementation framework for the Commercialization Fund, define KPIs, set appropriate pricing, and select auditors. USAID Missions and local governments will be most familiar with the unique supply chain challenges within their jurisdictions and should work alongside supply chain experts to define the desired supply chain results for the Commercialization Funds in their countries.

How are data- and evidence-driven policy integrated into the Commercialization Fund?

Through the Commercialization Fund, USAID will contract any supply chain service provider that can meet exceptionally high performance targets set by the Agency. USAID will increase its volume of business with providers that consistently hit relevant targets over consecutive months. Operators will be paid based on their performance under these contracts, providing them with predictable and consistent cash flows to grow their businesses and reach system-wide scale and impact. Based on these anticipated cash flows, DFC will be well-positioned with equity investments and able to provide upfront and working capital financing. 


As the highest-performing operators scale, they gain cost efficiencies that allow them to lower their pricing, just as with any technology adoption curve making services accessible to more customers. Over time, as clear pricing and operating standards are realized, USAID will transition from directly paying these operators for performance to supporting governments to remunerate them against transparent, auditable service contracts.


The Supply Chain Commercialization Fund will also facilitate an exchange of expertise, greater interagency learning, and long-term coordination. DFC will share with USAID how to commercialize sectors, transition them from aid to trade, and lay the groundwork for DFC deal flow, while USAID will help DFC evaluate smaller, riskier deals in sectors with fewer commercial entrants. Both institutions can use the Fund to align on clear measures of success through USAID’s contracting directly with supply chain service providers that get paid only if they hit exceptionally high performance targets and DFC’s increasing investment in companies based on their development effectiveness.

How can USAID ensure that transitioning to new partners does not create new risks that result in supply chain disruptions?

The risk of supply chain disruptions is low because the initial three countries proposed—Kenya, Ghana, and Nigeria—already have existing African-based logistics providers that provide essential health commodities to communities every day, including in last-mile and low-resourced settings. Many of these providers deliver products faster, cheaper, and more sustainably than international aid donor-funded distributors. The capacity-building fund mechanisms described above can also mitigate risks to ensure firms have the capital investment to scale their existing work to meet contract requirements.

How will the Fund’s impact be measured during and after the program?

USAID should hire third-party auditors to verify the impact and results of Fund investments. We anticipate the Agency should draw from Commercialization Fund resources to pay for these services.

Why $300 million?

While $300 million represents less than 2 percent of the overall Global Health Supply Chain suite of awards, this commitment would send important, long-term market signals for firms in partner countries over a multi-year period. It would also provide sufficient capital to scale selected companies and demonstrate how a new supply chain funding model can work.

Algorithmic Transparency Requirements for Lending Platforms Using Automated Decision Systems

Summary

Now is the time to ensure lending models offered by private companies are fair and transparent. Access to affordable credit greatly impacts quality of life and can potentially impact housing choice. Over the past decade, algorithmic decision-making has increasingly impacted the lives of American consumers. But it is important to ensure all forms of algorithmic underwriting are open to review for fairness and transparency, as inequities may appear in either access to funding or in credit terms. A recent report released by the U.S. Treasury Department speaks to the need for more oversight in the FinTech market. 

Challenge and Opportunity

The financial services sector, a historically non-technical industry, has recently and widely adopted automated platforms. Financial technology, known as “FinTech”, offers financial products and services directly to consumers by private companies or in partnership with banks and credit unions. These platforms use algorithms that are non-transparent but directly affect Americans’ ability to obtain affordable financing. Financial institutions (FIs) and mortgage brokers use predictive analytics and artificial intelligence to evaluate candidates for mortgage products, small business loans, and unsecured consumer products. Some lenders underwrite personal loans such as auto loans, personal unsecured loans, credit cards, and lines of credit with artificial intelligence. Although loans that are not government-securitized receive less scrutiny, access to credit for personal purposes impacts the debt-to-income ratios and credit scores necessary to qualify for homeownership or the global cash flow of a small business owner. Historic Home Mortgage Disclosure Act (HMDA) data and studies on small business lending demonstrate that disparate access to mortgages and small business loans occurs. This scenario will not be improved through unaudited decision automation variables, which can create feedback loops that hold the potential to scale inequities.

Forms of discrimination appear in credit approval software and can hinder access to housing. Lorena Rodriguez writes extensively about the current effect of technology on lending laws regulated by the Fair Housing Act of 1968, pointing out that algorithms have incorporated alternative credit scoring models into their decision trees. These newly selected variables have no place in determining someone’s creditworthiness. Inputs include factors like social media activity, retail spending activity, bank account balances, college of attendance, or retail spending habits. 

Traditional credit scoring models, although cumbersome, are understandable to the typical consumer who takes the time to understand how to impact their credit score. However, unlike credit scoring models, lending platforms can input a data variable with no requirement to disclose the models that impact decisioning. In other words, a consumer may never understand why their loan was approved or denied, because models are not disclosed. At the same time, it may be unclear which consumers are being solicited for financing opportunities, and lenders may target financially vulnerable consumers for profitable but predatory loans. 

Transparency around lending decision models is more necessary now than ever. The COVID-19 pandemic created financial hardship for millions of Americans. The Federal Reserve Bank of New York recently reported all-time highs in American household debt. In a rising interest rate environment, affordable and fair credit access will become even more critical to help households stabilize. Although artificial intelligence has been in use for decades, the general public is only recently beginning to realize the ethical impacts of its uses on daily life. Researchers have noted algorithmic decision-making has bias baked in, which has the potential to exacerbate racial wealth gaps and resegregate communities by race and class. While various agencies—such as the Consumer Financial Protection Bureau (CFPB), Federal Trade Commission (FTC), Financial Crimes Enforcement Network, Securities and Exchange Commission, and state regulators—have some level of authority over FinTech companies, there are oversight gaps. Although FinTechs are subject to fair lending laws, not enough is known about disparate impact or treatment, and regulation of digital financial service providers is still evolving. Modernization of policy and regulation is necessary to keep up with the current digital environment, but new legislation can address gaps in the market that existing policies may not cover.

Plan of Action

Three principles should guide policy implementation around FinTech: (1) research, (2) enforcement, (3) incentives. These principles balance oversight and transparency while encouraging responsible innovation by community development financial institutions (CDFIs) and charitable lenders that may lead to greater access to affordable credit. Interagency cooperation and the development of a new oversight body is critical because FinTech introduces complexity due to technical, trade, and financial services overlap. 

Recommendation 1: Research. The FTC should commission a comprehensive, independent research study to understand the scope and impact of disparate treatment in FinTech lending. 

To ensure equity, the study should be jointly conducted by a minimum of six research universities, of which at least two must be Historically Black Colleges and Universities, and should be designed to understand the scope and impact of fintech lending. A $3.5 million appropriation will ensure a well-designed, multiyear study. A strong understanding of the landscape of FinTech and its potential for disparate impact is necessary. Many consumers are not adequately equipped to articulate their challenges, except through complaints to agencies such as the Office of the Comptroller of Currency (OCC) and the CFPB. Even in these cases, the burden of responsibility is on the individual to be aware of channels of appeal. Anecdotal evidence suggests BIPOC borrowers and low-to-moderate income (LMI) consumers may be the target of predatory loans. For example, an LMI zip code may be targeted with FinTech ads, while product terms may be at a higher interest rate. Feedback loops in algorithms will continue to identify marginalized communities as higher risk. A consumer with lesser means who also receives a comparative triple-interest rate will remain financially vulnerable due to extractive conditions. 

Recommendation 2: Enforcement. A suite of enforcement mechanisms should be implemented.

Recommendation 3: Incentives. Develop an ethical FinTech certification that denotes a FinTech as responsible lender, such as modeled by the U.S. Treasury’s CDFI certification. 

The certification can sit with the U.S. Treasury and should create incentives for FinTechs demonstrated to be responsible lenders in forms such as grant funding, procurement opportunities, or tax credits. To create this certification, FI regulatory agencies, with input from the FTC and National Telecommunications and Information Administration, should jointly develop an interagency menu of guidelines that dictate acceptable parameters for what criteria may be input into an automated decision model for consumer lending. Guidelines should also dictate what may not be used in a lending model (example: college of attendance). Exceptions to guidelines must be documented, reviewed, and approved by the oversight body after being determined to be a legitimate business necessity. 

Conclusion

Now is the time to provide policy guidance that will prevent disparate impact and harm to minority, BIPOC, and other traditionally marginalized communities as a result of algorithmically informed biased lending practices. 

Doesn’t the CFPB regulate FinTechs?

Yes, but the CFPB’s general authority to do so is regularly challenged as a result of its independent structure. It is not clear if its authority extends to all forms of algorithmic harm, as its stated authority to regulate FinTech consumer lending is limited to mortgage and payday lending. UDAAP oversight is also less clear, as it pertains to nonregulated lenders. Additionally, the CFPB has the authority to regulate institutions over $10 billion. Many FinTechs operate below this threshold, leaving oversight gaps. Fair lending guidance through financial technology must be codified apart from the CFPB, although some oversight may continue to rest with the CFPB.

Will it be difficult to require private companies to submit reports on loan distribution?

Precedent is currently being set for regulation of small business lending data through the CFPB’s enforcement of Section 1071 of the Dodd-Frank Act. Regulation will require financial disclosure of small business lending data. Other government programs, such as the CDFI fund, currently require transaction-level reporting for lending data attached to federal funding. Over time, private company vendors are likely to develop tools to support reporting requirements around lending. Data collection can also be incentivized through mechanisms like certifications or tax credits for responsible lenders that are willing to submit data. 

Who should be responsible for regulating online lending platforms?

The OCC has proposed a charter for FinTechs that would subject them to regulatory oversight (see policy recommendation). Other FI regulators have adopted various versions of FinTech oversight. Oversight for FinTech-insured depository partnerships should remain with a primary regulatory authority for the depository with support from overarching interagency guidance. 


A new regulatory body with enforcement authority and congressional appropriations would be ideal, since FinTech is a unique form of lending that touches issues that impact consumer lending, regulation of private business, and data privacy and security.

Won’t new lending models mean expansion of access to credit for traditionally underserved consumers?

This argument is often used by payday lenders that offer products with egregious, predatory interest rates. Not all forms of access to credit are responsible forms of credit. Unless a FinTech operates as a charitable lender, its goal is profit maximization—which does not align well with consumer protection. In fact, research indicates financial inclusion promises in FinTech fall short. 

Private lenders that are not federally insured are not regulated. Why should FinTechs be regulated?

Many private lenders are regulated: Payday lenders are regulated by the CFPB once they reach a certain threshold. Pawn shops and mortgage brokers are subject to state departments for financial regulation. FinTechs also have the unique potential to have a different degree of harm because their techniques of automation and algorithmic evaluation allow for scalability and can create reinforcing feedback loops of disparate impact.

Aligning Regional Economic Development Plans with Federal Priorities

Summary

Economic development planning shouldn’t be this hard. Our planning system in the United States is highly disjointed, both from the bottom up and from the top down, and this negatively impacts our ability to build functioning, aligned, and specialized innovation ecosystems. Today, there is no single document or directive that outlines America’s economic priorities from an R&D, commercial, or economic development perspective. In addition, the organizations that carry out our economic development planning rarely include deep analysis of innovation ecosystems and opportunities for cluster development in their plans. 

The elements of a coherent innovation plan have started to appear in policy publications: for example, the 2022 National Security Strategy document outlines the need for a “modern industrial and innovation strategy,” and the biotechnology executive order, the CHIPS and Science Act, and the National Network for Critical Technology Assessment all send strong signals that a short list of industries, industrial capabilities, and strategic supply chains are critical to our country’s continued prosperity. However, while these signals might be strong, they are not yet clear and not yet strategically framed. The Office of Science and Technology Policy, in consultation with other federal agencies and non-governmental organizations, will bring together a national competitiveness plan from these disparate efforts in the coming months. Today, proponents of innovation would do well to think about the next step of this challenge: once a national competitiveness plan exists, how will it be implemented and who will lead the charge? 

Across the country, a network of regional development organizations (RDOs) regularly create and maintain economic development plans (called comprehensive economic development strategies, or CEDS) on a regional basis. At the same time, the federal government’s emphasis on building innovation ecosystems and developing regional innovation clusters has unleashed billions of dollars in funding for cluster-aligned projects. One might assume that these efforts are highly aligned and that CEDS created and maintained by RDOs provide the analysis and foundation for cluster development efforts. In reality, cluster development efforts rarely begin with a CEDS for a few key reasons: (1) CEDS are not aligned with a clear national competitiveness strategy; (2) the RDOs that create CEDS often have limited capacity to assess innovation ecosystems and even more limited resources with which to improve their capacity or conduct their analysis; and (3) existing CEDS are often hard to find (even for community members in the RDO’s district). 

Creating a better planning system will require clear, top-down guidance about competitiveness priorities, which is on its way. It will also require more sophisticated, focused, and better supported local economic planning. The U.S. Economic Development Administration (EDA) manages existing processes that allow for certification of RDOs and the regular production of CEDS. Additional guidelines and incentives should be structured into these programs in order to build our national capacity for strategic planning around shared competitiveness priorities and to ensure that regional planning processes incorporate a cohesive national framework. This will allow local cluster development efforts to best capitalize upon their respective comparative advantages, setting up communities for success as they develop plans to build stronger local economies, create better jobs, and promote sustainable growth.

Challenges

Challenge 1: Innovation ecosystem development is a form of economic development activity for which both funding and planning are highly fragmented. 

Innovation is a key part of economic development and is driven by young, dynamic firms, leading to higher levels of job creation and productivity gains. As such, the federal government has consistently taken an active role in incentivizing startup creation and growth, especially in high-tech industries. Historically, public sector tools for supporting innovation ecosystem development and startup creation have included grants, grand challenges, prize competitions, tax incentives, and loan assistance, among other mechanisms. In recent years, investments have promoted the growth of high-tech and advanced industry clusters in geographic areas outside of traditional innovation hubs like Silicon Valley in California or Boston’s Route 128 in Massachusetts. For example:

Many federal agencies provide funding for innovation ecosystem development activities. In 2018, the DoE spent $10 billion on R&D alone, and the passage of the Inflation Reduction Act (IRA) will add hundreds of billions of grant and loan support for commercialization of green technologies such as solar, wind, hydrogen, and carbon capture and storage. Beyond the DoE, the DoD’s DARPA, the Department of Homeland Security (DHS) Science & Technology Directorate, the National Science Foundation (NSF), and a host of other government agencies distribute billions in innovation funding, which has been recently buttressed by the American Rescue Plan, Inflation Reduction Act, CHIPS and Science Act, and the Infrastructure Investment and Jobs Act. These are all supported by smaller, but critically important, matching investments at the state level.

In short, innovation ecosystem development is economic development, and the federal government understands that. It has a clear national interest in prioritizing the development of certain industries in order to generate positive spillovers, correct market failures, and preserve national competitiveness. State governments and regional bodies have an interest in promoting the economic well-being of specific communities. So why is reconciling these interests across the country so difficult? The answer lies more in game theory than in politics. 

Challenge 2: Communities focus their ideas for developing innovation clusters in just a few industries and fail to give enough thought and analysis to their comparative advantage and their role in national competitiveness as they make these choices. 

When a region decides to assess its potential to develop an innovation cluster, its leaders must first decide which cluster to develop, turning to the information that is mostly easily accessible to them. This generally includes lagging metrics describing the region’s present-day economy (such as location quotient, industry-level employment, and skills concentration). In many regions of the country that do not already have a strong cluster, these metrics look very similar. It is also data that answers the wrong question. When seeking to build a cluster, regions should not just ask “What are our strengths today?” or “What industries have gotten the most press lately?” Instead, regions should ask “In which growing or emerging industries might our community have a comparative advantage?” Asking the wrong question also leads regions to end up proposing cluster efforts in a few industries (e.g., biotechnology, advanced manufacturing, and semiconductors), rather than picking a goal for cluster development in an industry that is comparatively underserved yet still vitally important (e.g., green tech, water tech, or aerospace). Even a modest concentration of assets in an underserved industry might position a region as a leading hub, and 40% of American regions cannot build identical hubs at the same time. 

For example, too many National Science Foundation Engines proposals are centered around semiconductor and microelectronic clusters. Funding to create semiconductor hubs is limited to a small number of places: recently, Commerce Secretary Gina Raimondo announced that the Department of Commerce would spend the $50 billion of CHIPS Act funds to develop at least two semiconductor hubs. However, given the scale and cost of developing semiconductor manufacturing facilities, as well as the required workforce, infrastructure, and other public services investments, only two or three additional hubs will likely be developed. Consequently, the vast majority of the 23 regions and cities that have submitted Engines applications focused on semiconductors and microelectronics will waste time and money while incurring significant opportunity costs chasing clusters that they are ill-suited to build. More importantly, however, this distracts cities and regions from making longer-term plans that they can stick to, which is essential to the long-term investments in infrastructure, education and training, housing, and land permitting, among others, that are needed to promote innovation.

While we have the systems and processes to support a massive push to integrate competitiveness priorities into local development plans, both the system and the organizations it funds have limited bandwidth and even more limited resources. Policymakers must also balance the need for increased attention to national competitiveness with the tradition of local control that is core to the American way. There is no appetite for central planning in the United States, but there is a desperate need for clear, shared priorities that allow each region to determine how their community can best serve a higher, patriotic purpose.

Challenge 3: The organizations responsible for economic planning (RDOs) need to improve their internal capacity to plan for innovation ecosystem development, which will require additional resources. 

It is easy to imagine a world in which RDOs take the lead on improving the quality of CEDS planning, and efforts led by the National Association for Development Organizations (NADO) Research Foundation are in place to do just that. In addition to managing an EDA-funded community of practice for RDOs, which includes maintaining resources and conducting webinar trainings, the NADO Research Foundation independently maintains CEDS Central, an excellent repository of best practices. While these resources and their consistent use demonstrate communities’ desires to plan well, they alone have not yet led to the widespread use of CEDS as a means of detailed cluster analysis and planning. 

When looking at any one individual RDO, it is easy to see why. RDOs (also called Councils of Governments, Economic Development Districts, Regional Development Districts, or Regional Planning Organizations) have incredibly broad planning responsibilities and limited staffing and resources. The CEDS that they manage reflect these broad remits and often include elements related to broadband access, transportation, aging population services, housing, education, and employment and economic growth. As a result, there is very little capacity to create clear and detailed innovation plans. Of the organizations whose plans NADO listed as exemplary on their CEDS Central site, the average total staff size was 17 with an average of three employees dedicated to economic development. Moreover, no employees were dedicated to innovation ecosystems, entrepreneurship, or cluster development. 

In order for RDOs to build their capacity for creating regional cluster development plans, they must train and hire staff with new capabilities. This is nearly impossible for these organizations to do on their own, given their current financial resources and the breadth of demands on their time. Changing that will require dedicated funding for new staff and training, as well as a clear directive to prioritize this work. 

Challenge 4: Many regional, local, state, and nongovernmental stakeholders participate in de facto economic planning activities. However, these are not universally integrated with RDO efforts, and transparency is a key barrier. 

The innovation funding picture is further complicated by a long tail of regional, local, and state players. There are over 520 RDOs in the United States. However, only 23 RDOs have published digital CEDS, indicating that these critical planning documents are not yet widely produced, or at least not widely shared, by local and regional stakeholders. In addition, there is no publicly accessible central repository of active CEDS. Providing such a resource could facilitate greater community alignment and better understanding of communities’ comparative advantage across the country. 

In addition, a wide range of private and social sector bodies participate in innovation planning and regional development. Incubators such as the Boston-based MassVentures provide venture funding but also support technology transfer, mentorship, and small business innovation research (SBIR) support. Industry trade organizations, local chambers of commerce, and large nonprofits lobby for regulatory change, help their constituents navigate government resources, and encourage informal planning. Without meaningful transparency in the CEDS process, these groups will struggle to align their activities with regional plans.

Transparency alone will not fix a highly fragmented system, but it will give groups that are inclined to seek alignment the opportunity to do so. It also allows the opportunity for more federal programs (including EDA’s own innovation programs) to require that applicants speak to alignment with their regional CEDS in more detailed ways during the application process and include alignment with CEDS as an evaluation criterion when applications are reviewed. 

Opportunity

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Figure 1: NCSES – Although total R&D as a percentage of GDP has increased over time, public investment has dramatically decreased. Source: National Center for Science and Engineering Statistics, National Patterns of R&D Resources (annual series), 2023 (accessed 21 March 2023).  

R&D is at the core of innovation, and the United States has excelled compared to its peers and competitors. Both the European Union and China have struggled to reach the benchmark level of 2% of gross domestic product (GDP) invested in R&D, giving the United States a huge edge in cutting-edge technologies such as biotechnology, clean tech, and software. However, the decline in public R&D spending, which was over 1% of GDP in the 1970s but is now down to ~0.7%, has significant repercussions for competitiveness in emerging technologies that require significant public investment to overcome developmental hurdles. For example, China was first to launch a quantum encryption satellite, and by 2030 China is projected to have 25% of semiconductor manufacturing capacity, compared to just 10% in the United States.

Figure 2: OECD – Gross domestic expenditure on R&D (GERD), selected economies, 2000-21.
US dollar (USD) billion in constant purchasing power parity (PPP) prices. Source: OECD R&D statistics, February 2023 (accessed on 21 March 2023).

To be clear, the United States retains a large quantitative and qualitative advantage in R&D and innovation, buttressed by a world-leading university system and large and growing private investments. Gross expenditures are increasing in the United States. However, private sector R&D is largely geared toward commercialization rather than developments in basic science given different incentives and time horizons. Economists have long recognized the market failures in early-stage R&D: private sector firms do not consider the positive social spillovers in investment, leading to suboptimal investment levels. The government is better able to justify the total social impact of investing in innovation.

Increasing the amount of public R&D and ecosystem spending, which includes workforce development and infrastructure, is crucial to accelerating American innovation. The $500 million appropriated in the FY23 omnibus spending bill for EDA’s Regional Technology and Innovation Hubs is a good start, but this is only a fraction of the amount proposed by the CHIPS Act. However, there is bipartisan agreement in favor of regional cluster building, most recently demonstrated by the December 2022 House Subcommittee on Research and Technology hearing on Building Regional Innovation Economies.

In addition to growing the cumulative effectiveness of national innovation spending, regionally based cluster development plans will distribute economic prosperity more equitably. In 2021, the United States invested nearly $350 billion in venture capital dollars. However, nearly $250 billion went to just three states: California, New York, and Massachusetts. While these three states are home to some of the nation’s largest, most productive, and best-educated cities, other regions also have budding clusters and compelling competitive advantages that deserve more financial and human capital. A well-structured innovation roadmap that starts with national priorities, incorporates local advantages, and encourages transparency will help public, private, and nonprofit stakeholders at the regional level develop long-term investment plans. In turn, this will enable a greater number of regions and individuals to reap the economic benefits of innovation, create good jobs, and increase standards of living.

Plan of Action

Recommendation 1: Direct, align, and coordinate innovation ecosystem development activities more clearly at the federal level. 

Better coordination of innovation spending starts at the top. Regions, states, and cities would benefit from greater clarity in the direction of U.S. priorities regarding innovation. This is especially true for technologies and sectors that are critical to national competitiveness, require significant upfront R&D, and have large spillover benefits.

Recommendation 2: Direct RDOs to include detailed innovation and cluster planning in the CEDS process. The EDA should update CEDS Content Guidelines to require that plans address opportunities to build innovation ecosystems and develop local clusters, as they have to require that plans include resilience measures. These plans should include:

Recommendation 3: Give RDOs the resources needed to include detailed innovation and cluster planning in the CEDS process. Congress should authorize annual funds to support the placement of senior innovation and cluster leaders in RDOs as Regional Competitiveness Officers (RECOs). This program should be administered by the EDA or its designee and be modeled on the Economic Recovery Corps fellowships. This will build staff capacity to help coordinate the development of regional strategies that cut across state and city lines such that innovation planning becomes a regular facet of economic development policy.

The EDA should provide innovation ecosystems and cluster research training through its existing community of practice for RDOs to invest in developing innovation strategies as a component of their CEDS process.  

Recommendation 4: Facilitate local alignment through greater CEDS transparency and require that federally funded cluster development initiatives to ask applicants to demonstrate alignment with their regional CEDS as they apply. 

Conclusion

The approach proposed here will facilitate the development of a coordinated national approach to innovation policy. Adopting this approach will help regions make better investments in their industry clusters, help private sector investors more productively channel funding into strategically vital areas, and accelerate the growth of high-quality jobs. Strengthening innovation planning will benefit all Americans by accelerating economic development, expanding local economic clusters, and generating middle-class employment that builds communities.

Meeting Agricultural Sustainability Goals by Increasing Federal Funding for Research on Genetically Engineered Organisms

Summary

Ensuring the sustainability and resiliency of American food systems is an urgent priority, especially in the face of challenges presented by climate change and international geopolitical conflicts. To address these issues, increased federal investment in new, sustainability-oriented agricultural technology is necessary in order to bring greater resource conservation and stress tolerance to American farms and fields. Ongoing advances in bioengineering research and development (R&D) offer a diverse suite of genetically engineered organisms, including crops, animals, and microbes. Given the paramount importance of a secure food supply for national well-being, federal actors should promote the development of genetically engineered organisms for agricultural applications. 

Two crucial opportunities are imminent. First, directives in the Biden Administration’s bioeconomy executive order provide the U.S. Department of Agriculture (USDA) a channel through which to request funding for sustainability-oriented R&D in genetically engineered organisms. Second, renewal of the Farm Bill in 2023 provides a venue for congressional legislators to highlight genetic engineering as a funding focus area of existing research grant programs. Direct beneficiaries of the proposed federal funding will predominantly be nonprofit research organizations such as land grant universities; innovations resulting from the funded research will provide a public good that benefits producers and consumers alike. 

Challenge and Opportunity

The resiliency of American agriculture faces undeniable challenges in the coming decades. The first is resource availability, which includes scarcities of fertile land due to soil degradation and of water due to overuse and drought. Resource availability is also vulnerable to acute challenges, as revealed by the impact of the COVID-19 pandemic and the Russian-Ukraine war on the supply of vital inputs such as fertilizer and gas. The second set of challenges are environmental stressors, many of which are exacerbated by climate change. Flooding can wipe out an entire harvest, while the spread of pathogens poses existential risks not only to individual livelihoods but also to the global market of crops like citrus, chocolate, and banana. Such losses would be devastating for both consumers and producers, especially those in the global south. 

Ongoing advances in bioengineering R&D provide technological solutions in the form of a diverse suite of genetically engineered organisms. These have the potential to address many of the aforementioned challenges, including increasing yield and/or minimizing inputs and boosting resilience to drought, flood, and pathogens. Indeed, existing transgenic crops, such as virus-resistant papaya and flood-tolerant rice, demonstrate the ability of genetically engineered organisms to address agricultural challenges. They can also address other national priorities such as climate change and nutrition by enhancing carbon sequestration and improving the nutritional profile of food. 

Recent breakthroughs in modifying and sequencing DNA have greatly enhanced the speed of developing new, commercializable bioengineered varieties, as well as the spectrum of traits and plants that can be engineered. This process has been especially expedited by the use of CRISPR gene-editing technology; the European Sustainable Agriculture Through Genome Editing (EU-SAGE)’s database documents more than 500 instances of gene-edited crops developed in research laboratories to target traits for sustainable, climate-resilient agriculture. There is thus vast potential for genetically engineered organisms to contribute to sustainable agriculture. 

More broadly, this moment can be leveraged to bring about a turning point in the public perception of genetically engineered organisms. Past generations of genetically engineered organisms have been met with significant public backlash, despite the pervasiveness of inter-organism gene transfer throughout the history of life on earth (see FAQ). Reasons for negative public perception are complex but include the association of genetically engineered organisms with industry profit, as well as an embrace of the precautionary principle to a degree that far exceeds its application to other products, such as pharmaceuticals and artificial intelligence. Furthermore, persistent misinformation and antagonistic activism have engendered entrenched consumer distrust. The prior industry focus on herbicide resistance traits also contributed to the misconception that the technology is only used to increase the use of harmful chemicals in the environment. 

Now, however, a new generation of genetically engineered organisms feature traits beyond herbicide resistance that address sustainability issues such as reduced spoilage. Breakthroughs in DNA sequencing, as well as other analytical tools, have increased our understanding of the properties of newly developed organisms. There is pervasive buy-in for agricultural sustainability goals across many stakeholder sectors, including individual producers, companies, consumers, and legislators on both sides of the aisle. There is great potential for genetically engineered organisms to be accepted by the public as a solution to a widely recognized problem. Dedicated federal funding will be vital in seeing that this potential is realized.

Plan of Action

Recommendation 1: Fund genetically engineered organisms pursuant to the Executive Order on the bioeconomy.

Despite the importance of agriculture for the nation’s basic survival and the clear impact of agricultural innovation, USDA’s R&D spending pales in comparison to other agencies and other expenditures. In 2022, for example, USDA’s R&D budget was a mere 6% of the National Institutes of Health’s R&D budget, and R&D comprised only 9.6% of USDA’s overall discretionary budget. The Biden Administration’s September 2022 executive order provides an opportunity to amend this funding shortfall, especially for genetically engineered organisms.  

The Executive Order on Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure American Bioeconomy explicitly embraces an increased role for biotechnology in agriculture. Among the policy objectives outlined is the call to “boost sustainable biomass production and create climate-smart incentives for American agricultural producers and forest landowners.” 

Pursuant to this objective, the EO directs the USDA to submit a plan comprising programs and budget proposals to “support the resilience of the United States biomass supply chain [and] encourage climate-smart production” by September 2023. This plan provides the chance for the USDA to secure funding for agricultural R&D in a number of areas. Here, we recommend (1) USDA collaboration in Department of Energy (DoE) research programs amended under the CHIPS and Science Act and (2) funding for startup seed grants. 

CHIPS and Science Act

The 2022 CHIPS and Science Act aims to accelerate American innovation in a number of technology focus areas, including engineering biology. To support this goal, the Act established a new National Engineering Biology Research and Development Initiative (Section 10402). As part of this initiative, the USDA was tasked with supporting “research and development in engineering biology through the Agricultural Research Service, the National Institute of Food and Agriculture programs and grants, and the Office of the Chief Scientist.” Many of the initiative’s priorities are sustainability-oriented and could benefit from genetic engineering contributions. 

A highlight is the designation of an interagency committee to coordinate activities. To leverage and fulfill this mandate, we recommend that the USDA better coordinate with the DoE on bioengineering research. Specifically, the USDA should be involved in the decision-making process for awarding research grants relating to two DoE programs amended by the Act.

The first program is the Biological and Environmental Research Program, which includes carbon sequestration, gene editing, and bioenergy. (See the Appendix for a table summarizing examples of how genetic engineering can contribute sustainability-oriented technologies to these key focus areas.)

The second program is the Basic Energy Sciences Program, which has authorized funding for a Carbon Sequestration Research and Geologic Computational Science Initiative under the DoE. Carbon sequestration via agriculture is not explicitly mentioned in this section, but this initiative presents another opportunity for the USDA to collaborate with the DoE and secure funding for agricultural climate solutions. Congress should make appropriating funding for this program a priority.

Seed Grants

The USDA should pilot a seed grant program to accelerate technology transfer, a step that often poses a bottleneck. The inherent risk of R&D and entrepreneurship in a cutting-edge field may pose a barrier to entry for academic researchers as well as small agricultural biotech companies. Funding decreases the barrier of entry, thus increasing the diversity of players in the field. This can take the form of zero-equity seed grants. Similar to the National Science Foundation (NSF)’s seed grant program, which awards $200+ million R&D funding to about 400 startups, this would provide startups with funding without the risks attached to venture capital funding (such as being ousted from company leadership). The NSF’s funding is spread across numerous disciplines, so a separate agricultural initiative from the USDA dedicated to supporting small agricultural biotech companies would be beneficial. These seed grants would meet a need unmet by USDA’s existing small business grant programs, which are only awarded to established companies.

Together, the funding areas outlined above would greatly empower the USDA to execute the EO’s objective of promoting climate-smart American agriculture.

Recommendation 2: Allocate funding through the 2023 Farm Bill.

The Farm Bill, the primary tool by which the federal government sets agricultural policy, will be renewed in 2023. Several existing mandates for USDA research programs, administered through the National Institute of Food and Agriculture as competitive grants, have been allocated federal funding. Congressional legislators should introduce amendments in the mandates for these programs such that the language explicitly highlights R&D of genetically engineered organisms for sustainable agriculture applications. Such programs include the Agriculture and Food Research Initiative, a major competitive grant program, as well as the Specialty Crop Research Initiative and the Agricultural Genome to Phenome Initiative. Suggested legislative text for these amendments are provided in the Appendix. Promoting R&D of genetically engineered organisms via existing programs circumvents the difficulty of securing appropriations for new initiatives while also presenting genetically engineered organisms as a critically important category of agricultural innovation.

Additionally, Congress should appropriate funding for the Agriculture Advanced Research and Development Authority (AgARDA) at its full $50 million authorization. Similar to its counterparts in other agencies such as ARPA-E and DARPA, AgARDA would enable “moonshot” R&D projects that are high-reward but high-risk or have a long timeline—such as genetically engineered organisms with genetically complex traits. This can be especially valuable for promoting the development of sustainability-oriented crops traits: though they are a clear public good, they may be less profitable and/or marketable than crops with consumer-targeted traits such as sweetness or color, and as such profit-driven companies may be dissuaded from investing in their development. The USDA just published its implementation strategy for AgARDA. Congress must now fully fund AgARDA such that it can execute its strategy and fuel much-needed innovation in agricultural biotechnology. 

Conclusion

Current federal funding for genetically engineered organism R&D does not reflect their substantial impact in ensuring a sustainable, climate-smart future for American agriculture, with applications ranging from increasing resource-use efficiency in bioproduction to enhancing the resilience of food systems to environmental and manmade crises. Recent technology breakthroughs have opened many frontiers in engineering biology, but free market dynamics alone are not sufficient to guarantee that these breakthroughs are applied in the service of the public good in a timely manner. The USDA and Congress should therefore take advantage of upcoming opportunities to secure funding for genetic engineering research projects.

Appendix

Biological and Environmental Research Program Examples 

Research focus area added in CHIPS and Science ActExample of genetic engineering contribution
Bioenergy and biofuelOptimizing biomass composition of bioenergy crops
Non-food bioproductsLab-grown cotton; engineering plants and microbes to produce medicines
Carbon sequestrationImproving photosynthetic efficiency; enhancing carbon storage in plant roots
Plant and microbe interactionsEngineering microbes to counter plant pathogens; engineering microbes to make nutrients more accessible to plants
BioremediationEngineering plants and microbes to sequester and/or breakdown contaminants in soil and groundwater
Gene editing Engineering plants for increased nutrient content, disease-resistance, storage performance
New characterization toolsCreating molecular reporters of plant response to abiotic and biotic environmental dynamics 

Farm Bill Amendments 

Agriculture and Food Research Initiative

One of the Agriculture and Food Research Initiative (AFRI)’s focus areas is Sustainable Agricultural Systems, with topics including “advanced technology,” which supports “cutting-edge research to help farmers produce higher quantities of safer and better quality food, fiber, and fuel to meet the needs of a growing population.” Furthermore, AFRI’s Foundational and Applied Science Program supports grants in priority areas including plant health, bioenergy, natural resources, and environment. The 2023 Farm Bill could amend the Competitive, Special, and Facilities Research Grant Act (7 U.S.C. 3157) to highlight the potential of genetic engineering in the pursuit of AFRI’s goals. 

Example text: 

Subsection (b)(2) of the Competitive, Special, and Facilities Research Grant Act (7 U.S.C. 3157(b)(2)) is amended—

(1) in subparagraph (A)—

(A) in clause (ii), by striking the semicolon at the end and inserting “including genetic engineering methods to make modifications (deletions and/or insertions of DNA) to plant genomes for improved food quality, improved yield under diverse growth conditions, and improved conservation of resource inputs such as water, nitrogen, and carbon;”;

(B) in clause (vi), by striking the “and”;

(C) in clause (vii), by striking the period at the end and inserting “; and”; and

(D) by adding at the end the following: 

“(viii) plant-microbe interactions, including the identification and/or genetic engineering of microbes beneficial for plant health”

(2) in subparagraph (C), clause (iii), by inserting “production and” at the beginning;

(3) in subparagraph (D)– 

(A) in clause (vii), by striking “and”;

(B) in clause (vii), by striking the period at the end and inserting “; and”; and

(C) by adding at the end the following: 

“(ix) carbon sequestration”.

Agricultural Genome to Phenome Initiative

The goal of this initiative is to understand the function of plant genes, which is critical to crop genetic engineering for sustainability. The ability to efficiently insert and edit genes, as well as to precisely control gene expression (a core tenet of synthetic biology), would facilitate this goal.

Example text:

Section 1671(a) of the Food, Agriculture, Conservation, and Trade Act of 1990 (7 U.S.C. 5924(a)) is amended—

  1. In subparagraph (4), by inserting “and environmental” after “achieve advances in crops and animals that generate societal”; and
  2. In subparagraph (5), by inserting “genetic engineering, synthetic biology,” after “to combine fields such as genetics, genomics,”

Specialty Crop Research Initiative

Specialty crops can be a particularly fertile ground for research. There is a paucity of genetic engineering tools for specialty crops as compared to major crops (e.g. wheat, corn, etc.). At the same time, specialty crops such as fruit trees offer the opportunity to effect larger sustainability impacts: as perennials, they remain in the soil for many years, with particular implications for water conservation and carbon sequestration. Finally, economically important specialty crops such as oranges are under extreme disease threat, as identified by the Emergency Citrus Disease Research and Extension Program. Genetic engineering offers potential solutions that could be accelerated with funding. 

Example text:

Section 412(b) of the Agricultural Research, Extension, and Education Reform Act of 1998 (7 U.S.C. 7632(b)) is amended—

  1. In paragraph (1), by inserting “transgenics, gene editing, synthetic biology” after “research in plant breeding, genetics,” and—
    1. In subparagraph (B), by inserting “and enhanced carbon sequestration capacity” after “size-controlling rootstock systems”; and
    2. In subparagraph (C), by striking the semi-colon at the end and inserting “, including water-use efficiency;”
Frequently Asked Questions
What is the definition of a genetically engineered organism? What is the difference between genetically engineered, genetically modified, transgenic, gene-edited, and bioengineered?

Scientists usually use the term “genetic engineering” as a catch-all phrase for the myriad methods of changing an organism’s DNA outside of traditional breeding, but this is not necessarily reflected in usage by regulatory agencies. The USDA’s glossary, which is not regulatorily binding, defines “genetic engineering” as “​​manipulation of an organism’s genes by introducing, eliminating or rearranging specific genes using the methods of modern molecular biology, particularly those techniques referred to as recombinant DNA techniques.” Meanwhile, the USDA’s Animal and Plant Health Inspection Service (APHIS)’s 2020 SECURE rule defines “genetic engineering” as “techniques that use recombinant, synthesized, or amplified nucleic acids to modify or create a genome.” The USDA’s glossary defines “genetic modification” as “the production of heritable improvements in plants or animals for specific uses, via either genetic engineering or other more traditional methods”; however, the USDA National Organic Program has used “genetic engineering” and “genetic modification” interchangeably. 


“Transgenic” organisms can be considered a subset of genetically engineered organisms and result from the insertion of genetic material from another organism using recombinant DNA techniques. “Gene editing” or “genome editing” refers to biotechnology techniques like CRISPR that make changes in a specific location in an organism’s DNA. 


The term “bioengineered” does carry regulatory weight. The USDA-AMS’s National Bioengineered Food Disclosure Standard (NBFDS), published in 2018 and effective as of 2019, defines “bioengineered” as “contains genetic material that has been modified through in vitro recombinant deoxyribonucleic acid (DNA) techniques; and for which the modification could not otherwise be obtained through conventional breeding or found in nature.” Most gene-edited crops currently in development, such as those where the introduced gene is known to occur in the species naturally, are exempt from regulation under both the AMS’s NBFDS and APHIS’s SECURE acts.

What are some examples of genetic engineering methods?

Though “genetic engineering” has only entered the popular lexicon in the last several decades, humans have modified the genomes of plants for millennia, in many different ways. Through genetic changes introduced via traditional breeding, teosinte became maize 10,000 years ago in Mesoamerica, and hybrid rice was developed in 20th-century China. Irradiation has been used to generate random mutations in crops for decades, and the resulting varieties have never been subject to any special regulation.


In fact, transfer of genes between organisms occurs all the time in nature. Bacteria often transfer DNA to other bacteria, and some bacteria can insert genes into plants. Indeed, one of the most common “genetic engineering” approaches used today, Agrobacterium-mediated gene insertion, was inspired by that natural phenomenon. Other methods of DNA delivery including biolistics (“gene gun”) and viral vectors. Each method for gene transfer has many variations, and each method varies greatly in its mode of action and capabilities. This is key for the future of plant engineering: there is a spectrum—not a binary division—of methods, and evaluations of engineered plants should focus on the end product.

How are genetically engineered organisms regulated in the United States?

Genetically engineered organisms are chiefly regulated by USDA-APHIS, the EPA, and the FDA as established by the 1986 Coordinated Framework for the Regulation of Biotechnology. They oversee experimental testing, approval, and commercial release. The Framework’s regulatory approach is grounded in the judgment that the potential risks associated with genetically engineered organisms can be evaluated the same way as those associated with traditionally bred organisms. This is in line with its focus on “the characteristics of the product and the environment into which it is being introduced, not the process by which the product is created.”


USDA-APHIS regulates the distribution of regulated organisms that are products of biotechnology to ensure that they do not pose a plant pest risk. Developers can petition for individual organisms, including transgenics, to be deregulated via Regulatory Status Review.


The EPA regulates the distribution, sale, use, and testing of all pesticidal substances produced in plants and microbes, regardless of method of production or mode of action. Products must be registered before distribution. 


The FDA applies the same safety standards to foods derived from genetically engineered organisms as it does to all foods under the Federal Food, Drug, and Cosmetic Act. The agency provides a voluntary consultation process to help developers ensure that all safety and regulatory concerns, such as toxicity, allergenicity, and nutrient content, are resolved prior to marketing.

How do genetically engineered crops work?

Mechanisms of action vary depending on the specific trait. Here, we explain the science behind two types of transgenic crops that have been widespread in the U.S. market for decades. 


Bt crops: Three of the major crops grown in the United States have transgenic Bt varieties: cotton, corn, and soybean. Bt crops are genetically engineered such that their genome contains a gene from the bacteria Bacillus thuringiensis. This enables Bt crops to produce a protein, normally only produced by the Bt bacteria, that is toxic to a few specific plant pests but harmless for humans, other mammals, birds, and beneficial insects. In fact, the bacteria itself is approved for use as an organic insecticide. However, organic applications of Bt insecticides are limited in efficacy: since the bacteria must be topically applied to the crop, the protein it produces is ineffective against insects that have penetrated the plant or are attacking the roots; in addition, the bacteria can die or be washed away by rain. 


Engineering the crop itself to produce the insecticidal protein more reliably reduces crop loss due to pest damage, which also minimizes the need for other, often more broadly toxic systemic pesticides. Increased yield allows for more efficient use of existing agricultural land. In addition, decreased use of pesticides reduces the energy cost associated with their production and application while also preserving wildlife biodiversity. With regards to concerns surrounding insecticide resistance, the EPA requires farmers who employ Bt, both as a transgenic crop and as an organic spray, to also plant a refuge field of non-Bt crops, which prevents pests from developing resistance to the Bt protein.


The only substantive difference between Bt crops and non-Bt crops is that the former produces an insecticide already permitted by USDA organic regulations. 


Ringspot-resistant rainbow papaya: The transgenic rainbow papaya is another example of the benefits of genetic engineering in agriculture. Papaya plantations were ravaged by the papaya ringspot virus in the late 1900s, forcing many farmers to abandon their lands and careers. In response, scientists developed the rainbow papaya, which contains a gene from the virus itself that allows it to express a protein that counters viral infection. This transgenic papaya was determined to be equivalent in nutrition and all other aspects to the original papaya. The rainbow papaya, with its single gene insertion, is widely considered to have saved Hawaii’s papaya industry, which in 2013 accounted for nearly 25% of Hawaii’s food exports. Transgenic papaya now makes up about 80% of the Hawaiian papaya acreage. The remaining comprise non-GMO varieties, which would have gone locally extinct had it not been for transgenic papayas preventing the spread of the virus. The rainbow papaya’s success has clearly demonstrated that transgenic crops can preserve the genetic diversity of American crops and preserve yield without spraying synthetic pesticides, both of which are stated goals of the USDA Organic Program. However, the National Organic Program’s regulations currently forbid organic farmers from growing virus-resistant transgenic papaya.

How have recent biotechnology breakthroughs accelerated the development of new crops?

With the advent of CRISPR gene-editing technology, which allows scientists to make precise, targeted changes in an organism’s DNA, new genetically engineered crops are being developed at an unprecedented pace. These new varieties will encompass a wider variety of qualities than previously seen in the field of crop biotechnology. Many varieties are directly aimed at shoring up agricultural resilience in the face of climate change, with traits including tolerance to heat, cold, and drought. At the same time, the cost of sequencing an organism’s DNA continues to decrease. This makes it easier to confirm the insertion of multiple transgenes into a plant, as would be necessary to engineer crops to produce a natural herbicide. Such a crop, similar to Bt crops but targeting weeds instead of insects, would reduce reliance on synthetic herbicides while enabling no-till practices that promote soil health. Furthermore, cheap DNA sequencing facilitates access to information about the genomes of many wild relatives of modern crops. Scientists can then use genetic engineering to make wild relatives more productive or introduce wild traits like drought resilience into domesticated varieties. This would increase the genetic diversity of crops available to farmers and help avoid issues inherent to monocultures, most notably the uncontrollable spread of plant diseases. 


At present, most crops engineered with CRISPR technology do not contain genes from a different organism (i.e., not transgenic), and thus do not have to face the additional regulatory hurdles that transgenics like Bt crops did. However, crops developed via CRISPR are still excluded from organic farming.

What are examples of genetically engineered organisms currently on the market or in active development that address sustainability issues?

  • Improving sustainability and land conservation: potatoes that are slower to spoil, wheat with enhanced carbon sequestration capacity 

  • Increasing food quality and nutrition: vegetables with elevated micronutrient content 

  • Increasing and protecting agricultural yields: higher-yield fish, flood-tolerant rice

  • Protecting against plant and animal pests and diseases: blight-resistant chestnut, HLB-resistant citrus

  • Cultivating alternative food sources: bacteria for animal-free production of protein

Which agricultural stakeholders are engaged in genetic engineering R&D and will benefit from federal funding?

The pool of producers of genetically engineered crops is increasingly diverse. In fact, of the 37 new crops evaluated by APHIS’s Biotechnology Regulatory Service under the updated guidelines since 2021, only three were produced by large (>300 employees) for-profit corporations. Many were produced by startups and/or not-for-profit research institutions. USDA NIFA research grants predominantly fund land-grant universities; other awardees include private nonprofit organizations, private universities, and, in select cases (such as small business grants), private for-profit companies.

Why are GMOs so often vilified?

Historically, the concept of GMOs has been associated with giant multinational corporations, the so-called Big Ag. The most prevalent GMOs in the last several decades have indeed been produced by industry giants such as Dow, Bayer, and Monsanto. This association has fueled the negative public perception of GMOs in several ways, including: 



  • Some companies, such as Dow, were responsible for producing the notorious chemical Agent Orange, used to devastating effect in the Vietnam War. While this is an unfortunate shadow on the company, it is unrelated to the properties of genetically engineered crops.

  • Companies have been accused of financially disadvantaging farmers by upholding patents on GMO seeds, which prevents farmers from saving seeds from one year’s crop to plant the next season. Companies have indeed enforced seed patents (which generally last about 20 years), but it is important to note that (1) seed-saving has not been standard practice on many American farms for many decades, since the advent of (nonbioengineered) hybrid crops, from which saved seeds will produce an inferior crop, and (2) bioengineered seeds are not the only seeds that can be and are patented.

How to Replicate the Success of Operation Warp Speed

Summary

Operation Warp Speed (OWS) was a public-private partnership that produced COVID-19 vaccines in the unprecedented timeline of less than one year. This unique success among typical government research and development (R&D) programs is attributed to OWS’s strong public-private partnerships, effective coordination, and command leadership structure. Policy entrepreneurs, leaders of federal agencies, and issue advocates will benefit from understanding what policy interventions were used and how they can be replicated. Those looking to replicate this success should evaluate the stakeholder landscape and state of the fundamental science before designing a portfolio of policy mechanisms.

Challenge and Opportunity

Development of a vaccine to protect against COVID-19 began when China first shared the genetic sequence in January 2020. In May, the Trump Administration announced OWS to dramatically accelerate development and distribution. Through the concerted efforts of federal agencies and private entities, a vaccine was ready for the public in January 2021, beating the previous record for vaccine development by about three years. OWS released over 63 million doses within one year, and to date more than 613 million doses have been administered in the United States. By many accounts, OWS was the most effective government-led R&D effort in a generation.

Policy entrepreneurs, leaders of federal agencies, and issue advocates are interested in replicating similarly rapid R&D to solve problems such as climate change and domestic manufacturing. But not all challenges are suited for the OWS treatment. Replicating its success requires an understanding of the unique factors that made OWS possible, which are addressed in Recommendation 1. With this understanding, the mechanisms described in Recommendation 2 can be valuable interventions when used in a portfolio or individually.

Plan of Action

Recommendation 1. Assess whether (1) the majority of existing stakeholders agree on an urgent and specific goal and (2) the fundamental research is already established. 

Criteria 1. The majority of stakeholders—including relevant portions of the public, federal leaders, and private partners—agree on an urgent and specific goal.

The OWS approach is most appropriate for major national challenges that are self-evidently important and urgent. Experts in different aspects of the problem space, including agency leaders, should assess the problem to set ambitious and time-bound goals. For example, OWS was conceptualized in April and announced in May, and had the specific goal of distributing 300 million vaccine doses by January. 

Leaders should begin by assessing the stakeholder landscape, including relevant portions of the public, other federal leaders, and private partners. This assessment must include adoption forecasts that consider the political, regulatory, and behavioral contexts. Community engagement—at this stage and throughout the process—should inform goal-setting and program strategy. Achieving ambitious goals will require commitment from multiple federal agencies and the presidential administration. At this stage, understanding the private sector is helpful, but these stakeholders can be motivated further with mechanisms discussed later. Throughout the program, leaders must communicate the timeline and standards for success with expert communities and the public.

Example Challenge: Building Capability for Domestic Rare Earth Element Extraction and Processing
Rare earth elements (REEs) have unique properties that make them valuable across many sectors, including consumer electronics manufacturing, renewable and nonrenewable energy generation, and scientific research. The U.S. relies heavily on China for the extraction and processing of REEs, and the U.S. Geological Survey reports that 78% of our REEs were imported from China from 2017-2020. Disruption to this supply chain, particularly in the case of export controls enacted by China as foreign policy, would significantly disrupt the production of consumer electronics and energy generation equipment critical to the U.S. economy. Export controls on REEs would create an urgent national problem, making it suitable for an OWS-like effort to build capacity for domestic extraction and processing.

Criteria 2. Fundamental research is already established, and the goal requires R&D to advance for a specific use case at scale.

Efforts modeled after OWS should require fundamental research to advance or scale into a product. For example, two of the four vaccine platforms selected for development in OWS were mRNA and replication-defective live vector platforms, which had been extensively studied despite never being used in FDA-licensed vaccines. Research was advanced enough to give leaders confidence to bet on these platforms as candidates for a COVID-19 vaccine. To mitigate risk, two more-established platforms were also selected.

Technology readiness levels (TRLs) are maturity level assessments of technologies for government acquisition. This framework can be used to assess whether a candidate technology should be scaled with an OWS-like approach. A TRL of at least five means the technology was successfully demonstrated in a laboratory environment as part of an integrated or partially integrated system. In evaluating and selecting candidate technologies, risk is unavoidable, but decisions should be made based on existing science, data, and demonstrated capabilities.

Example Challenge: Scaling Desalination to Meet Changing Water Demand
Increases in efficiency and conservation efforts have largely kept the U.S.’s total water use flat since the 1980s, but drought and climate variability are challenging our water systems. Desalination, a well-understood process to turn seawater into freshwater, could help address our changing water supply. However, all current desalination technologies applied in the U.S. are energy intensive and may negatively impact coastal ecosystems. Advanced desalination technologies—such as membrane distillation, advanced pretreatment, and advanced membrane cleaning, all of which are at technology readiness levels of 5–6—would reduce the total carbon footprint of a desalination plant. An OWS for desalination could increase the footprint of efficient and low-carbon desalination plants by speeding up development and commercialization of advanced technologies.

Recommendation 2: Design a program with mechanisms most needed to achieve the goal: (1) establish a leadership team across federal agencies, (2) coordinate federal agencies and the private sector, (3) activate latent private-sector capacities for labor and manufacturing, (4) shape markets with demand-pull mechanisms, and (5) reduce risk with diversity and redundancy.

Design a program using a combination of the mechanisms below, informed by the stakeholder and technology assessment. The organization of R&D, manufacturing, and deployment should follow an agile methodology in which more risk than normal is accepted. The program framework should include criteria for success at the end of each sprint. During OWS, vaccine candidates were advanced to the next stage based on the preclinical or early-stage clinical trial data on efficacy; the potential to meet large-scale clinical trial benchmarks; and criteria for efficient manufacturing.

Mechanism 1: Establish a leadership team across federal agencies

Establish an integrated command structure co-led by a chief scientific or technical advisor and a chief operating officer, a small oversight board, and leadership from federal agencies. The team should commit to operate as a single cohesive unit despite individual affiliations. Since many agencies have limited experience in collaborating on program operations, a chief operating officer with private-sector experience can help coordinate and manage agency biases. Ideally, the team should have decision-making authority and report directly to the president. Leaders should thoughtfully delegate tasks, give appropriate credit for success, hold themselves and others accountable, and empower others to act.

The OWS team was led by personnel from the Department of Health and Human Services (HHS), the Department of Defense (DOD), and the vaccine industry. It included several HHS offices at different stages: the Centers for Disease Control and Prevention (CDC), the Food and Drug Administration (FDA), the National Institutes of Health (NIH), and the Biomedical Advanced Research and Development Authority (BARDA). This structure combined expertise in science and manufacturing with the power and resources of the DOD. The team assigned clear roles to agencies and offices to establish a chain of command.

Example Challenge: Managing Wildland Fire with Uncrewed Aerial Systems (UAS)
Wildland fire is a natural and normal ecological process, but the changing climate and our policy responses are causing more frequent, intense, and destructive fires. Reducing harm requires real-time monitoring of fires with better detection technology and modernized equipment such as UAS. Wildfire management is a complex policy and regulatory landscape with functions spanning multiple federal, state, and local entities. Several interagency coordination bodies exist, including the National Wildfire Coordinating Group, Wildland Fire Leadership Council, and the Wildland Fire Mitigation and Management Commission, but much of these efforts are consensus-based coordination models. The status quo and historical biases against agencies have created silos of effort and prevent technology from scaling to the level required. An OWS for wildland fire UAS would establish a public-private partnership led by experienced leaders from federal agencies, state and local agencies, and the private sector to advance this technology development. The team would motivate commitment to the challenge across government, academia, nonprofits, and the private sector to deliver technology that meets ambitious goals. Appropriate teams across agencies would be empowered to refocus their efforts during the duration of the challenge.

Mechanism 2: Coordinate federal agencies and the private sector

Coordinate agencies and the private sector on R&D, manufacturing, and distribution, and assign responsibilities based on core capabilities rather than political or financial considerations. Identify efficiency improvements by mapping processes across the program. This may include accelerating regulatory approval by facilitating communication between the private sector and regulators or by speeding up agency operations. Certain regulations may be suspended entirely if the risks are considered acceptable relative to the urgency of the goal. Coordinators should identify processes that can occur in parallel rather than sequentially. Leaders can work with industry so that operations occur under minimal conditions to ensure worker and product safety.

The OWS team worked with the FDA to compress traditional approval timelines by simultaneously running certain steps of the clinical trial process. This allowed manufacturers to begin industrial-scale vaccine production before full demonstration of efficacy and safety. The team continuously sent data to FDA while they completed regulatory procedures in active communication with vaccine companies. Direct lines of communication permitted parallel work streams that significantly reduced the normal vaccine approval timeline.

Example Challenge: Public Transportation and Interstate Rail
Much of the infrastructure across the United States needs expensive repairs, but the U.S. has some of the highest infrastructure construction costs for its GDP and longest construction times. A major contributor to costs and time is the approval process with extensive documentation, such as preparing an environmental impact study to comply with the National Environmental Policy Act. An OWS-like coordinating body could identify key pieces of national infrastructure eligible for support, particularly for near-end-of-lifespan infrastructure or major transportation arteries. Reducing regulatory burden for selected projects could be achieved by coordinating regulatory approval in close collaboration with the Department of Transportation, the Environmental Protection Agency, and state agencies. The program would need to identify and set a precedent for differentiating between expeditable regulations and key regulations, such as structural reviews, that could serve as bottlenecks.

Mechanism 3: Activate latent private-sector capacities for labor and manufacturing

Activate private-sector capabilities for production, supply chain management, deployment infrastructure, and workforce. Minimize physical infrastructure requirements, establish contracts with companies that have existing infrastructure, and fund construction to expand facilities where necessary. Coordinate with the Department of State to expedite visa approval for foreign talent and borrow personnel from other agencies to fill key roles temporarily. Train staff quickly with boot camps or accelerators. Efforts to build morale and ensure commitment are critical, as staff may need to work holidays or perform higher than normally expected. Map supply chains, identify critical components, and coordinate supply. Critical supply chain nodes should be managed by a technical expert in close partnership with suppliers. Use the Defense Production Act sparingly to require providers to prioritize contracts for procurement, import, and delivery of equipment and supplies. Map the distribution chain from the manufacturer to the endpoint, actively coordinate each step, and anticipate points of failure.

During OWS, the Army Corps of Engineers oversaw construction projects to expand vaccine manufacturing capacity. Expedited visa approval brought in key technicians and engineers for installing, testing, and certifying equipment. Sixteen DOD staff also served in temporary quality-control positions at manufacturing sites. The program established partnerships between manufacturers and the government to address supply chain challenges. Experts from BARDA worked with the private sector to create a list of critical supplies. With this supply chain mapping, the DOD placed prioritized ratings on 18 contracts using the Defense Production Act. OWS also coordinated with DOD and U.S. Customs to expedite supply import. OWS leveraged existing clinics at pharmacies across the country and shipped vaccines in packages that included all supplies needed for administration, including masks, syringes, bandages, and paper record cards.

Example Challenge: EV Charging Network
Electric vehicles (EVs) are becoming increasingly popular due to high gas prices and lower EV prices, stimulated by tax credits for both automakers and consumers in the Inflation Reduction Act. Replacing internal combustion engine vehicles with EVs is aligned with our current climate commitments and reduces overall carbon emissions, even when the vehicles are charged with energy from nonrenewable sources. Studies suggest that current public charging infrastructure has too few functional chargers to meet the demand of EVs currently on the road. Reliable and available public chargers are needed to increase public confidence in EVs as practical replacements for gas vehicles. Leveraging latent private-sector capacity could include expanding the operations of existing charger manufacturers, coordinating the deployment and installation of charging stations and requisite infrastructure, and building a skilled workforce to repair and maintain this new infrastructure. In February 2023 the Biden Administration announced actions to expand charger availability through partnerships with over 15 companies.

Mechanism 4: Shape markets with demand-pull mechanisms

Use contracts and demand-pull mechanisms to create demand and minimize risks for private partners. Other Transaction Authority can also be used to procure capabilities quickly by bypassing elements of the Federal Acquisition Regulation. The types of demand-pull mechanisms available to agencies are:

HHS used demand-pull mechanisms to develop the vaccine candidates during OWS. This included funding large-scale manufacturing and committing to purchase successful vaccines. HHS made up to $483 million in support available for Phase 1 trials of Moderna’s mRNA candidate vaccine. This agreement was increased by $472 million for late-stage clinical development and Phase 3 clinical trials. Several months later, HHS committed up to $1.5 billion for Moderna’s large-scale manufacturing and delivery efforts. Ultimately the U.S. government owned the resulting 100 million doses of vaccines and reserved the option to acquire more. Similar agreements were created with other manufacturers, leading to three vaccine candidates receiving FDA emergency use authorization.

Example Challenge: Space Debris
Low-earth orbit includes dead satellites and other debris that pose risks for existing and future space infrastructure. Increased interest in commercialization of low-earth orbit will exacerbate a debris count that is already considered unstable. Since national space policy generally requires some degree of engagement with commercial providers, the U.S. would need to include the industry in this effort. The cost of active space debris removal, satellite decommissioning and recycling, and other cleanup activities are largely unknown, which dissuades novel business ventures. Nevertheless, large debris objects that pose the greatest collision risks need to be prioritized for decommission. Demand-pull mechanisms could be used to create a market for sustained space debris mitigation, such as an advanced market commitment for the removal of large debris items. Commitments for removal could be paired with a study across the DOD and NASA to identify large, high-priority items for removal. Another mechanism that could be considered is fixed milestone payments, which NASA has used in past partnerships with commercial partners, most notably SpaceX, to develop commercial orbital transportation systems.

Mechanism 5: Reduce risk with diversity and redundancy

Engage multiple private partners on the same goal to enable competition and minimize the risk of overall program failure. Since resources are not infinite, the program should incorporate evidence-based decision-making with strict criteria and a rubric. A rubric and clear criteria also ensure fair competition and avoid creating a single national champion. 

During OWS, four vaccine platform technologies were considered for development: mRNA, replication-defective live-vector, recombinant-subunit-adjuvanted protein, and attenuated replicating live-vector. The first two had never been used in FDA-licensed vaccines but showed promise, while the second two were established in FDA-licensed vaccines. Following a risk assessment, six vaccine candidates using three of the four platforms were advanced. Redundancy was incorporated in two dimensions: three different vaccine platforms and two separate candidates. The manufacturing strategy also included redundancy, as several companies were awarded contracts to produce needles and syringes. Diversifying sources for common vaccination supplies reduced the overall risk of failure at each node in the supply chain.

Example Challenge: Alternative Battery Technology
Building infrastructure to capture energy from renewable sources requires long-term energy storage to manage the variability of renewable energy generation. Lithium-ion batteries, commonly used in consumer electronics and electric vehicles, are a potential candidate, since research and development has driven significant cost declines since the technology’s introduction in the 1990s. However, performance declines when storing energy over long periods, and the extraction of critical minerals is still relatively expensive and harmful to the environment. The limitations of lithium-ion batteries could be addressed by investing in several promising alternative battery technologies that use cheaper materials such as sodium, sulfur, and iron. This portfolio approach will enable competition and increase the chance that at least one option is successful.

Conclusion

Operation Warp Speed was a historic accomplishment on the level of the Manhattan Project and the Apollo program, but the unique approach is not appropriate for every challenge. The methods and mechanisms are best suited for challenges in which stakeholders agree on an urgent and specific goal, and the goal requires scaling a technology with established fundamental research. Nonetheless, the individual mechanisms of OWS can effectively address smaller challenges. Those looking to replicate the success of OWS should deeply evaluate the stakeholder and technology landscape to determine which mechanisms are required or feasible.

Acknowledgments

This memo was developed from notes on presentations, panel discussions, and breakout conversations at the Operation Warp Speed 2.0 Conference, hosted on November 17, 2022, by the Federation of American Scientists, 1Day Sooner, and the Institute for Progress to recount the success of OWS and consider future applications of the mechanisms. The attendees included leadership from the original OWS team, agency leaders, Congressional staffers, researchers, and vaccine industry leaders. Thank you to ​​Michael A. Fisher, FAS senior fellow, who contributed significantly to the development of this memo through January 2023. Thank you to the following FAS staff for additional contributions: Dan Correa, chief executive officer; Jamie Graybeal, director, Defense Budgeting Project (through September 2022); Sruthi Katakam, Scoville Peace Fellow; Vijay Iyer, program associate, science policy; Kai Etheridge, intern (through August 2022).

Frequently Asked Questions
When is the OWS approach not appropriate?

The OWS approach is unlikely to succeed for challenges that are too broad or too politically polarizing. For example, curing cancer: While a cure is incredibly urgent and the goal is unifying, too many variations of cancer exist and they include several unique research and development challenges. Climate change is another example: particular climate challenges may be too politically polarizing to motivate the commitment required.

Can the OWS mechanisms work for politicized topics?

No topic is immune to politicization, but some issues have existing political biases that will hinder application of the mechanisms. Challenges with bipartisan agreement and public support should be prioritized, but politicization can be managed with a comprehensive understanding of the stakeholder landscape.

Can the OWS mechanisms be used broadly to improve interagency coordination?

The pandemic created an emergency environment that likely motivated behavior change at agencies, but OWS demonstrated that better agency coordination is possible.

How do you define and include relevant stakeholders?

In addition to using processes like stakeholder mapping, the leadership team must include experts across the problem space that are deeply familiar with key stakeholder groups and existing power dynamics. The problem space includes impacted portions of the public; federal agencies and offices; the administration; state, local, Tribal, and territorial governments; and private partners. 


OWS socialized the vaccination effort through HHS’s Office of Intergovernmental and External Affairs, which established communication with hospitals, healthcare providers, nursing homes, community health centers, health insurance companies, and more. HHS also worked with state, local, Tribal, and territorial partners, as well as organizations representing minority populations, to address health disparities and ensure equity in vaccination efforts. Despite this, OWS leaders expressed that better communication with expert communities was needed, as the public was confused by contradictory statements from experts who were unaware of the program details.

How can future OWS-like efforts include better communication and collaboration with the public?

Future efforts should create channels for bottom-up communication from state, local, Tribal, and territorial governments to federal partners. Encouraging feedback through community engagement can help inform distribution strategies and ensure adoption of the solution. Formalized data-sharing protocols may also help gain buy-in and confidence from relevant expert communities.

Can the OWS mechanisms be used internationally?

Possibly, but it would require more coordination and alignment between the countries involved. This could include applying the mechanisms within existing international institutions to achieve existing goals. The mechanisms could apply with revisions, such as coordination among national delegations and nongovernmental organizations, activating nongovernmental capacity, and creating geopolitical incentives for adoption.

Who was on the Operation Warp Speed leadership team?

The team included HHS Secretary Alex Azar; Secretary of Defense Mark Esper; Dr. Moncef Slaoui, former head of vaccines at GlaxoSmithKline; and General Gustave F. Perna, former commanding general of U.S. Army Materiel Command. This core team combined scientific and technical expertise with military and logistical backgrounds. Dr. Slaoui’s familiarity with the pharmaceutical industry and the vaccine development process allowed OWS to develop realistic goals and benchmarks for its work. This connection was also critical in forging robust public-private partnerships with the vaccine companies.

Which demand-pull mechanisms are most effective?

It depends on the challenge. Determining which mechanism to use for a particular project requires a deep understanding of the particular R&D, manufacturing, supply chain landscapes to diagnose the market gaps. For example, if manufacturing process technologies are needed, prize competitions or challenge-based acquisitions may be most effective. If manufacturing volume must increase, volume guarantees or advance purchase agreements may be more appropriate. Advance market commitments or milestone payments can motivate industry to increase efficiency. OWS used a combination of volume guarantees and advance market commitments to fund the development of vaccine candidates and secure supply.

Creating Equitable Outcomes from Government Services through Radical Participation

Summary

Government policies, products, and services are created without the true and full design participation and expertise of the people who will use them–the public: citizens, refugees, and immigrants. As a result, the government often replicates private sector anti-patterns1, using or producing oppressive, disempowering, and colonial policies through products and services that embody bias, limit access, create real harm, and discriminate against underutilized communities2 on the basis of various identities violating the President’s Executive Order on Equity. Examples include life-altering police use of racially and sexually biased facial recognition products, racial discrimination in the delivery access of life-saving Medicaid services and SNAP benefits, and racist child welfare service systems.

The Biden-Harris Administration should issue an executive order to embed Radical Participatory Design (RPD) into the design and development of all government policies, products, and services, and to require all federally-funded research to use Radical Participatory Research (RPR). Using an RPD and RPR approach makes the Executive Order on Racial Equity, Executive Order on Transforming the Customer Experience, and the Executive Order on DEIA more likely to succeed. Using RPD and RPR as the implementation strategy is an opportunity to create equitable social outcomes by embodying equity on the policy, product and service design side (Executive Order on Racial Equity), to improve the public’s customer experience of the government (Executive Order on Transforming the Customer Experience, President’s Management Agenda Priority 2), and to lead to a new and more just, equitable, diverse, accessible, and inclusive (JEDAI) future of work for the federal government (Executive Order on DEIA).

Challenge and Opportunity

The technology industry is disproportionately white and male. Compared to private industry overall, whites, men, and Asians are overrepresented while Latinx people, Black people, and women are underrepresented. Only 26% of technology positions in the U.S. are held by women though they represent 57% of the US workforce. Even worse, women of color hold 4% of technology positions even though they are 16% of the population. Similarly, Black Americans are 14% of the population but hold 7% of tech jobs. Latinx Americans only hold 8% of tech jobs while comprising 19% of the population. This representation decreases even more as you look at leadership roles in technology. In FY2020, the federal government spent $392.1 billion contracting services, including services to build products. Latinx, African Americans, Native Americans, and women are underrepresented in the contractor community.

The lack of diversity in designers and developers of the policies, products, and services we use leads to harmful effects like algorithmic bias, automatic bathroom water and soap dispensers that do not recognize darker skin, and racial bias in facial recognition (mis)identification of Black and Brown people. 

With a greater expectation of equity from government services, the public experiences greater disappointment when government policies, services, and products are biased, discriminatory, or harmful. Examples include inequitable public school funding services, race and poverty bias in child welfare systems, and discriminatory algorithmic hiring systems used in government.

The federal government has tried to improve the experience of its products and services through methodologies like Human-centered Design (HCD). In HCD, the design process is centered on the community who will use the design, by first conducting research interviews or observations. Beyond the research interactions with community members, designers are supposed to carry empathy for the community all the way through the design, development, and launch process. Unfortunately, given the aforementioned negative outcomes of government products and services for various communities, empathy often is absent. What empathy may be generated does not persist long enough to influence or impact the design process. Ultimately, individual appeals to empathy are inadequate at generating systems level change. Scientific studies show that white people, who make up the majority of technologists and policy-makers, have a reduced capacity for empathy for people of other and similar backgrounds. As a result, the push for equity remains in government services, products, and policies, leading to President Biden’s Executive Order on Advancing Racial Equity and Support for Underserved Communities and, still, again, with the Executive Order on Further Advancing Racial Equity and Support for Underserved Communities.

The federal government lacks processes to embed empathy throughout the lifecycle of policy, product, and service design, reflecting the needs of community groups. Instead of trying to build empathy in designers who have no experiential knowledge, we can create empathetic processes and organizations by embedding lived experience on the team.

Radical Participatory Design (RPD) is an approach to design in which the community members, for whom one is designing, are full-fledged members on the research, design, and development team. In traditional participatory design, designers engage the community at certain times and otherwise work, plan, analyze, or prepare alone before and after those engagements. In RPD, the community members are always there because they are on the team; there are no meetings, phone calls, or planning without them.

RPD has a few important characteristics. First, the community members are always present and leading the process. Second, the community members outnumber the professional designers, researchers, or developers. Third, the community members own the artifacts, outcomes, and narratives around the outcomes of the design process. Fourth, community members are compensated equitably as they are doing the same work as professional designers. Fifth, RPD teams are composed of a qualitatively representative sample (including all the different categories and types of people) of the community.

Embedding RPD in the government connects the government to a larger movement toward participatory democracy. Examples include the Philadelphia Participatory Design Lab, the Participatory City Making Lab, the Center for Lived Experience, the Urban Institute’s participatory Resident Researchers, and Health and Human Service’s “Methods and Emerging Strategies to Engage People with Lived Experience.” Numerous case studies show the power of participatory design to reduce harm and improve design outcomes. RPD can maximize this by infusing equity as people with lived experience both choose, check, and direct the process.

As the adoption of RPD increases across the federal government, the prevalence and incidence of harm, bias, trauma, and discrimination in government products and services will decrease, aiding the implementation of the executive orders on Advancing Racial Equity and Support for Underserved Communities and Further Advancing Racial Equity and Support for Underserved Communities, and ensuring the OSTP AI Bill of Rights for AI products and services. Additionally, RPR aligns with OSTP’s actions to advance open and equitable research. Second, the reduction of harm, discrimination, and trauma improves the customer experience (CX) of government services aiding the implementation of the Executive Order on Transforming the Customer Experience, the President’s Management Agenda Priority 2, and the CAP goal on Customer Experience. An improved CX will increase community adoption, use, and engagement with potentially helpful and life-supporting government services that underutilized people need. RPD highlights the important connection between equity and CX and creates a way to link the two executive orders. You cannot claim excellent CX when the CX is inequitable and entire underutilized segments of the public have a harmful experience.

Third, instead of seeking the intersection of business needs and user needs like in the private sector, RPD will move the country closer to its democratic ideals by equitably aligning the needs of the people with the needs of the government of the people, by the people, and for the people. There are various examples where the government acts like a separate entity completely unaligned to the will of a majority of the public (gun control, abortion). Project by project, RPD helps align the needs of the people and the needs of the government of the people when representative democracy does not function properly.
Fourth, all community members, from all walks of life, brought into government to do participatory research and design will gain or refine skills they can then use to stay in government policy, product, and service design or to get a job outside of government. The workforce outcomes of RPD further diversify policy, product, and service designers and researchers both inside and outside the federal government, aligning with the Executive Order on DEIA in the Federal Workforce.

Plan of Action

The use of RPD and RPR in government is the future of participatory government and a step towards truly embodying a government of the people. RPD must work at the policy level as well, as policy directs the creation of services, products, and research. Equitable product and service design cannot overcome inequitable and discriminatory policy.  The following recommended actions are initial steps to embody participatory government in three areas: policy design, the design and development of products and services, and funded research. Because all three areas occur across the federal government, executive action from the White House will facilitate the adoption of RPD.

Policy Design

An executive order from the president should direct agencies to use RPD when designing agency policy. The order should establish a new Radical Participatory Policy Design Lab (RPPDL) for each agency with the following characteristics:

The executive order should also create a Chief Experience Officer (CXO) for the U.S. as a White House role. The Office of the CXO (OCXO) would coordinate CX work across the government in accordance with the Executive Order on Transforming the CX, the PMA Priority 2, the CX CAP goal, and the OMB Circular A-11 280. The executive order would focus the OCXO on the work of coordinating, approving, advising the RPD work across the federal government, including the following initiatives:

Due to the distributed nature of the work, the funding for the various RPPDLs and the OCXO should come from money the director of OMB has identified and added to the budget the President submits to Congress, according to Section 6 of the Executive Order on Advancing Racial Equity. Agencies should also utilize money appropriated by the Agency Equity Teams required by the Executive Order on Further Advancing Racial Equity.

Product and Service Design

The executive order should mandate that all research, design, and delivery of agency products and services for the public be done through RPR and RPD. RPD should be used both for in-house and contracted work through grants, contracts, or cooperative agreements.

On in-house projects, funding for the RPD team should come from the project budget. For grants, contracts, and cooperative agreements, funding for the RPD team should come from the acquisition budget. As a result, the labor costs will increase since there are more designers on the project. The non-labor component of the project budget will be less. A slightly lower non-labor project budget is worth the outcome of improved equity. Agency offices can compensate for this by requesting a slightly higher project budget for in-house or contracted design and development services. 

In support of the Executive Order on Transforming the CX, the PMA Priority 2, and the CX CAP goal,  OMB should amend the OMB Circular A-11 280 to direct High Impact Service Providers (HISPs) to utilize RPD in their service work.

OSTP should add RPD and RPD case studies as example practices in OSTP’s AI Bill of Rights. RPD should be listed as a practice that can affect and reinforce all five principles.

Funded Research

The executive order should also mandate that all government-funded, use-inspired research about communities or intended to be used by people or communities, should be done through RPR. In order to determine if a particular intended research project is use-inspired, the following questions should be asked by the government funding agency prior to soliciting researchers:

  1. For technology research, is the technology readiness level (TRL) 2 or higher?
  2. Is the research about people or communities?
  3. Is the research intended to be used by people or communities?
  4. Is the research intended to create, design, or guide something that will be used by people and communities?

If the answer to any of the questions is yes, the funding agency should require the funded researchers to use an RPR approach.

Funding for the RPR team comes from the research grant or funding. Researchers can use the RPR requirement to estimate how much funding should be requested in the proposal.
OSTP should add RPR and the executive order to their list of actions to advance open and equitable research. RPR should be listed as a key initiative of the year of Open Science.

Conclusion

In order to address inequity, the public’s lived experience should lead the design and development process of government products and services. Because many of those products and services are created to comply with government policy, we also need lived experience to guide the design of government policy. Embedding Radical Participatory Design in government-funded research as well as policy, products, and services reduces harm, creates equity, and improves the public customer experience. Additionally, RPD connects and embeds equity in CX, moves us toward our democratic ideals, and creatively addresses the future of work by diversifying our policy, product, and service design workforce.

Frequently Asked Questions
What is the difference between a product and a service in technology?

Because we do not physically hold digital products, the line between a software product and a software service is thin. Usually, a product is an offering or part of an offering that involves one interaction or touchpoint with a customer. In contrast, a service involves multiple touchpoints both online and offline, or multiple interactions both digital and non-digital.


For example, Google Calendar can be considered a digital product. A product designer for Google Calendar might work on designing its software interface, colors, options, and flows. However, a library is a service. As a library user, you might look for a book on the library website. If you can’t find it, you might call the library. The librarian might ask you to come in. You go in and work with the librarian to find the book. After realizing it is not there, the librarian might then use a software tool to request a new book purchase. Thus, the library service involved multiple touchpoints, both online and offline: a website, a phone line, an in-person service in the physical library, and an online book procurement tool.


Most of the federal government’s offerings are services. Examples like Medicare, Social Security, and veterans benefits involve digital products, in-person services in a physical building, paper forms, phone lines, email services, etc. A service designer designs the service and the mechanics behind the service in order to improve both the customer experience and the employee experience across all touchpoints, offline and online, across all interactions, digital and non-digital.

Why do you use the word “radical?” What is the difference between Participatory Design and RPD?

Participatory design (PD) has many interpretations. Sometimes PD simply means interviewing research participants. Because they are “participants,” by being interviewees, the work is participatory. Sometimes, PD  means a specific activity or method that is participatory. Sometimes practitioners use PD to mean a way of doing an activity. For example, we can do a design studio session with just designers, or we can invite some community members to take part for a 90-minute session. PD can also be used to indicate a methodology. A methodology is a collection of methods or activities; or a methodology is a philosophy or guiding philosophy or principles that help you choose a particular method or activity at a particular point in time or in a process.


In all the above ways of interpreting PD, there are times when the community is present and times when they are not. Moreover, the community members are never leading the process.


Radical comes from the Latin word “radix” meaning root. RPD means design in which the community participates “to the root,” fully, completely, from beginning to end. There are no times, planning, meetings, or phone calls where the community is not present because the community is the team.

What is the difference between RPD and peer review?

Peer review is similar to an Institutional Review Board (IRB). A participatory version of this could be called a Community Review Board (CRB). The difficulty is that a CRB can only reject a research plan; a CRB does not create the proposed research plans. Because a CRB does not ensure that great research plans are created and proposed, it can only reduce harm. It cannot create good. 


Equality means treating people the same. Equity means treating people differently to achieve equal outcomes. CRBs achieve equality only in approving power, by equally including community members in the approving process. CRBs fail to achieve equity in social outcomes of products and services because community members are missing in the research plan creation process, research plan implementation process, and the development process of policy, products, and services where inequity can enter. To achieve equal outcomes, equity, their lived experiential knowledge is needed throughout the entire process and especially in deciding what to propose to a CRB.


Still a CRB can be a preliminary step before RPR. Unfortunately, IRBs are only required for US government-funded research with human subjects. In practice, it is not interpreted to apply to the approval of design research for policy, products, and services, even when the research usually includes human subjects. The application of participatory CRBs to approve all research–including design research for policy, products, and services–can be an initial step or a pilot.

If anyone can do research, design, and development work, what is the point of hiring professional researchers, designers, or developers?

A good analogy is that of cooking. It is quite helpful for everyone to know how to cook. Most of us cook in some capacity. Yet, there are people who attend culinary school and become chefs or cooks. Has the fact that individual people can and do cook eliminated the need for chefs? No. Chefs and cooks are useful for various situations – eating at a restaurant, catering an event, the creation of cookbooks, lessons, etc.


The main idea is that the chefs have mainstream institutional knowledge learned from books and universities or cooking schools. But that is not the only type of knowledge. There is also lived, experiential knowledge as well as community, embodied, relational, energetic, intuitive, aesthetic, and spiritual knowledge. It is common to meet amazing chefs who have never been to a culinary school but simply learned to cook through lived experience of experimentation and having to cook everyday for X people. Some learned to cook through relational and community knowledge passed down in their culture through parents, mothers, and aunties. Sometimes, famous chefs will go and learn the knowledge of a particular culture from people who did not go to a learning school. The chefs will appropriate the knowledge and then create a cookbook to sell marketing a fusion cuisine, infused with the culture whose culinary knowledge they appropriated.


Similarly, everyone designs. It is not enough to be tech-savvy or an innovation and design expert. The most important knowledge to have is the lived experiential, community, relational, and embodied knowledge of the people for whom we are designing. When lived experience leads, the outcomes are amazing. Putting lived experience alongside professional designers can be powerful as well. Professional designers are still needed, as their knowledge can help improve the design process. Professionals just cannot lead, lead alone, or be the only knowledge base because inequity enters the system more easily.

Do RPR or RPD teams serve full-time or is it a part-time role?

To realize the ambitions of this policy proposal, full-time teams will be needed. The RPPDLs who are designing policy are full-time roles due to the amount and various levels of policy to design. For products and services, however, some RPD teams may be part-time. For example, improving an existing product or service may be one of many work projects a government team is conducting. So if they are only working on the project 50% of the time, they may only require a group of part-time community members. On the other hand, the work may require full-time work for RPD team members for the design and development of a greenfield or new product or service that does not exist. Full-time projects will need full-time community members. For part-time projects, community members can work on multiple projects to reach full-time capacity.

How do we compensate RPR or RPD team members outside of a grant, cooperative agreement, or contract?

Team members can receive non-monetary compensation like a gift card, wellness services, or child care. However, it is best practice to allow the community member to choose. Most will choose monetary compensation like grants, stipends, or cash payments.


Ultimately they should be paid at a level equal to that of the mainstream institutional experts (designers and developers) who are being paid to do the same work alongside the community members. Remember to compensate them for travel and child care when needed.

Why is the government the right sector to implement this? Why can’t this first be done in the private or nonprofit sector or even by government at the state or local level?

RPD is an opportunity for the government to lead the way. The private sector can make money without equitably serving everyone, so it has no incentive to do so. Nonprofits do not carry the level of influence the federal government carries. The federal government has more money to engage in this work than state or local governments. The federal government has a mandate to be equitable in its products and services and their delivery, and if this goes well, the government can make a law mandating organizations in the private and nonprofit sector to do the same work to transform. The government has a long history of using policy and services to discriminate against various underutilized groups. So the federal government should be the first one to use RPD to move towards equity. Ultimately the federal government has a huge influence on the lives of citizens, immigrant residents, and refugees, and the opportunity is great to move us toward equity.


Embedding RPD in government products and services should also be done at the state and local level. Each level will require different memos due to the different mechanics, budgets, dynamics, and policies. The hope is that RPD work at the federal government can help spark RPD work at various state, local, and county governments.

Is there a pilot or scaled-down version that could be implemented as a first step?

Possible first steps include:



  • Mandate that all use-inspired research, including design research for policy, products, and services, be reviewed by a Community Review Board (CRB) for approval.



  • If not approved, the research, design, and development cannot move forward.



  • Only mandate all government-funded, use-inspired research be conducted using RPR. Focusing on research funding alone shifts the payment of RPR community teams to the grant recipients, only.



  • Mandate all government-funded, use-inspired research use RPR and all contracted research, design, development, and delivery of government products and services uses RPD.



  • Focusing on research funding and contracted product and service work shifts the payment of RPR and RPD community team members to the grant recipients, vendors, and contract partners.



  • Choose a pilot agency, like NIH, to start.




  • Start with a high-profile set of projects such as the OMB life experience projects.
    Then, later we can advance to an entire pilot agency.



  • Focus on embedding equity measures in CX.


After equity is embedded in CX, start by choosing a pilot agency, benchmarking equity and CX, piloting RPD, and measuring the change attributable to RPD.
This allows time to build more evidence.

How do you ensure that a product or service continues developing according to community desires after the RPD team is finished?

In modern product and service development, products and services never convert into an operations and maintenance phase alone. They are continually being researched, designed, and developed due to continuous changes in human expectations, migration patterns, technology, human preferences, globalization, etc. If community members were left out of research, design, and development work after a service or product launches, then the service or product would no longer be designed and developed using an RPD approach. As long as the service or product is active and in service, radical participation in the continuous research, design, and development is needed.

Protecting Civil Rights Organizations and Activists: A Policy Addressing the Government’s Use of Surveillance Tools

Summary

In the summer of 2020, some 15 to 26 million people across the country participated in protests against the tragic killings of Black people by law enforcement officers, making it the largest movement in US history. In response, local and state government officials and federal agencies deployed surveillance tools on protestors in an unprecedented way. The Department of Homeland Security used aerial surveillance on protesters across 15 cities, and several law enforcement agencies engaged in social media monitoring of activists. But there is still a lot the public does not know, such as what other surveillance tactics were used during the protests, where this data is being stored, and for what future purpose. 

Government agencies have for decades secretly used surveillance tactics on individual activists, such as during the 1950s when the FBI surveilled human rights activists and civil rights organizations. These tactics have had a detrimental effect on political movements, causing people to forgo protesting and activism out of fear of such surveillance. The First Amendment protects freedom of speech and the right to assemble, but allowing government entities to engage in underground surveillance tactics strips people of these rights. 

It also damages people’s Fourth Amendment rights. Instead of agencies relying on the court system to get warrants and subpoenas to view an individual’s online activity, today some agencies are entering into partnerships with private companies to obtain this information directly. This means government agencies no longer have to meet the bare minimum of having probable cause before digging into an individual’s private data.

This proposal offers a set of actions that federal agencies and Congress should implement to preserve the public’s constitutional rights. 

Challenges and Opportunities 

Government entities have been surveilling activists and civil rights organizations long before the 2020 protests. Between 1956 and 1971, the FBI engaged in surveillance tactics to disrupt, discredit, and destroy many civil rights organizations, such as the Black Panther Party, American Indian Movement, and the Communist Party. Some of these tactics included illegal wiretaps, infiltration, misinformation campaigns, and bugs. This program was known as COINTELPRO, and the FBI’s goal was to destroy organizations and activists who had political agendas that they viewed as radical and would challenge “the existing social order.” While the FBI didn’t completely achieve this goal, their efforts did have detrimental effects on activist communities, as members were imprisoned or killed for their activist work, and membership in organizations  like the Black Panther Party significantly declined and eventually dissolved in 1982

After COINTELPRO was revealed to the public, reforms were put in place to curtail the FBI’s surveillance tactics against civil rights organizations, but those reforms were soon rolled back after the September 11 attacks. Since 9/11, it has been revealed, mostly through FOIA requests, that the FBI has surveilled the Muslim community, Occupy Wall Street, Standing Rock protesters, murder of Freddie Gray protesters, Black Lives Matter protests, and more. Today, the FBI has more technological tools at their disposal that make mass surveillance and data collection on activist communities incredibly easy. 

In 2020, people across the country used social media sites like Facebook to increase engagement and turnout in local Black Lives Matters protests. The FBI’s Joint Terrorism Task Forces responded by visiting people’s homes and workplaces to question them about their organizing, causing people to feel alarmed and terrified. U.S. Customs and Border Protection (CBP) also got involved, deploying a drone over Minneapolis to provide live video to local law enforcement. The Acting Secretary of CBP also tweeted out that CBP was working with law enforcement agencies across the nation during the 2020 Black Lives Matter Protests. CBP involvement in civil rights protests is incredibly concerning given its ability to circumvent the Fourth Amendment and conduct warrantless searches due to the border search exception. (Federal regulations and federal law gives CBP the authority to conduct warrantless searches and seizures within 100 miles of the U.S. border, where approximately two-thirds of the U.S. population resides.)

The longer government agencies are allowed to surveil people who are simply organizing for progressive policies, the more people will be terrified to voice their opinion about the state of affairs in the United States. This has had detrimental effects on people’s First and Fourth Amendment rights and will continue to have even more effects as technology improves and government entities have access to advanced tools. Now is the time for government agencies and Congress to act to prevent further abuse of the public’s rights to protest and assemble. A country that uses tools to watch its residents will ultimately lead to a country with little to no civic engagement and the complete silencing of marginalized communities. 

While there is a lot of opportunity to address mass surveillance and protect people’s constitutional rights, government officials have refused to address government surveillance for decades, despite public protest. In the few instances where government officials put up roadblocks to stop surveillance tactics, those roadblocks were later removed or reformed so as to allow the previous surveillance to continue. The lack of political will of Congressmembers to address these issues has been a huge challenge for civil rights organizations and individuals fighting for change. 

Plan of Action 

Regulations need to be put in place to restrict federal agency use of surveillance tools on the public. 

Recommendation 1. Federal agencies must disclose technologies they are using to surveil individuals and organizations, as well as the frequency with which they use them. Agencies should to publish this information on their websites and produce a more comprehensive report for the Department of Justice (DOJ) to review. 

Every six months, Google releases the number of requests it receives from government agencies asking for user information. Google informs the public on the number of accounts that were affected by those requests and whether the request was a subpoena, search warrant, or other court order. The FBI also discloses the number of DNA samples it has collected from individuals in each U.S. state and territory and how many of those DNA samples aided in investigations.

Likewise, government agencies should be required to disclose the names of the technologies they are purchasing to surveil people in the United States as well as the number of times they use this technology within the year. Government entities should no longer be able to hide which technologies their departments are using to watch the public. People should be informed on the depth of the government’s use of these tools so they have a chance to voice their objections and concerns. 

Federal agencies also need to publish a more comprehensive report for the DOJ to review. This report will include what technologies were used and where, what category of organizations they were used against, racial demographics of the people who were surveilled, and possible threats to civil rights. The DOJ will use this information to run investigate whether agencies are violating the Fourth Amendment or First Amendment in using these technologies against the public. 

Agencies may object to releasing this information because of the possibility of it interfering with investigations. However, Google does not release the names of individuals who have had their user information requested, and neither should government agencies release user information. Because government agencies won’t be required to release specific information on individuals to the public, this will not affect their investigations. This disclosure request is aimed at knowing what tools government agencies are using and giving the DOJ the opportunity to investigate whether these tools violate constitutional rights. 

Recommendation 2. Attorney General Guidelines should be revised in collaboration with the White House Office of Science and Technology Policy (OSTP) and civil rights organizations that specialize in technology issues.

The FBI has used advanced technology to watch activists and protests with little to no government oversight or input from civil rights organizations. When conducting an investigation or assessment of an individual or organization, FBI agents follow the Attorney General Guidelines, which dictate how investigations should be conducted. Unfortunately, these guidelines do little to protect the public’s civil rights—and in fact contain a few provisions that are quite problematic: 

These provisions are problematic for a few reasons. FBI employees should not be able to conduct assessments on individuals without a factual basis. Giving employees the power to pick and choose who they want to assess provides an opportunity for inherent bias. Instead, all assessments and investigations should have some factual basis behind them and receive approval from a supervisor. Physical surveillance and internet searches, likewise, should not be conducted by FBI agents without probable cause. Allowing these kinds of practices opens the entire public to having their privacy invaded. 

These policies should be reviewed and revised to ensure that activists and organizations won’t be subject to surveillance due to internal bias. President Biden should issue an executive order directing OSTP to collaborate with the Office of the Attorney General on the guidelines. OSTP should have a task force dedicated to researching government surveillance and the impact on marginalized groups to guide them on this collaboration. 

External organizations that are focused on technology and civil rights should also be brought in to review the final guidelines and voice any concerns. Civil rights organizations are more in tune with the effect that government surveillance has on their communities and the best mechanisms that should be put in place to preserve privacy rights. 

Congress also should take steps to protect the public’s civil rights by passing the Fourth Amendment Is Not for Sale Act, revising the Stored Communications Act, and passing border exception legislation. 

Recommendation 3. Congress should close the loophole that allows government agencies to circumvent the Fourth Amendment and purchase data from private companies by passing the Fourth Amendment Is Not for Sale Act. 

In 2008, it was revealed that AT&T had entered into a voluntary partnership with the National Security Agency (NSA) from 2001 to 2008. AT&T built a room in its headquarters that was dedicated to providing the NSA with a massive quantity of internet traffic, including emails and web searches. 

Today, AT&T has eight facilities that intercept internet traffic across the world and provide it to the NSA, allowing them to view people’s emails, phone calls, and online conversations. And the NSA isn’t the only federal agency partnering with private companies to spy on Americans. It was revealed in 2020 that the FBI has an agreement with Dataminr, a company that monitors people’s social media accounts, and Venntel, Inc., a company that purchases bulk location data and maps the movements of millions of people in the United States. These agreements were signed and modified after BLM protests were held across the country. 

Allowing government agencies to enter into agreements with private companies to surveil people gives them the ability to bypass the Fourth Amendment and spy on individuals with no restriction. Federal agencies no longer need rely on the courts when seeking private communications and thoughts; they can now purchase sensitive information like a person’s location data and social media activity from a private company. Congress should end this practice and ban federal government agencies from purchasing people’s private data from third parties by passing the Fourth Amendment Is Not For Sale Act. If this bill passed, government agents could no longer purchase location data from a data broker to figure out who was in a certain area during a protest or partner with a company to obtain people’s social media postings without going through the legal process. 

Recommendation 4. Congress should amend the Stored Communications Act of 1986 (SCA) to compel electronic communication service companies to prove they are in compliance with the act. 

The SCA prohibits companies that provide an electronic communication service from “knowingly” sharing their stored user data with the government. While data brokers are more than likely excluded from this provision, companies that provide direct services to the public such as Facebook, Twitter, and Snapchat are not. Because of this law, direct service companies aren’t partnering with government agencies to sell user information, but they are selling user data to third parties like data brokers. 

There should be a responsibility placed on electronic communication service companies to ensure that the companies they sell user information to won’t sell data to government entities. Congress should amend the SCA to include a provision requiring companies to annually disclose who they sold user data to and whether they verified with the third party that the data will not be eventually sold to a government entity. Verification should require at minimum a conversation with the third party about the SCA provision and a signed agreement that the third party will not sell any user information to the government. The DOJ will be tasked with reviewing these disclosures for compliance. 

Recommendation 5. Congress should pass legislation revoking the border search exception. As stated earlier, this exception allows federal agents to conduct warrantless searches and seizures within 100 miles of the U.S. border. It also allows federal agents to search and seize digital devices at the border without having any level of suspicion that the traveler has committed a crime. CBP agents have pressured travelers to unlock their devices to look at the content, as well as downloaded the content of the devices and stored the data in a central database for up to 15 years. 

While other law enforcement agencies are forced to abide by the Fourth Amendment, federal agents have been able to bypass the Fourth Amendment and conduct warrantless searches and seizures without restriction. If federal agents are allowed to continue operating without the restrictions of the Fourth Amendment, it’s possible we will see more instances of local law enforcement agencies calling on CBP to conduct surveillance operations on the general public during protests. This is an unconscionable amount of power to give to agencies that can and has led to serious abuse of the public’s privacy rights. Congress must roll back this authority and require all law enforcement agencies—local, state, and federal—to have probable cause at a minimum before engaging in searches and seizures. 

Conclusion

For too long, government agencies have been able to surveil individuals and civil rights organizations with little to no oversight. With the advancement of technology, their surveillance capabilities have grown tremendously, leading to near 24/7 surveillance. Regulations must be put in place to restrict the use of surveillance technologies by federal agencies, and Congress must pass legislation to protect the public’s constitutional rights.

Frequently Asked Questions
What are Attorney General Guidelines?

The FBI operates under the jurisdiction of the DOJ and reports to the Attorney General. The Attorney General has been granted the authority under U.S. Codes and Executive Order 12333 to issue guidelines for the FBI to follow when they conduct domestic investigations. These are the Attorney General Guidelines.

What is the Fourth Amendment Is Not For Sale Act?

This bill was introduced by Senators Ron Wyden, Rand Paul, and 18 others in 2021 to protect the public from having government entities purchase their personal information, such as location data, from private companies rather than going through the court system. Instead, the government would be required to obtain a court order before they getting an individual’s personal information from a data broker. This is a huge step in protecting people’s private information and stopping mass government surveillance.

Modernizing Enforcement of the Civil Rights Act to Mitigate Algorithmic Harm in Determining Federal Benefits

Summary

The Department of Justice should modernize the enforcement of Title VI of the Civil Rights Act to guide effective corrective action for algorithmic systems that produce discriminatory outcomes with regard to federal benefits. To do so, the Department of Justice should clarify the definition of “algorithmic discrimination” in the context of federal benefits, establish systems to identify which federally funded public benefits offices use machine-learning algorithms, and secure the necessary human resources to properly address algorithmic discrimination. This crucial action would leverage a demonstrable, growing interest in regulating algorithms that has bloomed over the past year via policy actions in both the White House and Congress but has yet to concretely establish an appropriate enforcement mechanism for acting on instances of demonstrated algorithmic harm. 

Challenge and Opportunity

Algorithmic systems are inescapable in modern life. They have become core elements of everyday activities, like surfing the web, driving to work, and applying for a job. It is virtually impossible to go through life without encountering an algorithmic system multiple times per day.

As machine-learning technologies have become more pervasive, they have also become gatekeepers for crucial resources, like accessing credit, receiving healthcare, securing housing, and getting a mortgage. Both local and federal governments have embraced algorithmic decision-making to determine which constituents are able to access key services, often with little transparency, if any, for those who are subject to such decision-making.

When it comes to federal benefits, imperfections in these systems scale significantly. For example, the deployment of flawed algorithmic tools led to the wrongful termination of Medicaid for 19% of beneficiaries in Arkansas, the wrongful termination of Social Security income for thousands in New York, wrongful termination of $78 million worth of Medicaid and Supplemental Nutrition Assistance Program benefits in Indiana, and erroneous unemployment fraud charges for 40,000 people in Michigan. These errors are particularly harmful to low-income Americans for whom access to credit, housing, job opportunities, and healthcare are especially important.

Over the past year, momentum for regulating algorithmic systems has grown, resulting in several key policy actions. In February 2022, Senators Ron Wyden and Cory Booker and Representative Yvette Clarke introduced the Algorithmic Accountability Act. Endorsed by AI experts, this bill would have required deployers of algorithmic systems to conduct and publicly share impact assessments of their systems. In October 2022, the White House released its Blueprint for an AI Bill of Rights. Although not legally enforceable, this robust rights-based framework for algorithmic systems was developed with a broad coalition of support through an intensive, yearlong public consultation process with community members, private sector representatives, tech workers, and policymakers. Also in October 2022, the AI Training Act was passed into law. The legislation requires the development of a training curriculum covering core concepts in artificial intelligence for federal employees in a limited range of roles, primarily those involved in procurement. Finally, January 2023 saw the introduction of the NIST AI Risk Management Framework to guide how organizations and individuals design, develop, deploy, or use artificial intelligence to manage risk and promote responsible use.

Collectively, these actions demonstrate clear interest in preventing harm caused by algorithmic systems, but none of them provide clear enforcement mechanisms for federal agencies to pursue corrective action in the wake of demonstrated algorithmic harm.

However, Title VI of the Civil Rights Act offers a viable and legally enforceable mechanism to aid anti-discrimination efforts in the algorithmic age. At its core, Title VI bans the use of federal funding to support programs (including state and local governments, educational institutions, and private companies) that discriminate on the basis of race, color, or national origin. Modernizing the enforcement of Title VI, specifically in the context of federal benefits, offers a clear opportunity for developing and refining a modern enforcement approach to civil rights law that can respond appropriately and effectively to algorithmic discrimination. 

Plan of Action

Fundamentally, this plan of action seeks to:

Clarify the Framework for Algorithmic Bias in Federal Benefits

Recommendation 1. Fund the Department of Justice (DOJ) to develop a new working group focused specifically on civil rights concerns around artificial intelligence.

The DOJ has already requested funding for and justified the existence of this unit in its FY2023 Performance Budget. In that budget, the DOJ requested $4.45 million to support 24 staff. 

Clear precedents for this type of cross-sectional working group already exist within the Department of Justice (e.g., the Indian Working Group and LGBTQI+ Working Group). Both of these groups contain members of the 11 sections of the Civil Rights Division to ensure a comprehensive strategy for protecting the civil rights of Indigenous peoples and the LGBTQ+ community, respectively. The pervasiveness of algorithmic systems in modern life suggests a similarly broad scope is appropriate for this issue.

Recommendation 2. Direct the working group to develop a framework that defines algorithmic discrimination and appropriate corrective action specifically in the context of public benefits.

A clear framework or rubric for assessing when algorithmic discrimination has occurred is a prerequisite for appropriate corrective action. Despite having a specific technical definition, the term “algorithmic bias” can vary widely in its interpretation depending on the specific context in which an automated decision is being made. Even if algorithmic bias does exist, researchers and legal scholars have made the case that biased algorithms may be preferable to biased human decision-makers on the basis of consistency and the relative ease of behavior change. Consequently, the DOJ should develop a context-specific framework for determining when algorithmic bias leads to harmful discriminatory outcomes in federal benefits systems, starting with major federal systems like Social Security and Medicare/Medicaid. 

As an example, the Brookings Institution has produced a helpful report that illustrates what it means to define algorithmic bias in a specific context. Cross-walking this blueprint with existing Title VI procedures can yield guidelines for how the Department of Justice can notify relevant offices of algorithmic discrimination and steer corrective action.

Identify Federal Benefits Systems that Use Algorithmic Tools

Recommendation 3. Establish a federal register or database for offices that administer federally funded public benefits to document when they use machine-learning algorithms.

This system should specifically detail the developer of the algorithmic system and the office using said system. If possible, descriptions of relevant training data should be included as well, especially if these data are federal property. Consider working with the Office of Federal Contract Compliance Programs to secure this information from current and future government contractors within the federal benefits domain.

In terms of cost, previous budget requests for databases of this type have ranged from $2 million to $5 million.

Recommendation 4. Provide public access to the federal register.

Making the federal register public would provide baseline transparency regarding the federal funding of algorithmic systems. This would facilitate external investigative efforts to identify possible instances of algorithmic discrimination in public benefits, which would complement internal efforts by directing limited federal staff bandwidth towards cases that have already been identified. The public-facing portion of this registry should be structured to respecting appropriate privacy and trade secrecy restrictions

Recommendation 5. Link the public-facing register to a public-facing form for submitting claims of algorithmic discrimination in the context of federal benefits.

This step would help channel public feedback regarding claims of algorithmic discrimination with a sufficiently high threshold to minimize frivolous claims. A well-designed system will ask for evidence and data to justify any claim of algorithmic discrimination, allowing federal employees to prioritize which claims to pursue.

Equip Agencies with Necessary Resources for Addressing Algorithmic Discrimination

Recommendation 6. Authorize funding for technical hires in enforcement arms of federal regulatory agencies, including but not limited to the Department of Justice.

Effective enforcement of anti-discrimination statutes today requires technical fluency in machine-learning techniques. In addition to the DOJ’s Civil Rights Division (see Recommendation 1), consider directing funds to hire or train technical experts within the enforcement arms of other federal agencies with explicit anti-discrimination enforcement authority, including the Federal Trade Commission, Federal Communications Commission, and Department of Education.

Recommendation 7. Pass the Stopping Unlawful Negative Machine Impacts through National Evaluation Act.

This act was introduced with bipartisan support in the Senate at the very end of the 2021–2022 legislative session by Senator Rob Portman. The short bill seeks to clarify that civil rights legislation applies to artificial intelligence systems and decisions made by these systems will be liable to claims of discrimination under said legislation, including the Civil Rights Act, the Americans with Disabilities Act, and the Age Discrimination Act of 1975, among others. Passing the bill is a simple but effective way to indicate to federal regulatory agencies (and those they regulate) that artificial intelligence systems must comply with civil rights law and affirms the federal government’s authority to ensure they do so.

Conclusion

On his first day in office, President Biden signed an executive order to address the entrenched denial of equal opportunities for underserved communities in the United States. Ensuring that federal benefits are not systematically denied via algorithmic discrimination to low-income Americans and Americans of color is crucial to successfully meeting the goals of that order and the rising chorus of voices who want meaningful regulation for algorithmic systems. The authority for such regulation in the context of federal benefits already exists. To ensure that authority can be effectively enforced in the modern age, the federal government needs to clearly define algorithmic discrimination in the context of federal benefits, identify where federal funding is supporting algorithmic determination of federal benefits, and recruit the necessary talent to verify instances of algorithmic discrimination.

Frequently Asked Questions
What is an algorithm? How is it different from machine learning or artificial intelligence?

An algorithm is a structured set of steps for doing something. In the context of this memo, an algorithm usually means computer code that is written to do something in a structured, repeatable way, such as determining if someone is eligible for Medicare, identifying someone’s face using a facial recognition tool, or matching someone’s demographic profile to a certain kind of advertisement.


Machine-learning techniques are a specific set of algorithms that train a computer to do different tasks by taking in a massive amount of data and looking for patterns. Artificial intelligence generally refers to technical systems that have been trained to perform tasks with minimal human oversight. Machine learning and artificial intelligence are similar and often used as interchangeable terms.

How can we determine if an algorithm is biased?

We can identify algorithmic bias by comparing the expected outputs of an algorithm to the actual outputs for an algorithm. For example, if we find that an algorithm uses race as a decisive factor in determining whether someone is eligible for federal benefits that should be race-neutral, that would be an example of algorithmic bias. In practice, these assessments often take the form of statistical tests that are run over multiple outputs of the same algorithmic system.

Is algorithmic bias inherently bad?

Although many algorithms are biased, not all biases are equally harmful. This is due to the highly contextual nature in which an algorithm is used. For example, a false positive in a criminal-sentencing algorithm arguably causes more harm than a false positive in a federal benefits determination. Algorithmic bias is not inherently a bad thing and, in some cases, can actually advance equity and inclusion efforts depending on the specific contexts (consider a hiring algorithm for higher-level management that weights non-male gender or non-white race more heavily for selection).