Renewing the Call for Bold Policy Ideas

The original elevator pitch for the Day One Project wasn’t hard to boil down: 100 actionable science and technology policy ideas we could deliver to the victor in January 2021 – ideas ready for the new president on “Day One” of their time in the White House. We saw opportunities for great progress no matter which party emerged victorious – and so we focused on ideas that could garner bipartisan support. We couldn’t be prouder of the policy innovations that surfaced at the outset of Day One – from Mike Stebbins and Geoff Ling’s memo laying out the case for ARPA-H, an agency since launched and funded with over $2.5B in appropriations, to Adam Marblestone and Sam Rodriques’ memo proposing the creation of “Focused Research Organizations,” which has led to the creation of a network of philanthropically-supported research initiatives as well as inspired a number of new federal initiatives. These are but two examples from a very long list.

This is how policy actually changes. We believe our emphasis on concisely outlining the challenge, opportunities and specific steps for policymakers to take represents a leap forward for how technologists, scientists, and those with lived experience could make a difference. I add the last category because it’s often overlooked in policy circles but is where some of the best ideas can originate. At FAS, we take our role in creating the platform to democratize the policy making process seriously and seek to include an array of voices in creating sound and equitable policy.

The “secret sauce” of the Day One Project isn’t just the format of the policy recommendations we publish. It’s the “policy entrepreneurs” who make them happen: the people who make up FAS staff and policy contributors. My colleague Erica Goldman recently wrote eloquently in Issues in Science and Technology about why it’s so important that more scientists take the plunge into policy entrepreneurship. She highlighted the examples of policy entrepreneurs such as Julian Elliott, who rose to the challenge we posed before the last presidential election – individuals who came to us with bold policy ideas, but were also willing to put in the work to hammer those ideas into actionable forms, engage in dialogue with policymakers, and keep pushing for progress, celebrating both incremental and monumental steps toward change.

The thinking behind the Day One Project now has a track record of success – and the proud history of the Federation of American Scientists behind it. Since that initial batch of policy memos we unveiled nearly five years ago, we have launched 18 accelerators, with 183 participants – resulting in 132 additional policy memos and recommendations – all driven by policy entrepreneurs. We continue to mine for talent and remain committed to helping these individuals and teams refine their ideas – and it’s continuing to pay off. Groundwork laid in part by Lauren Shum’s memo about lead pollution from aviation fuel helped spur an endangerment finding from the EPA just this past October.

Now we sit on the verge of another Presidential election – and again FAS sees opportunity for meaningful, science-based policy innovations that can appeal to lawmakers on both sides of the aisle. That’s why we’re launching Day One 2025 – and renewing the call for bold policy ideas, grounded in science and evidence, that can tackle the country’s biggest challenges and bring us closer to the prosperous, equitable and safe future that we all hope for.

For this new effort, FAS has identified four priority areas where ideas and action are most sorely needed:

Government Capacity Policy and practice changes that enhance government’s ability to deliver, spanning talent, spending, culture, and more. 

One of my favorite Day One Project memos in this vein is about common-sense reforms to accelerate the “Authority to Operate” process for government tech by Mary Lazzeri, Dayton Williams, Greg Elin and Fen Labalme. 

Emerging Technologies and Global Risk The promise and peril of artificial intelligence, and the resurgent threat of nuclear conflict; emerging biorisks; safeguarding against planetary threats; all of these fields require robust approaches that will leverage technological progress, new policy frameworks and collaboration.

A great example in this vein is about establishing an AI Center of Excellence to address maternal health disparities by Kumba Sennaar and Grace Wickerson. 

Innovation and Competitiveness How can the U.S. better convert the strength of its R&D enterprise into shared prosperity and train it on the biggest challenges of the 21st century? 

We need more ideas to accelerate the development of thriving regional innovation ecosystems, foster the development of a K-12 education system that prepares students for tomorrow’s challenges, expand access to STEM talent pipelines, accelerate translation of promising innovations from lab to market, and more. 

Mark Lemley and Orly Lobel’s (now partially implemented) proposal for an array of strategies to ban non-competes to boost industry competition is a wonderful model of a memo focused on these questions.

Energy and Environment  Steps to accelerate a clean energy transition and ensure a world resilient to a changing climate. 

FAS’s own Zoë Brouns authored a memo on how community navigators could accelerate the distribution of federal climate funding. It’s one of many examples of great environmental policy recommendations already in our library.

We are again on the cusp of a massive policy window, an opportunity to arm a new or second-term administration with new ideas. Leading up to the launch of Day One 2025, FAS will be highlighting stories of policy entrepreneurs on our website. We hope these stories will be a reminder that great policy can come from anywhere – be it a young scientist yet to truly begin their career, or a policy veteran who’s served in the White House.

Maybe, as you read about the passion, persistence and imagination exhibited by one or all of these individuals, you’ll be inspired to try your hand at policy entrepreneurship with a policy proposal to make this country, and the world, a better place.

Automating Scientific Discovery: A Research Agenda for Advancing Self-Driving Labs

Despite significant advances in scientific tools and methods, the traditional, labor-intensive model of scientific research in materials discovery has seen little innovation. The reliance on highly skilled but underpaid graduate students as labor to run experiments hinders the labor productivity of our scientific ecosystem. An emerging technology platform known as Self-Driving Labs (SDLs), which use commoditized robotics and artificial intelligence for automated experimentation, presents a potential solution to these challenges.

SDLs are not just theoretical constructs but have already been implemented at small scales in a few labs. An ARPA-E-funded Grand Challenge could drive funding, innovation, and development of SDLs, accelerating their integration into the scientific process. A Focused Research Organization (FRO) can also help create more modular and open-source components for SDLs and can be funded by philanthropies or the Department of Energy’s (DOE) new foundation. With additional funding, DOE national labs can also establish user facilities for scientists across the country to gain more experience working with autonomous scientific discovery platforms. In an era of strategic competition, funding emerging technology platforms like SDLs is all the more important to help the United States maintain its lead in materials innovation.

Challenge and Opportunity

New scientific ideas are critical for technological progress. These ideas often form the seed insight to creating new technologies: lighter cars that are more energy efficient, stronger submarines to support national security, and more efficient clean energy like solar panels and offshore wind. While the past several centuries have seen incredible progress in scientific understanding, the fundamental labor structure of how we do science has not changed. Our microscopes have become far more sophisticated, yet the actual synthesizing and testing of new materials is still laboriously done in university laboratories by highly knowledgeable graduate students. The lack of innovation in how we historically use scientific labor pools may account for stagnation of research labor productivity, a primary cause of concerns about the slowing of scientific progress. Indeed, analysis of scientific literature suggests that scientific papers are becoming less disruptive over time and that new ideas are getting harder to find. The slowing rate of new scientific ideas, particularly in the discovery of new materials or advances in materials efficiency, poses a substantial risk, potentially costing billions of dollars in economic value and jeopardizing global competitiveness. However, incredible advances in artificial intelligence (AI) coupled with the rise of cheap but robust robot arms are leading to a promising new paradigm of material discovery and innovation: Self-Driving Labs. An SDL is a platform where material synthesis and characterization is done by robots, with AI models intelligently selecting new material designs to test based on previous experimental results. These platforms enable researchers to rapidly explore and optimize designs within otherwise unfeasibly large search spaces.

Today, most material science labs are organized around a faculty member or principal investigator (PI), who manages a team of graduate students. Each graduate student designs experiments and hypotheses in collaboration with a PI, and then executes the experiment, synthesizing the material and characterizing its property. Unfortunately, that last step is often laborious and the most time-consuming. This sequential method to material discovery, where highly knowledgeable graduate students spend large portions of their time doing manual wet lab work, rate limits the amount of experiments and potential discoveries by a given lab group. SDLs can significantly improve the labor productivity of our scientific enterprise, freeing highly skilled graduate students from menial experimental labor to craft new theories or distill novel insights from autonomously collected data. Additionally, they yield more reproducible outcomes as experiments are run by code-driven motors, rather than by humans who may forget to include certain experimental details or have natural variations between procedures.

Self-Driving Labs are not a pipe dream. The biotech industry has spent decades developing advanced high-throughput synthesis and automation. For instance, while in the 1970s statins (one of the most successful cholesterol-lowering drug families) were discovered in part by a researcher testing 3800 cultures manually over a year, today, companies like AstraZeneca invest millions of dollars in automation and high-throughput research equipment (see figure 1). While drug and material discovery share some characteristics (e.g., combinatorially large search spaces and high impact of discovery), materials R&D has historically seen fewer capital investments in automation, primarily because it sits further upstream from where private investments anticipate predictable returns. There are, however, a few notable examples of SDLs being developed today. For instance, researchers at Boston University used a robot arm to test 3D-printed designs for uniaxial compression energy adsorption, an important mechanical property for designing stronger structures in civil engineering and aerospace. A Bayesian optimizer was then used to iterate over 25,000 designs in a search space with trillions of possible candidates, which led to an optimized structure with the highest recorded mechanical energy adsorption to date. Researchers at North Carolina State University used a microfluidic platform to autonomously synthesize >100 quantum dots, discovering formulations that were better than the previous state of the art in that material family.

These first-of-a-kind SDLs have shown exciting initial results demonstrating their ability to discover new material designs in a haystack of thousands to trillions of possible designs, which would be too large for any human researcher to grasp. However, SDLs are still an emerging technology platform. In order to scale up and realize their full potential, the federal government will need to make significant and coordinated research investments to derisk this materials innovation platform and demonstrate the return on capital before the private sector is willing to invest it.

Other nations are beginning to recognize the importance of a structured approach to funding SDLs: University of Toronto’s Alan Aspuru-Guzik, a former Harvard professor who left the United States in 2018, has created an Acceleration Consortium to deploy these SDLs and recently received $200 million in research funding, Canada’s largest ever research grant. In an era of strategic competition and climate challenges, maintaining U.S. competitiveness in materials innovation is more important than ever. Building a strong research program to fund, build, and deploy SDLs in research labs should be a part of the U.S. innovation portfolio.

Plan of Action

While several labs in the United States are working on SDLs, they have all received small, ad-hoc grants that are not coordinated in any way. A federal government funding program dedicated to self-driving labs does not currently exist. As a result, the SDLs are constrained to low-hanging material systems (e.g., microfluidics), with the lack of patient capital hindering labs’ ability to scale these systems and realize their true potential. A coordinated U.S. research program for Self-Driving Labs should:

Initiate an ARPA-E SDL Grand Challenge: Drawing inspiration from DARPA’s previous grand challenges that have catalyzed advancements in self-driving vehicles, ARPA-E should establish a Grand Challenge to catalyze state-of-the-art advancements in SDLs for scientific research. This challenge would involve an open call for teams to submit proposals for SDL projects, with a transparent set of performance metrics and benchmarks. Successful applicants would then receive funding to develop SDLs that demonstrate breakthroughs in automated scientific research. A projected budget for this initiative is $30 million1, divided among six selected teams, each receiving $5 million over a four-year period to build and validate their SDL concepts. While ARPA-E is best positioned in terms of authority and funding flexibility, other institutions like National Science Foundation (NSF) or DARPA itself could also fund similar programs.

Establish a Focused Research Organization to open-source SDL components: This FRO would be responsible for developing modular, open-source hardware and software specifically designed for SDL applications. Creating common standards for both the hardware and software needed for SDLs will make such technology more accessible and encourage wider adoption. The FRO would also conduct research on how automation via SDLs is likely to reshape labor roles within scientific research and provide best practices on how to incorporate SDLs into scientific workflows. A proposed operational timeframe for this organization is five years, with an estimated budget of $18 million over that time period. The organization would work on prototyping SDL-specific hardware solutions and make them available on an open-source basis to foster wider community participation and iterative improvement. A FRO could be spun out of the DOE’s new Foundation for Energy Security (FESI), which would continue to establish the DOE’s role as an innovative science funder and be an exciting opportunity for FESI to work with nontraditional technical organizations. Using FESI would not require any new authorities and could leverage philanthropic funding, rather than requiring congressional appropriations.

Provide dedicated funding for the DOE national labs to build self-driving lab user facilities, so the United States can build institutional expertise in SDL operations and allow other U.S. scientists to familiarize themselves with these platforms. This funding can be specifically set aside by the DOE Office of Science or through line-item appropriations from Congress. Existing prototype SDLs, like the Argonne National Lab Rapid Prototyping Lab or Berkeley Lab’s A-Lab, that have emerged in the past several years lack sustained DOE funding but could be scaled up and supported with only $50 million in total funding over the next five years. SDLs are also one of the primary applications identified by the national labs in the “AI for Science, Energy, and Security” report, demonstrating willingness to build out this infrastructure and underscoring the recognized strategic importance of SDLs by the scientific research community.

Frequently Asked Questions
What factors determine whether an SDL is appropriate for materials innovation?

As with any new laboratory technique, SDLs are not necessarily an appropriate tool for everything. Given that their main benefit lies in automation and the ability to rapidly iterate through designs experimentally, SDLs are likely best suited for:

  • Material families with combinatorially large design spaces that lack clear design theories or numerical models (e.g., metal organic frameworks, perovskites)

  • Experiments where synthesis and characterization are either relatively quick or cheap and are amenable to automated handling (e.g., UV-vis spectroscopy is relatively simple, in-situ characterization technique)

  • Scientific fields where numerical models are not accurate enough to use for training surrogate models or where there is a lack of experimental data repositories (e.g., the challenges of using density functional theory in material science as a reliable surrogate model)

While these heuristics are suggested as guidelines, it will take a full-fledged program with actual results to determine what systems are most amenable to SDL disruption.

What aren’t SDLs?

When it comes to exciting new technologies, there can be incentives to misuse terms. Self-Driving Labs can be precisely defined as the automation of both material synthesis and characterization that includes some degree of intelligent, automated decision-making in-the-loop. Based on this definition, here are common classes of experiments that are not SDLs:

  • High-throughput synthesis, where synthesis automation allows for the rapid synthesis of many different material formulations in parallel (lacks characterization and AI-in-the-loop)

  • Using AI as a surrogate trained over numerical models, which is based on software-only results. Using an AI surrogate model to make material predictions and then synthesizing an optimal material is also not a SDL, though certainly still quite the accomplishment for AI in science (lacks discovery of synthesis procedures and requires numerical models or prior existing data, neither of which are always readily available in the material sciences).

Will SDLs “automate” away scientists? How will they change the labor structure of science?

SDLs, like every other technology that we have adopted over the years, eliminate routine tasks that scientists must currently spend their time on. They will allow scientists to spend more time understanding scientific data, validating theories, and developing models for further experiments. They can automate routine tasks but not the job of being a scientist.

However, because SDLs require more firmware and software, they may favor larger facilities that can maintain long-term technicians and engineers who maintain and customize SDL platforms for various applications. An FRO could help address this asymmetry by developing open-source and modular software that smaller labs can adopt more easily upfront.

What Works in Boston, Won’t Necessarily Work in Birmingham: 4 Pragmatic Principles for Building Commercialization Capacity in Innovation Ecosystems

Just like crop tops, flannel, and some truly unfortunate JNCO jeans that one of these authors wore in junior high, the trends of the 90’s are upon us again. In the innovation world, this means an outsized focus on tech-based economic development, the hottest new idea in economic development, circa 1995. This takes us back in time to fifteen years after the passage of the Bayh Dole Act, the federal legislation that granted ownership of federally funded research to universities. It was a time when the economy was expanding, dot-com growth was a boom, not a bubble, and we spent more time watching Saved by the Bell than thinking about economic impact. 

After the creation of tech transfer offices across the country and the benefit of time, universities were just starting to understand how much the changes wrought by Bayh-Dole would impact them (or not). A raft of optimistic investments in venture development organizations and state public-private partnerships swept the country, some of which (like Ben Franklin Technology Partners and BioSTL) are still with us today, and some of which (like the Kansas Technology Enterprise Center) have flamed out in spectacular fashion. All of a sudden, research seemed like a process to be harnessed for economic impact. Out of this era came the focus on “technology commercialization” that has captured the economic development imagination to this day. 

Commercialization, in the context of this piece, describes the process through which universities (or national labs) and the private sector collaborate to bring to the market technologies that were developed using federal funding. Unlike sponsored research and development, in which industry engages with universities from the beginning to fund and set a research agenda, commercialization brings in the private sector after the technology has been conceptualized. Successful commercialization efforts have now grown across the country, and we believe they can be described by four practical principles: 

Principle 1: A strong research enterprise is a necessary precondition to building a strong commercialization pipeline.

The first condition necessary to developing a commercialization pipeline is a reasonably advanced research enterprise. While not every region in the U.S. has access to a top-tier research university, there are pockets of excellent research at most major U.S. R1 and R2 institutions. However, because there is natural attrition at each stage of the commercialization process (much like the startup process) a critical mass of novel, leading, and relevant research activity must exist in a given University. If that bar is assumed to be the ability to attract $10 million in research funding (the equivalent of winning 20-25 SBIR Phase 1 grants annually), that limits the number of schools that can run a fruitful commercialization pipeline to approximately 350 institutions, based on data from the NSF NCSES. A metro area should have at least one research institution that meets this bar in order to secure federal funding for the development of lab-to-market programs, though given the co-location of many universities, it is possible for some metro areas to have several such research institutions or none at all.

Principle 2: Commercialization via established businesses creates different economic impacts than commercialization via startups; each pathway requires fundamentally different support.

When talking about commercialization, it is also important to differentiate between whether a new technology is brought to market by a large, incumbent company or start-up. The first half of the commercialization process is the same for both: technology is transferred out of universities, national labs, and other research institutions through the process of registering, patenting, and licensing new intellectual property (IP). Once licensed, though, the commercialization pathway branches into two. 

With an incumbent company, whether or not it successfully brings new technology to the market is largely dependent on the company’s internal goals and willingness to commit resources to commercializing that IP. Often, incumbent companies will license patents as a defensive strategy in order to prevent competition with their existing product lines. As a result, license of a technology by an incumbent company cannot be assumed to represent a guarantee of commercial use or value creation.

The alternative pathway is for universities to license their IP to start-ups, which may be spun out of university labs. Though success is not guaranteed, licensing to these new companies is where new programs and better policies can actually make an impact. Start-ups are dependent upon successful commercialization and require a lot of support to do so. Policies and programs that help meet their core needs can play a significant role in whether or not a start-up succeeds. These core needs include independent space for demonstrating and scaling their product, capital for that work and commercialization activities (e.g. scouting customers and conducting sales), and support through mentorship programs, accelerators, and in-kind help navigating regulatory processes (especially in deep tech fields). 

Principle 3: Local context matters; what works in Boston won’t necessarily work in Birmingham. 

Unfortunately, many universities approach their tech transfer programs with the goal of licensing their technology to large companies almost exclusively. This arises because university technology transfer offices (TTOs) are often understaffed, and it is easier to license multiple technologies to the same large company under an established partnership than to scout new buyers and negotiate new contracts for each patent. The Bayh-Dole Act, which established the current tech transfer system, was never intended to subsidize the R&D expenditures of our nation’s largest and most profitable companies, nor was it intended to allow incumbents to weaponize IP to repel new market entrants. Yet, that is how it is being used today in practical application.

Universities are not necessarily to blame for the lack of resources, though. Universities spend on average 0.6% of their research expenditures on their tech transfer programs. However, there is a large difference in research expenditures between top universities that can attract over a billion in research funding and the average research university, and thus a large difference in the staffing and support of TTOs. State government funding for the majority of public research universities have been declining since 2008, though there has been a slight upswing since the pandemic, while R&D funding at top universities continues to increase. Only a small minority of TTOs bring in enough income from licensing in order to be self-sustaining, often from a single “blockbuster” patent, while the majority operate at a loss to the institution. 

To successfully develop innovation capacity in ecosystems around the country through increased commercialization activity, one must recognize that communities have dramatically different levels of resources dedicated to these activities, and thus, “best practices” developed at leading universities are seldom replicable in smaller markets. 

Principle 4: Successful commercialization pipelines include interventions at the individual, institutional, and ecosystem level.

As we’ve discussed at length in our FAS “systems-thinking” blog series, which includes a post on innovation ecosystems, a systems lens is fundamental to how we see the world. Thinking in terms of systems helps us understand the structural changes that are needed to change the conditions that we see playing out around us every day. When thinking about the structure of commercialization processes, we believe that intervention at various structural levels of a system is necessary to create progres on challenges that seem insurmountable at first—such as changing the cultural expectations of “success” that are so influential in the academic systems. Below we have identified some good practices and programs for supporting commercialization at the individual, institutional, and ecosystem level, with an emphasis on pathways to start-ups and entrepreneurship.

Practices and Programs Targeted at Individuals

University tech transfer programs are often reliant on individuals taking the initiative to register new IP with their TTOs. This requires individuals to be both interested enough in commercialization and knowledgeable enough about the commercialization potential of their research to pursue registration. Universities can encourage faculty to be proactive in pursuing commercialization through recognizing entrepreneurial activities in their hiring, promotion and tenure guidelines and encouraging faculty to use their sabbaticals to pursue entrepreneurial activities. An analog to the latter at national laboratories are Entrepreneurial Leave Programs that allow staff scientists to take a leave of up to three years to start or join a start-up before returning to their position at the national lab.

Faculty and staff scientists are not the only source of IP though; graduate students and postdoctoral researchers produce much of the actual research behind new intellectual property. Whether or not these early-career researchers pursue commercialization activities is correlated with whether they have had research advisors who were engaged in commercialization. For this reason, in 2007, the National Research Foundation of Singapore established a joint research center with the Massachusetts Institute of Technology (MIT) such that by working with entrepreneurial MIT faculty members, researchers at major Singaporean universities would also develop a culture of entrepreneurship. Most universities likely can’t establish programs of this scale, but some type of mentorship program for early-career scientists pre-IP generation can help create a broader culture of translational research and technology transfer. Universities should also actively support graduate students and postdoctoral researchers in putting forward IP to their TTO. Some universities have even gone so far as to create funds to buy back the time of graduate students and postdocs from their labs and direct that time to entrepreneurial activities, such as participating in an iCorps program or conducting primary market research.  

Student at work in the NOAA CIGLR Lab at the University of Michigan School for Environment and Sustainability

Some universities have even gone so far as to create funds to buy back the time of graduate students and postdocs from their labs and direct that time to entrepreneurial activities, such as participating in an iCorps program or conducting primary market research.

Once IP has been generated and licensed, many universities offer mentorship programs for new entrepreneurs, such as MIT’s Venture Mentorship Services. Outside of universities, incubators and accelerators provide mentorship along with funding and/or co-working spaces for start-ups to grow their operation. Hardware-focused start-ups especially benefit from having a local incubator or accelerator, since hard-tech start-ups attract significantly less venture capital funding and support than digital technology start-ups, but require larger capital expenditures as they scale. Shared research facilities and testbeds are also crucial for providing hard-tech start-ups with the lab space and equipment to refine and scale their technologies.

For internationally-born entrepreneurs, an additional consideration is visa sponsorship. International graduate students and postdocs that launch start-ups need visa sponsors in order to stay in the United States as they transition out of academia. Universities that participate in the Global Entrepreneur in Residence program help provide H-1B visas for international entrepreneurs to work on their start-ups in affiliation with universities. The university benefits in return by attracting start-ups to their local community that then generate economic opportunities and help create an entrepreneurial ecosystem.

Practices and Programs Targeted at Institutions

As mentioned in the beginning, one of the biggest challenges for university tech transfer programs is understaffed TTOs and small patent budgets. On average, TTOs have only four people on staff, who can each file a handful of patents a year, and budgets for the legal fees on even fewer patents. Fully staffing TTOs can help universities ensure that new IP doesn’t slip through the cracks due to a lack of capacity for patenting or licensing activities. Developing standard term sheets for licensing agreements can also reduce administrative burden and make it easier for TTOs to establish new partnerships.

Instead of TTOs, some universities have established affiliated technology intermediaries, which are organizations that take on the business aspects of technology commercialization. For example, the Wisconsin Alumni Research Foundation (WARF) was launched as an independent, nonprofit corporation to manage the University of Wisconsin–Madison’s vitamin D patents and invest the resulting revenue into future research at the university. Since its inception 90 years ago, WARF has provided $2.3 billion in grants to the university and helped establish 60 start-up companies. 

In general, universities need to be more consistent about collecting and reporting key performance indicators for TTOs outside of the AUTM framework, such as the number of unlicensed patents and the number of products brought to the market using licensed technologies. In particular, universities should disaggregate metrics for licensing and partnerships between companies less than five years old and those greater than five years old so that stakeholders can see whether there is a difference in commercialization outcomes between incumbent and start-up licensees.

Practices and Programs Targeted at Innovation Ecosystems

Innovation ecosystems are made up of researchers, entrepreneurs, corporations, the workforce, government, and sources of capital. Geographic proximity through co-locating universities, corporations, start-ups, government research facilities, and other stakeholder institutions can help foster both formal and informal collaboration and result in significant technology-driven economic growth and benefits. Co-location may arise organically over time or result from the intentional development of research parks, such as the NASA Research Park. When done properly, the work of each stakeholder should advance a shared vision. This can create a virtuous cycle that attracts additional talent and stakeholders to the shared vision and can integrate with more traditional attraction and retention efforts. One such example is the co-location of the National Bio- and Agro-Defense Facility in Manhattan, KS, near the campus of Kansas State University. After securing that national lab, the university made investments in additional BSL-2, 3 and 3+ research facilities including the Biosecurity Research Institute and its Business Development Module. The construction and maintenance of those facilities required the creation of new workforce development programs to train HVAC technicians that manage the independent air handling capabilities of the labs and train biomanufacturing workers, which was then one of the selling points for the successful campaign for the relocation of corporation Scorpius Biologics to the region. At best, all elements of an innovation ecosystem are fueled by a research focus and the commercialization activity that it provides. 

For regions that find themselves short of the talent they need, soft-landing initiatives can help attract domestic and international entrepreneurs, start-ups, and early-stage firms to establish part of their business in a new region or to relocate entirely. This process can be daunting for early-stage companies, so soft-landing initiatives aim to provide the support and resources that will help an early-stage company acclimatize and thrive in a new place. These initiatives help to expand the reach of a community, create a talent base, and foster the conditions for future economic growth and benefits.

Alongside the creation of innovation ecosystems should be the establishment of “scale-up ecosystems” focused on developing and scaling new manufacturing processes necessary to mass produce the new technologies being developed. This is often an overlooked aspect of technology development in the United States, and supply chain shocks over the past few years have shone a light on the need to develop more local manufacturing supply chains. Fostering the growth of manufacturing alongside technology innovation can (1) reduce the time cycling between product and process development in the commercialization process, (2) capture the “learning by doing” benefits from scaling the production of new technologies, and (3) replenish the number of middle-income jobs that have been outsourced over the past few decades. 

Any way you slice it, commercialization capacity is one clear and critical input to a successful innovation ecosystem. However, it’s not the only element that’s important. A strong startup commercialization effort, standing alone, without the corporate, workforce, or government support that it needs to build a vibrant ecosystem around its entrepreneurs, might wane with time or simply be very successful at shipping spinouts off to a coastal hotspot. Building a commercialization pipeline is not, nor has it ever been, a one-size-fits-all solution for ecosystem building. 

It may even be something we’ve over-indexed on, given the widespread adoption of tech-based economic development strategies. One significant reason for this is the fact that entrepreneurship via commercialization is most open to those who already have access to a great deal of privilege–who have attained, or are on the path to, graduate degrees in STEM fields critical to our national competitiveness. If you’ve already earned a Ph.D. in machine learning, chances are your future is looking pretty bright—with or without entrepreneurial opportunity involved. To truly reap the economic benefits of commercialization activity (and the startups it creates), we need to aggressively implement programs, training, and models that change the demographics of who gets to commercialize technology, not just how they do it. To shape this, we’ll need to change the conditions for success for early-career researchers and reconsider the established model of how we mentor and train the next generation of scientists and engineers–you’ll hear more from us on these topics in future posts!

Developing a Mentor-Protégé Program for Fintech SBLC Lenders


The Biden Administration has recognized that small businesses, particularly minority-owned small businesses lack adequate access to capital. While SBA has operated its 7(a) Loan Program for multiple decades the program has historically shown poor results reaching minority-owned businesses and those in low- and moderate-income communities. Recently, the SBA has leveraged innovative fintech lenders to help fill this gap. 

While the agency has finalized a rule that would allow fintech companies to participate in the 7(a) Loan Program, there are significant concerns that new entrants would put the program at risk due to a lack of internal controls and transparent evaluation. To help increase lending to low- and moderate-income communities while not increasing the overall risk to the 7(a) Loan Program, SBA should establish a mentor-protégé program and conditional certification regime for innovative financial technology companies to participate responsibly in the SBA’s 7(a) Loan Program and ensure that SBA adequately preserves the safety and soundness of the program.

The Challenge

The Biden Administration has recognized that small businesses, particularly minority-owned small businesses lack adequate access to capital. While SBA has operated its 7(a) Loan Program for multiple decades, the program has historically shown poor results in reaching minority-owned businesses and those in low- and moderate-income communities. According to a 2022 Congressional Research Service report, “[i]n FY2021, 30.1% of 7(a) loan approvals ($10.98 billion of $36.54 billion) were [made] to minority-owned businesses (20.8% Asian, 6.0% Hispanic, 2.6% African American, and 0.7% American Indian)”. 

SBA has made a concerted effort previously to increase 7(a) small business lending to underserved communities by establishing the Community Advantage (CA) 7(a) loan initiative. Launched as a pilot program in 2011 and subsequently reauthorized, the CA loan initiative has been successful in encouraging mission-driven nonprofit lenders to underserved communities; however, the impact has been relatively small when compared to the traditional 7(a) loan program. In FY 2022, the CA Pilot Program approved just 722 loans totaling $114,804; whereas the general SBA 7(a) Loan Program approved 3,501 loans totaling $3,498,234,800–an order of magnitude of difference. 

The COVID-19 pandemic created an unprecedented demand for assistance to the country’s small businesses, as they were forced to close their doors and saw their revenues dwindle. Congress responded to this demand by passing the Coronavirus Aid, Relief, and Economic Security (CARES) Act, which established one of the largest government-backed lending programs ever, the Paycheck Protection Program (PPP). During the PPP, fintech lenders, which for this policy memo includes technology-savvy banks and nonbank financial institutions that operate online and through mobile applications, proved uniquely adept at serving small businesses in traditionally underserved communities, even without specific guidance to do so from the SBA. 

Many of the borrowers assisted by fintech lenders did not have pre-existing borrowing relationships with a financial institution and were therefore deprioritized by traditional financial institutions offering PPP loans, who favored lending to small businesses with existing relationships. Previously published research showed that not only did fintech lenders receive more applications from businesses from Black and Hispanic-owned businesses, but also extended a significant amount of lending to these businesses. Fintech lenders therefore expanded the impact of the PPP to underserved borrowers and successfully bolstered the efforts of mission-driven lenders, such as Community Development Financial Institutions and Minority Depository Institutions. For example, Unity National Bank of Houston, a Minority Depository Institution partnered with Cross River, a tech-focused bank that partners with fintech companies, to increase its lending from 500 loans to nearly 200,000 loans by leveraging Cross River’s lending technology.  Similarly, Accion Opportunity Fund, a large Community Development Financial Institution, partnered with Lending Club, another tech-focused lender, to improve both entities’ lending operations to borrowers that were underserved during the first round of the PPP. However, Community Development Financial Institutions and Minority Depository Institutions often face challenges procuring and implementing the technology needed to help scale their nontraditional lending activities, which limits the efficacy of their mission-driven lending in an increasingly internet-based lending environment. 

In an effort to increase access to capital and build on the efforts of fintech companies that successfully provided capital to small businesses in the Paycheck Protection Program, SBA has proposed lifting its moratorium on non-depository lenders participating in the program. SBA and the Biden Administration have shown real progress in removing the moratorium on Small Business Lending Company (SBLC) licenses to include fintech companies, which would expand the eligible participants in the program for the first time in 40 years. 

Expanding access to capital and support for small businesses is a key priority for the Biden Administration. Specifically, the Administration noted the importance of expanding underserved small business’ access to capital.  They recommended expanding the SBA’s 7(a) program by extending SBLC licenses to nonbank lenders, which include fintech companies, as one promising strategy. To this end, SBA has established a strategy of expanding its lending network by leveraging fintech companies. The SBA previously issued a proposed rulemaking to remove the moratorium on SBLC licenses and add three new categories of SBLC licenses.

However, policymakers and some industry participants have cast serious doubts on fintech companies’ participation in SBA’s 7(a) Loan Program, due to weak internal controls of unpartnered fintech companies and subsequent fraud issues experienced during the Paycheck Protection Program. Further, these critics have cited concerns with the agency’s ability to properly oversee these fintech companies due to a lack of ability to manage the fraud risks associated with developing or expanding a lending program that includes unpartnered fintech companies. Overall, the agency has shown that both it and fintech companies should improve their engagement together to ensure that the many program requirements are adhered to, and that SBA improves its abilities to mitigate potentially new or unique risks to the 7(a) Loan Program.

The Plan of Action

To solve the aforementioned issues, SBA should establish a mentor-protégé program and conditional certification regime for innovative nonbank financial technology companies to participate responsibly in the SBA’s 7(a) Loan Program. By creating a mentor-protégé program and conditional certification regime, SBA can continue to encourage the expansion of the 7(a) Loan Program to lenders that have shown their willingness and ability to lend to traditionally underserved small business borrowers, while ensuring that the agency adequately preserves the safety and soundness of the 7(a) Loan Program.

In the proposed mentor-protégé program, SBA would conduct an initial assessment of the fintech applicant and provide a conditional certification contingent on the fintech’s participation in the mentor-protégé program. To ensure that only the most well-suited fintech companies are allowed to engage in the 7(a) program, SBA should conduct a fair lending assessment. This would include a gap analysis of the company’s lending processes, akin to the existing interagency fair lending examinations conducted by the federal banking regulators. Further, SBA should require fintech companies to complete a “Community Lending Plan” detailing the specific small business lending activities the fintech company intends to complete in traditionally underserved areas. SBA would conduct a review of applications it receives and match them with banks that are established 7(a) lenders. 

To help ensure that both mentors and protégés develop throughout the program, SBA would need to create program criteria for both mentor banks and protégé fintech companies. Mentor criteria should focus on ensuring that mentor banks assist and grow the knowledge of their fintech proteges. Thus, both mentors and protégés should be required to complete periodic progress reports. Further, mentors should conduct their own periodic assessments of the fintech protégé’s compliance and lending processes to ensure that the fintech is able to comply with existing 7(a) Loan Program requirements and not create an undue risk to the program. These criteria should be determined based on the expertise of the Office of Capital Access and Office of Credit Risk Management with advice from SBA’s 8(a) Business Development Program staff. Lastly, to ensure that mentors and protégés can speak candidly about their experience with the other participant, SBA would need to create communication portals for both entities that are walled-off review by either participant. 

Recognizing the potential apprehension existing 7(a) lenders might have to eventually increasing competition to the 7(a) lending market, the SBA would need to incentivize banks to provide mentorship services to fintech companies by providing participating mentor banks with Community Reinvestment Act (CRA) credit and an increased SBA guarantee threshold for the bank’s 7(a) loans. By pursuing these two incentives, the SBA would provide banks with clear business and regulatory benefits from participating in the mentor-protégé program.

Based on a review of the SBA’s 2023 Congressional Budget Justification, SBA has accounted for much of the increased cost that would stem from expanding the 7(a) Lending Program to additional SBLCs. SBA noted that part of its $93.6 million request for fiscal year 2023 was to attract new lenders that participated in the Paycheck Protection Program. Similarly, SBA identified the need to continue building its oversight of Paycheck Protection Program and Community Advantage lenders. To this end, SBA requested an additional $13.9 million in small business lender oversight. Establishing the 7(a) mentor-protégé program would likely require only a small amount of additional funds relative to the 2023 requested amount. To account for the additional programmatic and administrative requirements needed to establish the 7(a) mentor-protégé program, SBA should include an additional $500 thousand to $1 million to its future Congressional Budget Justifications.

Success of the mentor-protégé program depends on robust program requirements and continuous monitoring to ensure the participants are adhering to the goal of responsibly expanding capital access to underserved small businesses. To accomplish this endeavor, SBA should leverage the internal expertise of its Office of Capital Access and Office of Credit Risk Management, while also coordinating with prudential and state financial services regulators to adequately understand the novel business models of fintech companies applying to and participating in the program. Interagency coordination between state and federal regulators will ensure that the 7(a) program’s integrity is maintained at the macro and micro levels.


Expanding small business lending to low- and moderate- income communities is an especially important endeavor. Few opportunities for real social and economic growth exist in these traditionally underserved communities without robust access to small business credit. While the importance of expanding access is clear, SBA has a responsibility to ensure that its flagship 7(a) Loan Program remains safe, sound, and available for the benefit of all small businesses. The recent decision to finalize rulemaking that would expand allowable lenders to the 7(a) Loan Program must come with careful consideration of which lenders should be able to participate. Incorporating fintech lenders presents an opportunity to solve the issues of small business lending to traditionally underserved communities. However, given the concerns identified throughout the rulemaking process and after its finalization, SBA should work diligently to ensure that only the best-suited entities are allowed to become 7(a) lenders. To help ensure that this occurs, they should create a mentor-protégé program that will afford fintech companies the best opportunity to succeed in the program while maintaining the safety and soundness that is so important to the overall success of the 7(a) Loan Program.

Frequently Asked Questions
How might your proposed action fit in within the broader priorities of the administration or relative agencies?

Expanding access to capital and support for small businesses is a key priority for the Biden Administration. Specifically, the Administration noted the importance of expanding underserved small business’ access to capital by expanding the SBA’s 7(a) program through extending SBLC licenses to nonbank lenders, which include fintech companies. To this end, SBA established a strategy of expanding its lending network by leveraging fintech companies. The SBA previously issued and finalized a rulemaking process to remove the moratorium on SBLC licenses and add three new categories of SBLC licenses.

What government agency, office, or body will lead this effort?

Success of the mentor-protégé program depends on robust program requirements and continuous monitoring to ensure the participants are adhering to the goal of responsibly expanding capital access to underserved small businesses. To accomplish this endeavor, SBA should leverage the internal expertise of its Office of Capital Access and Office of Credit Risk Management, while also coordinating with prudential and state financial services regulators to adequately understand the novel business models of fintech companies applying to and participating in the program.

What are the parameters of the program (establishment, oversight, etc.)?

The SBA can conduct an initial assessment of the fintech applicant and provide a conditional certification contingent on the fintech’s participation in the mentor-protégé program. Further, the SBA should develop program criteria for both mentor banks and protégé fintech companies and application portals for both entities. SBA would conduct a review of applications it receives. The SBA would incentivize banks to provide mentorship services to fintech companies seeking to gain SBLC certification by providing CRA credit banks and an increased SBA guarantee threshold for the bank’s 7(a) loans.

Why should we rely on for-profit fintech lenders, rather than non-profit or mission-led lenders to expand funding to underserved communities?

Providing equitable access to capital for underserved communities in our country will require actions beyond the scope of this policy recommendation, including changes to the regulations that govern community banks, fintech lenders, CDFIs, and other mission-driven lenders. Fintech lenders have a proven ability to contribute to this expansion of capital access, given their collective performance as PPP lenders. In addition, fintech lenders have an ability to scale the solutions that they provide quickly, something that CDFIs and other mission-led lenders have traditionally struggled to do well.

Why reform 7(a) as opposed to creating a new, fintech-specific lending program at the SBA?

Fintech lenders compete with conventional lenders for market share; the SBA should take care not to create programs that give one competing group an advantage over another. Creating a bespoke program, tailored to the needs of fintech lenders, would run the risk of creating more than an incidental competitive advantage. Instead, this program proposal advocates for utilizing a mentorship model that helps build strategic partnerships to accelerate access to capital for underserved groups, without creating separate rules or carve-outs.

ALI Releases Statement on the President’s FY2024

WASHINGTON, D.C. — The Alliance for Learning Innovation (ALI) applauds the increases proposed for education research and development (R&D) and innovation in the President’s budget request. These include the $870.9 million proposed for the Institute of Education Sciences (IES), including $75 million for a National Center for Advanced Development in Education (NCADE), the $405 million proposed for the Education Innovation and Research (EIR) program and the $1.4 billion for the National Science Foundation’s (NSF) Directorate for STEM Education. These investments represent real commitments to advancing an inclusive education research system that centers students, teachers, and communities.

These recommendations build upon the bipartisan interest in utilizing education R&D to  accelerate learning recovery, increase student achievement, and ensure students and teachers are prepared for the continued impact technology will have on teaching and learning. National and economic security depends on the success of our students and ALI appreciates the priorities this budget request places on fostering innovations in education that will support U.S. competitiveness.

Dan Correa, CEO of the Federation of American Scientists and co-lead of ALI notes, “Investments in education research and development hold so much promise for dramatically improving gaps in student achievement. Learning recovery, workforce development, and global competition all demand a pool of talent that can only come from an education system that meets the needs of diverse learners. The President’s budget request recognizes that more robust education R&D is needed to support bold innovations that meet the needs of students, teachers, families, and communities.”

This budget will allow IES and other federal agencies the ability to build on boundary-pushing efforts like the National AI Institute for Exceptional Education, which is supporting advancements in AI, human-AI interaction, and learning science to improve educational outcomes for children with speech and language related challenges.

For too long, federal support for education R&D has languished while resources and attention have been devoted to R&D in health care, defense, energy, and other fields. Today’s budget represents a critical step forward in addressing this deficiency. The Alliance for Learning Innovation looks forward to championing the continued development of an education R&D ecosystem that will lead to the types of groundbreaking developments and advancements we see in health care and defense; thus affording students everywhere access to fulfilling futures.

For more information about the Alliance for Learning Innovation, please visit

FAS Statement on President Biden’s FY2024 Budget Proposal

WASHINGTON, D.C. – Federation of American Scientists CEO Dan Correa released the following statement on President Joe Biden’s 2024 budget proposal:

“We’re pleased to see the Administration continuing its support for critical investments in science and technology. These investments are vital for achieving national goals  like excelling in AI and the bioeconomy, managing wildfire risks, and enhancing STEM training opportunities. It is also crucial to expand funding for tech and innovation hubs across the country. Robust support for science and innovation agencies is necessary to fulfill the national competitiveness vision of CHIPS and Science. But the budget request is only a first step, and we look forward to working with Congress this year to achieve the investments that strengthen American prosperity.”

The Federation of American Scientists (FAS) is a nonprofit policy research and advocacy organization founded in 1945 to meet national security challenges with evidence-based, scientifically-driven, and nonpartisan policy, analysis, and research. The organization works to advance progress on a broad suite of contemporary issues where science, technology, and innovation policy can deliver dramatic progress, and seeks to ensure that scientific and technical expertise have a seat at the policymaking table.

Find more ideas aimed at today’s greatest challenges in FAS’ report: Science and Innovation in the 118th Congress. You can also explore further – or submit your own ideas through FAS’ Day One Project.

CHIPS and Science Highlights: Developing a Scientific Workforce of the Future

With the goal of jump-starting American innovation post-pandemic, and building a foundation for the challenges of the future, including in artificial intelligence, quantum computing, and semiconductor manufacturing, the CHIPS and Science Act was signed into law. The multi-year legislative effort  started as an attempt to build upon Vannevar Bush’s legacy, with a bill titled the “Endless Frontier Act” named after Bush’s famous report, “Science, The Endless Frontier.” But as Congress looked at creating a vision for science in America, almost everyone was focused on how much money the bill authorizes for scientific research. But there are many often-overlooked sections of Bush’s original report that are just as important to today’s scientific enterprise as the overall budget. In particular, what has been missing from the public discussion is his focus on the development of scientific talent.

There is no question that our science-funding institutions need significant investment and reform, but funding is only part of the puzzle. As Bush noted in the Endless Frontier, “the most important ways in which the Government can promote industrial research are to increase the flow of new scientific knowledge through support of basic research and to aid in the development of scientific talent.”

Authors of the CHIPS and Science Act clearly took note. After months of negotiations between the House and the Senate, the hard work of the staff who recognized this imperative was thus reflected in the final text of this legislation. Let’s look at some of these provisions.

Expanded GRFPs

The legislation increases the number of Graduate Research Fellowships from 2,000 to 3,000 per year. The GRFP is the National Science Foundation’s premier fellowship for graduate students in science and engineering, and it provides three years of support for exceptional students to pursue their research. The GRFP has an impressive track record: over forty Nobel Laureates and over four hundred and fifty members of the National Academy of Science started their graduate research with the help of GRFP. Aside from all the good company the award puts you in, the GRFP provides students the flexibility to work with an advisor that aligns with their interests rather than settling for whoever has money available to fund them, potentially stifling their potential. That is a big deal for these graduate students who’re still early in their career and whose interests may evolve over the years. A recent report looking at the success of GRFP recipients found that GRFP participation increased students’ likelihood of PhD completion. Fellows also published more peer reviewed papers, gave more presentations at national or international meetings, and were awarded more grants and contracts as a PI after graduate school. It also found that women who were awarded a GRFP filed more patents in graduate school than non-GRFP recipients.

Combatting Sexual Harassment in Science

In 2018, the National Academies released a report which looked at the factors that contribute to an environment tolerant of sexual harassment and its impact on women’s careers. The negative outcomes students experience when they are sexually harassed include: declining motivation to attend class, greater truancy, dropping classes, paying less attention in class, receiving lower grades, changing advisors, changing majors and transferring to another educational institution or dropping out. Additionally, Gender harassment that is severe or occurs frequently over a period of time can result in the same level of negative professional and psychological outcomes as isolated instances of sexual coercion. Therefore, Gender harassment, which is often considered a “lesser,” more inconsequential form of sexual harassment, cannot be dismissed when present in an organization. This further showed up in a recent survey conducted by the Association of American Universities to study the campus climate across 33 research universities. The survey found that 41.8 percent of all students have experienced sexual harassment since enrolling, and 18.9 percent of students have experienced sexual harassment that interfered with their academic or professional performance, limited their ability to participate in an academic program, or created an intimidating, hostile, or offensive social, academic, or work environment. Among women graduate and professional students who were sexually harassed, nearly one in four reported that the perpetrator was a faculty member or instructor. The Combating Sexual Harassment in Science Act included in the CHIPS and Science Act addresses key recommendations from the report and builds on steps that have already been taken to address this issue. The legislation will establish a grant program for research into the causes and consequences of sexual harassment, issue policy guidelines for agencies making extramural research awards, convene an interagency working group to coordinate efforts, and assess the progress of these efforts over time. The bill authorizes over $32 million in spending to enact this provision, making it one of the most aggressive commitments by the federal government to combat sexual harassment in science.

A Focus on Good Mentoring and Good Mental Health

The CHIPS and Science Act also increases NSF’s focus on mentorship as a workforce development tool by establishing new programs to promote mentoring relationships between graduate students and PIs, including an expansion of Individual Development Plans for graduate researchers. These programs will help ensure that all scientists have access to quality mentors who can guide them through their careers—a critically important component to ensuring success in science as laid out by a 2019 report by the National Academies. The legislation also directs NSF to support research on graduate education system and outcomes of various interventions including the effects of traineeships, fellowships, internships, the effects of graduate education and mentoring policies and procedures on degree completion, development and assessment of approaches to improve mentorship, and to research, collect and assess data around graduate student mental health crisis and developing strategies to support graduate student mental health. 

These provisions only scratch the surface. The bill includes many more provisions that would ensure we develop a scientific workforce that will be ready to tackle the challenges of the future. If we want to keep America at the forefront of scientific discovery, we need to make sure that we are constantly replenishing our pool of scientists with the best and brightest minds. The investment in future scientists contained in the CHIPS and Science Act will pay dividends not just for those individuals but for our country as a whole. By nurturing the next generation of scientific talent, we can ensure that America remains a world leader in science and technology for generations to come.

CHIPS and Science Highlights: Regional Innovation

The passage of the much-discussed “Chips and Science Act” (CHIPS+) promises an injection of more than $50 billion to energize the U.S. semiconductor industry. This is a catalyzing moment. And yes, it represents an investment slightly larger than the Apollo Program, in real terms

The long list of new programs funded and authorized in CHIPS+ includes a flagship program of the National Science Foundation’s Technology Innovation and Partnerships Directorate (NSF TIP), the first new Directorate to be created at the NSF since the C+C Music Factory was topping the charts. The NSF Regional Innovation Engines Program (colloquially called NSF Engines), now officially authorized by Congress, joins a series of aggressive investments in regional cluster development programs at other agencies. These contemporary programs include the Economic Development Administration’s Build Back Better Regional Challenge and Good Jobs Challenge, which represent a combined $1.5 billion in appropriations. 

CHIPS+ also includes an additional authorization (if not funding) for the EDA’s work to develop regional innovation capacity across the country, including two major elements: a $10 billion regional tech hub program with outposts in every EDA region and a $1 billion tech hub development program intended “distressed communities” (originally included in the Recompete Act).  

These three new programs, NSF Engines, Tech Hubs and Recompete, plus existing programs like BBBRC and GJC, represent a massive proposed investment in building regional innovation clusters. Both legislation and the zeitgeist dictate that these investments will be distributed across the country, virtually guaranteeing geographic inclusion. But as regional innovation ecosystems and cluster development efforts become the dominant mode of economic development strategy, we would do well to consider the degree to which these efforts drive broad wealth creation, creating inclusive opportunity in our communities. 

But this bill’s least-discussed impact will likely be its most transformative. The CHIPS+ investment puts an exclamation point on an ongoing narrative–that the federal government has effectively declared cluster development to be the dominant way in which Washington thinks about supporting local economic development efforts. 

This mode of targeting the co-location and creation of like-minded firms in a close geographic area was pioneered by Michael Porter, the father of modern competitive strategy. These groups, or clusters, of companies in a particular industry, share critical infrastructure like equipment, space, and talent in ways that maximize regional efficiency and increase firm productivity.  “A cluster,” Porter said, “allows each member to benefit as if it had greater scale or as if it had joined with others without sacrificing its flexibility.” Building targeted, relevant, and world-class research and commercialization capacity at Universities was added as a prerequisite tenet over time. Modern cluster development theory–the economic development philosophy so central to CHIPS+–is the practice of engaging universities, government, corporations, capital providers, and entrepreneurs as stakeholders to create comparative local advantage in a global context by driving the development of a cluster of innovation-led companies. 

Cluster development, however, is not always executed in an inclusive and equitable way, and it’s easy to see why. Today, many communities approach cluster development as a conversation between R1 universities, corporate executives, top government staffers, and elite economic development leaders. While these approaches are effective in driving short-term resources and focus to support these efforts, they often omit the voices and views of communities that have been systemically left behind–those that they allude to as benefitting from the increased productivity, efficiency, job creation, wealth creation, and research activity that these efforts promote. For instance: the creation of “good jobs” (and especially “good jobs” in STEM fields) is an oft-measured outcome of cluster development efforts, but people who identify as Black and Hispanic make up just 9% and 8% of the employment in STEM fields, respectively. This is a stark outcome that lays bare the failure of traditional economic development efforts to engage diverse communities in the work of cluster development. This will not change unless time and resources are dedicated to starting conversations that are shrugged off today.

Conversely, when communities that have experienced disinvestment start new innovation and small business support efforts, they seldom turn to the institutions that have left their communities underserved for decades. It is more common for grassroots efforts to emerge, led by determined local leaders, as they did in Kansas City with the development of G.I.F.T., La Placita, the Prospect Business Association, The Prospect, and others (these represent just a few of many such efforts in Kansas City alone).  

This bottom-up approach has led to vibrant, innovative, and extremely well-networked small business ecosystems. In this context, trust (not funding) is the essential currency driving entrepreneurial ecosystems. Yet, trust-building is an inherently time-intensive, complex process that is seldom funded by government programs, philanthropy, or anyone else. 

So how might cluster building efforts more scalably and thoughtfully engage in the trust building activities that are required to make their work more inclusive and equitable? How might the institutions leading cluster development conversations invite engagement in the process of cluster selection, when the cluster in question seems inaccessible, and therefore irrelevant to large swaths of their communities? How can we integrate the systems that have been created to support small businesses and those that support innovation-driven enterprises in ways that emphasize their interdependence, as is characteristic of true ecosystems? These are the questions that our next generation of cluster development efforts must address. 

Today, as we begin to emerge from the COVID-19 pandemic, we can see the ways in which the impact has brought to light long-present inequities. For instance: only 8.6% of PPP loans were distributed to Black-owned businesses, but then again, Black-owned firms experienced persistent challenges in accessing capital relative to white-owned firms long before COVID, controlling for similar levels of creditworthiness. Yes, underserved communities were disproportionately impacted by the COVID-19 pandemic, but the systemic problems that these recent failures represent have been present for many years. 

Perhaps even more troubling is the fact that we continue to build for the future without considering the fact that great ideas come from everywhere and everyone. The proliferation of new technologies is often impacted by old systems–which means that critical infrastructure for building innovation ecosystems is widening. Today, 20% of disproportionately low-income, Black, Hispanic, and rural Americans lack access to broadband–this represents, essentially, digital redlining. Clearly, the challenge of achieving equitable innovation outcomes is both urgent and systemic, as our solutions must be.  

As we enter the age of cluster development and regional innovation ecosystem building, we can take comfort in knowing that geographic diversity has been designed as a condition of our investments. But to build a system in which innovation truly can come from anyone, anywhere will take trust-building. It will take time, care, and a willingness to engage unusual voices in coalition efforts. We will need to carefully consider how these efforts might have a more equitable impact than past movements to grow high-tech and deep-tech companies, in order to be successful. 

We have an opportunity to design this approach into these new regional innovation funding mechanisms, just as we designed in geographic diversity. Just as importantly, we have the opportunity to proactively answer these questions in communities across the country. With that in mind, this author offers a humble prediction–that our next generation of breakout innovation clusters will be those that engage their communities most inclusively, not just those that develop efficiently. 

Industrial Policy Memo

This summer, National Economic Council Director Brian Deese articulated a new vision for a robust and equitable U.S. industrial policy. The strategy seeks to help us reach the full potential of American competitiveness while delivering justice, equity, and prosperity to all citizens.

To inform the Administration’s new strategy, we pulled together a curated set of ideas from our extensive portfolio of nonpartisan, actionable ideas in science and technology policy. These ideas were diversely sourced from more than 300 Day One contributors — including students, academics, activists, industry leaders, local and international government officials, and more.​

Our letter addresses each of the industrial strategy’s core pillars:

Pillar I: Supply-Chain Resilience
Pillar II: Targeted Public Investment
Pillar III: Public Procurement
Pillar IV: Climate Resilience
Pillar V: Equity

​We hope that these ideas help advance the vision of a modern industrial policy that benefits all Americans.

Read the full memo at Day One Project

How to Unlock the Potential of the Advanced Research Projects Agency Model


America faces a host of daunting problems that demand forward-looking solutions. Addressing these challenges will require us to unleash the full potential of our research and development community, leveraging new approaches to innovation that break through both technical and institutional barriers and initiate wholly new capabilities. The Advanced Research Projects Agency (ARPA) model has resulted in exactly this kind of high-impact innovation in defense, intelligence, and energy. This model can be applied to other critical societal challenges such as climate, labor, or health. But an ARPA must have the right core elements if it is to create the fresh solutions the country needs.

The ARPA model is distinctly different from other federal agencies in mission, operations, and culture. ARPA organizations are part of a much broader ecosystem that spans from research to implementation. Their role is to create breakthrough, paradigm-shifting solutions and capabilities. In order to position a new ARPA for success, Congress, the Administration, and the agency’s founding leaders must understand the unique properties of an ARPA and the process by which ARPAs approach and manage risk to develop game-changing advances.

To establish a strong foundation for a new ARPA to do this work, Congress and the Administration will need to address four factors:

Over the course of a few years, a new ARPA can grow into a powerfully effective organization with people, practices, and culture honed to create breakthroughs. If well implemented, new ARPAs can be extraordinary additions to our R&D ecosystem, providing unimagined new capabilities to help us meet our most essential societal challenges.

Challenge and Opportunity

America faces some daunting problems today. Many millions of Americans are unable to access our nation’s rich opportunities, leaving all of us poorer without their contributions. Dozens of other countries have longer life spans and lower infant mortality rates, although we spend more per capita on healthcare than any other country. We are not yet on track to contain the damages of a changing climate or to manage its impacts. Global competition has resulted in more and more U.S. research advances being used to create jobs elsewhere. R&D alone won’t solve any of these problems. But every one of these challenges demands creative new solutions.

However, America’s phenomenally productive R&D ecosystem—with its half a trillion dollars spent annually by the public and private sectors—is not aimed at these large, society-wide challenges. How do we create a generational shift in our innovation ecosystem so that it contributes as much to meeting this century’s challenges as it did for those of the last century? What can we learn from our successful R&D history, and what approaches can we adapt to address the problems that we now face?

One part of the answer lies in the Advanced Research Projects Agency (ARPA) model for innovation. This kind of innovation knocks down both technical and institutional barriers to create transformational new capabilities. ARPA organizations are part of a much broader ecosystem, spanning from research to implementation, in which their role is to create breakthrough solutions and capabilities that fundamentally change what we define as possible. In pursuit of revolutionary advances, they accept and manage a level of risk for which companies and other government agencies have no incentive.

The first ARPA, the Defense Advanced Research Projects Agency (DARPA), was launched in 1958 at the height of the Cold War. DARPA shifted military capabilities from mass bombing to precision strike with GPS, stealth technologies, and integrated combat systems. These innovations recast defense systems, changed military outcomes, and shaped geopolitics over decades. Meanwhile, DARPA’s programs in enabling technologies also seeded artificial intelligence, developed advanced microelectronics, and started the internet. In recent years, DARPA programs have built the first ship able to navigate from the pier and cross oceans without a single sailor on board,1 created a radical new approach to reconfigurable military capabilities to outpace global adversaries,2 developed the first systems—now in operation by the Port Authority of New York and New Jersey—for cities to continuously monitor for dangerous nuclear and radiological materials,3 and created a rapid-response mRNA vaccine platform4 that enabled the astonishingly fast development5 of today’s mRNA vaccines for COVID-19.

We are also starting to show that the ARPA model can be successfully adapted to other national purposes. In 2006, the Intelligence Advanced Research Projects Activity (IARPA) was formed to serve the intelligence community. One of IARPA’s programs has developed methods to overcome individual cognitive biases by weighting and synthesizing the judgments of many analysts. This approach provides important gains in prediction and is a new paradigm for forecasting events in a complex world. In 2009, the Advanced Research Projects Agency–Energy (ARPA-E) launched in the Department of Energy. Its programs have created new power semiconductors, new battery technologies, and new methods to improve appliance efficiency, making vital contributions to our clean energy future. Both ARPAs have invigorated R&D communities by connecting them to hard, important problems and giving them a pathway to drive impact.

Implementing the ARPA model to meet other critical challenges could have enormous impact. Indeed, President Biden has already proposed ARPAs for health and climate,6 and others have advanced visions for ARPAs for agriculture,7 labor8 and education. In addition, the Endless Frontier Act9 takes inspiration from the ARPA model in its vision for an expanded technology function at NSF to address economic competitiveness.

Behind each call for an “ARPA for X” is a yearning for R&D that throws open new doors to radically better solutions. But the ARPA model is very different from other federal agencies and unlocking its potential will require much more than affixing the name. The starting point is an understanding of how ARPAs generate their outsized advances.

Though specifics vary according to the mission of a new ARPA, the essential operating model is based on these elements:

ARPA Programs

An ARPA generates major advances through intelligently managed risk-taking. The fundamental unit of work for an ARPA is a solutions-oriented R&D program that aims at achieving a previously unimaginable goal. Each program has a fixed term, typically 3-5 years, and each is designed, executed, and transitioned by an ARPA program manager.


The program manager designs the program to achieve a bold goal—one that may seem impossible but that, if demonstrated, could catalyze a major advance. They build a rigorous plan to achieve the goal. A set of questions known as the Heilmeier Catechism10 (from an iconic DARPA director in the 1970s) guides program development:

These questions are easy—even obvious—to ask, but surprisingly difficult to answer well. Program managers typically grapple with them over 6-12 months to design a strong program, and agency leaders use them to guide their judgement about the potential of a new program for approval. The questions also guide program execution.


Once a program is launched, the program manager contracts with whichever organizations are needed to achieve the program’s goal. That typically means companies, universities, nonprofits, other parts of government, and other organizations with the talent and capacity to conduct the necessary R&D. Contracting this work has the obvious benefit that the ARPA doesn’t have to hire staff and provide facilities for this R&D. But even more important is the fact that this approach mobilizes individuals and organizations. Over the course of the program, these participants become a community that not only delivers the program vision but can help drive it forward beyond the term of the ARPA program.

The work of the program is to weave the threads of research from multiple domains together with lessons from the reality of use and practice in order to develop and demonstrate prototype systems or capabilities. The program rigorously evaluates how well its innovation works, how it works in specific environments, and how it can be scaled. 

An ARPA program often draws on basic research and often generates fresh research, but research is an input rather than the objective. Unlike the management of basic research, these programs drive to a specific goal. They may sometimes resemble product development, but for a prototype product that serves a public purpose rather than a visible market opportunity. Often, they require a much higher degree of risk than product development because they reach for a barely feasible goal. 

An ARPA program aims to demonstrate that a powerful new approach can work despite the risk inherent in trying something radically different. This requires actively managing the multiple efforts within the ARPA program. An ARPA program manager accelerates lines of work that show great promise and redirects or stops work that is not yielding results. They nimbly reallocate resources to keep wringing out risk and driving to the program’s objective.  


In parallel, the program manager engages the decision makers who can advance, adopt, implement, and fully scale the results of the program. If the breakthrough will require commercialization, that could include additional companies, investors, and entrepreneurs. If full-scale implementation requires changes in policies and practices, that means engaging regulators, policy makers, and community organizations. Understanding the needs and realities of implementers is important from the early stages of program design. It is sometimes the case that these implementers are skeptical about the program’s bold goal at the start. As the program unfolds, they are invited to program reviews and demonstrations. The program strives to address their concerns and may even provide support for their internal analyses, evaluations, and trials. When these engagements work well, the ARPA program manager is able to bring implementers along on the journey from wild dream to demonstrated reality. Successful transition starts when they change their minds about what’s possible. And the ultimate societal impact of the ARPA program comes when these implementers have fully scaled the ARPA breakthrough. 

A fully successful program ends with a convincing demonstration of a new capability; a community that can carry it forward; and decision makers who are ready to support and fund implementation in products, services, policies, and practices.

ARPA program managers

None of this can happen without exceptionally capable program managers. An ARPA organization hires program managers on fixed terms to design, manage, and transition these high-impact programs. ARPA leadership coaches program managers, helps build partnerships and remove obstacles, and approves and oversees all programs. But it puts enormous responsibility and authority on the shoulders of program managers. 

ARPA program managers come from backgrounds in companies, universities, nonprofits, and other parts of government, and they serve at different times in their careers. They bring a “head in the stars, feet on the ground” blend of these key characteristics: 

ARPA portfolios

ARPA leadership approves a series of individual programs, constructing and managing a full portfolio that is diversified to maximize total impact despite the risk inherent in each program. Every program learns, not all succeed, and failure is accepted as integral to the mission.

Plan of Action 

Based on these core elements of a successful ARPA model, we offer four recommendations for policy makers as they establish new ARPA organizations. 


Clearly and succinctly define the vital national purpose for the new ARPA. An ARPA exists to create breakthroughs for an important public need. For DARPA, this is national security. For ARPA-E, it is economic and energy security, and for IARPA, it is national intelligence. 


Set up the agency to function autonomously, with its own budget, staff and organization, and operating practices. An ARPA is a deliberate counterpoint to work already underway, originating from a recognition that something more and different is needed to achieve our national goals. An ARPA will not succeed if it is tightly integrated into its parent organization. Ironically, it may be more difficult to start a successful new ARPA in an area that already has robust federal research, because of the inclination to fit the square-peg ARPA into round-hole traditional research methods. The ARPA model is completely different than our well-honed approach to sponsoring fundamental research. The ARPA solutions-driven approach would not work well for greatly needed and highly valued basic research, and conversely, funding methods for fundamental research will not lead to ARPA-scale breakthroughs for our societal problems. This work is different, and it will require different people, different practices, and a different culture to succeed. 

Independent funding is also necessary. To develop a portfolio of programs with the potential for high impact, an ARPA requires funding that is sufficient to achieve its programs’ objectives. ARPA programs are sized not just to generate a new result, but to convincingly demonstrate a new approach, often across a variety of circumstances, in order to prove that the method can succeed and scale. 

The agency’s chain of command and Congressional authorizers and appropriators provide important oversight. However, the ARPA organization itself must bear the responsibility for designing, selecting, managing, and transitioning its programs. A new ARPA should report directly to the cabinet secretary to maintain independence and secure the support needed to achieve its mission. 


Give the new ARPA flexible hiring and contracting authorities to draw new and extraordinary talent to the nation’s challenges. Flexible hiring mechanisms have proven to be very valuable in allowing ARPAs to attract the rare combination of expertise, vision, and execution required in great program managers. In addition, program managers must be able to contract with exceptional people and teams in companies, universities, nonprofits, and other government entities to achieve their aggressive program goals. ARPAs have used flexible contracting mechanisms to move fast and work effectively with all kinds of organizations, not just those already designed to work with government.

Flexible hiring and contracting authorities are extremely helpful tools for an ARPA organization. It’s worth noting, though, that flexible authorities by themselves do not an ARPA make. 


Appoint an exceptional leadership team, hold them to a high standard for impact, and create room for them to deliver on the full potential of the ARPA model. A new ARPA’s director will be responsible for building an organization with people, practices, and culture honed for the mission of creating breakthroughs. This person must bring fresh and creative ways of looking at seemingly impossible problems, a rigorous approach to managing risk, a drive to achieve outsized impact, and an ability to lead people. A strong ethical orientation is also essential for a role that will grapple with the implications of powerful new capabilities for our society. 

The person to whom the ARPA director reports also plays an essential role. This individual must actively prevent others from trying to set the agenda for the ARPA. They enable the ARPA organization to hire program managers who don’t look like other department staff, undertake programs that conventional wisdom decries, manage programs actively, and develop a culture that celebrates bold risk-taking in pursuit of a great national purpose. They hold the ARPA organization accountable for the mission of creating breakthroughs and create room for the unconventional methods needed to realize that mission. 

Note that these four recommendations about purpose, independence, authorities, and leadership are interconnected. All are necessary to build the foundation for a successful new ARPA, and cherry-picking the easy ones will not work. 


A total of 87 years of experience across three different ARPA organizations have provided many lessons about how to build and run an organization that creates breakthroughs for an important national purpose. In establishing any new ARPA, both Congress and the Administration must create the space and allocate the resources that will allow it to flourish and realize its mission. 

Like its programs, a new ARPA will itself be a high-risk, high-reward experiment. If our challenges were modest, or if our current innovation methods were sufficient, there would be no need to try these kinds of experiments. But the problems we face today demand powerful new approaches. Adapting the ARPA model and aiming it at the most critical challenges ahead can create breakthroughs that redefine what is possible for our future. Let’s do everything possible to start new ARPAs on the right track/

Frequently Asked Questions
What is an Advanced Research Projects Agency (ARPA)?

ARPAs create radically better approaches to hard problems by conducting solutions-oriented R&D. The Department of Defense (DOD)’s Defense Advanced Research Projects Agency (DARPA), now in its seventh decade, conducted the pivotal R&D for new military capabilities such as stealth and precision strike and, more broadly, for new information technologies ranging from the internet to artificial intelligence. DARPA’s track record inspired the establishment of the Department of Energy’s ARPA-E and the Office of the Director of National Intelligence’s IARPA. Both of these new ARPAs are well underway, with robust portfolios of R&D programs and encouraging results. They show that it is possible to adapt DARPA’s model for different public purposes.

Who leads an ARPA? Who will this person report to?

For the independence, authority, and responsibility that a new ARPA requires, its Directorship should be a senior appointment reporting directly to the Secretary of the appropriate department. If this role is filled by a Senate-confirmed Presidential appointment, it will be important for stability to have a civil servant to serve as the Deputy Director.

How does an ARPA coordinate its work with other organizations?

ARPA leaders and program managers communicate with their entire ecosystem: other parts of government, the R&D community, and the entities that can implement and scale ARPA results. An ARPA holds the responsibility for selecting and executing its programs.

DARPA and ARPA-E create new technologies, but that’s not what we need for social problems. How does the ARPA model apply to these very different challenges?
For any new ARPA, the model needs to be adapted to its context. For example, a promising
solution for a social problem may come from implementing new insights from behavioral science.
It is helpful to think about the desired future state a program will aim to realize, and then work
backwards to the new approaches, methods, or tools that could enable it, as well as the
institutional changes that will be needed. These solutions may or may not involve technology.
How can a new ARPA be successful without a customer like the Department of Defense to procure what it creates?
For DARPA programs that create revolutionary prototypes of military systems, DOD is indeed
the customer. But the internet, miniaturized GPS receivers, microelectromechanical systems,
and new waves of artificial intelligence did not make their mark through Pentagon procurement. As part of the design of an ARPA program, the program manager needs to think
through how their advance could be adopted and fully scaled. That could involve a
government agency that procures a product or service, companies that commercialize the
results, policy makers or regulators who can design rules and laws that are more effective
because of the program’s results, and/or other avenues

Accelerating Deployment of Innovations to Modernize the U.S. Electric Grid

Grid modernization should be a major part of a national infrastructure-investment initiative. Effectively and efficiently modernizing the U.S. electric grid requires rapid deployment of innovative grid technologies. The next administration should establish a Grid Resilience Innovation Demonstration (GRID) Network, run in partnership between the Department of Energy (DOE) and the Department of Defense (DoD), to test and accelerate deployment of such technologies. The GRID Network would integrate and build on existing microgrids on federal installations and other relevant facilities, resulting in a group of geographically distributed test beds that can be managed and operated as a national user facility. The distributed nature of the network would allow test beds to ensure that solutions are compatible with a variety of grid technologies and operational structures and would also insulate the network from security threats, and other risks. Prioritizing establishment of the GRID Network early in the next administration will enable our nation to quickly realize the benefits of a modern electric grid, including enhanced resilience to natural disasters, entrepreneurship opportunities, and job growth. Failure to act will leave our national grid vulnerable to hostile actors, rob the country of needed shovel-ready construction projects and manufacturing jobs, and undermine U.S. leadership in electric sector innovation and the resulting impacts to our economy.

Challenge and Opportunity

The U.S. electric grid is a critical backbone of our nation’s economy, national security, health, and social interactions. Yet the current grid is ill-suited to modern demands. Our nation’s grid contains many critical components that were originally constructed in the early 20th century. The grid as a whole is based on an outdated structure that was not designed for today’s varying power demand requirements, such as for the internet data centers, or for the widescale integration of intermittent sources of electricity such as wind turbines and solar panels. The grid is also poorly equipped to withstand the many cyber, physical, and electromagnetic threats that exist today. 

These problems can cause extensive and expensive blackouts, such as the widespread outages across the Northeast in 2003 that cost $6 billion in damages. The possibility of foreign interference presents a threat multiplier. In 2015, a Russian assault on the Ukrainian grid cut power for six hours in the dead of winter. A similar attack on the U.S. grid is possible. In fact, the same malware the triggered the Ukraine attack has been found in US-based critical infrastructure facilities. 

There is a clear need to make the U.S. electric grid much more secure to thwart attacks, robust to withstand physical threats, resilient to ensure rapid and full recovery from adverse impacts, stronger to accommodate greater demands, and flexible to enable a broader deployment of clean-energy technologies.

Yet grid modernization is easier said than done. The U.S. electric grid is a massive, complex system that comprises various technologies for electricity generation, transmission, and distribution as well as multiple operators, regulators, and markets to ensure the continual flow of electricity. Few incentives or financially-attractive opportunities exist for grid stakeholders to demonstrate and deploy innovative models and technologies. And finally, the national-security benefits of a secure, robust, and resilient grid do not deliver direct, sufficient financial gains, creating a market failure that leaves the grid vulnerable to interference.

Plan of Action

The next administration should establish the Grid Resilience Innovation Demonstration (GRID) Network, a national-scale test facility designed to propel the nation toward a more secure, robust, and resilient grid that can strengthen economic and national security while enabling a clean-energy future. The GRID Network should comprise multiple, geographically distributed test beds that are widely accessible to institutions and researchers seeking to demonstrate technologies in prototypical environments. These test beds would be user facilities similar to those owned by the National Science Foundation (NSF) and the Department of Energy (DOE).

The overall goal of the GRID Network would be to support development, demonstration, and deployment of innovations in grid operation and technology, which are needed to address the evolving energy needs and expanding risks. The types of innovations could run from small to large scale, and from technical to operations, for example, components for high-voltage transmission or distribution, smart meters and associated cyber controls, direct current connects and disconnects, and microgrid operations with a variety of sources, loads and sizes.

The GRID Network would focus on innovations at mid- to high technology-readiness levels, i.e., innovations that have already been demonstrated successful at a limited level and seem like promising candidates for scale-up and commercialization. GRID Network test beds would provide the capacity to test at all scales from individual components in situ up to full end-to-end tests from the electricity generator to the final use. As modernization of the grid continues to occur, the anticipated outcomes will continue to evolve, and this facility will enable more innovations to be developed rapidly and tested such that the decision and risk of implementation can be reduced, which in turn should facilitate deployment. After all, utilities and investors want proven technologies, not science projects. As a result, we will see a more resilient grid that is both more secure and more robust (i.e., less blackouts, more value, savings and/or avoided costs).

GRID Network test beds could serve as official sites for the government to validate and certify any concept or technology intended for use in national-security applications. Through partnerships with community colleges, test beds could also offer workforce-development opportunities and vocational training to prepare technicians to install and operate next-generation grid technologies.

Implicit in the proposed action is that there are innovative technologies and strategies for operation that could be tested and rapidly deployed. While this has not been demonstrated through a survey or collection of data, it is a reasonable assumption based on our knowledge of the research and development (R&D) that is being done in this area as well as some general issues that impact the rapid, successful advancement from R&D to demonstration and deployment (i.e., crossing the so-called “Valley of Death”). Having a user facility aimed at helping bridge that gap that is available to companies and researchers widely would encourage innovators and innovations to surface, as has been demonstrated to work well in the past in the DoD and DOE. A minimally viable prototype will be needed for testing, which focuses the role of the facility between “development” and “deployment.” The costs for testing would be covered by the government, and like the existing user facilities, access to apply for time on GRID would be open to all ideas through a merit-review process. As a result, innovators should be motivated to develop their ideas to a product or operations model that can be tested given the low or zero cost of testing because the value of a having a government-tested and demonstrated device or operating model will be very high.

As is typical for federally-funded user facilities, the GRID Network would be run by a private entity (e.g., an objective management organization) through a public-private partnership with government agencies: in this case, likely DoD and DOE. The partnership could be managed by either agency or by an external entity, such as the National Resilient Grid Authority (NRGA) conceptualized in a 2020 report from the National Commission on Grid Resilience. Existing microgrids and other assets at DoD and DOE sites could provide the foundation for the GRID Network. The GRID Network will also build on and enhance the grid-resilience and modernization efforts that were established and have been pursued at both agencies.

Establishing and managing the GRID Network would cost the Federal Government an estimated $25–50 million per year at the low end to $200–300 million per year at the high end. This funding range is consistent with the funding levels for similar research and development facilities that DOE and DoD have supported over the last 15 years. Funding at the high end would support more sophisticated, comprehensive testing equipment, would permit users to take more time to test ideas, and would permit testing of more high-risk, high-reward ideas. Funding at the high end would also support efforts beyond just testing, such as development of national standards and protocols for grid operations, pursuit of collaborative technologies that would benefit niche applications, such as defense resilience pilot projects, and technology certifications.

The U.S. electric grid must be modernized to enable more use of renewable energy, deploy storage, and assure we improve the resilience. A test facility, such as the GRID facility described above, could help with modernization and entice investments toward deployment of new technologies. As a result, federal investment in the GRID Network would pay off directly or indirectly in four key ways:

  1. Modernizing the U.S. electric grid will create shovel-ready construction jobs across the country. Since the GRID facility would be oriented toward rapid development and deployment of innovations, the facility could help enable aggressive and comprehensive modernization of the electric grid, which would involve construction jobs.
  2. Grid components that are critical to U.S. infrastructure and national security—ranging from sensors to transformers—must be made through a trusted U.S. supply chain. Investments in the GRID Network hence represent investments in American manufacturing.
  3. The GRID Network will support user generation of intellectual property and associated small business start-ups because some of the innovations that are tested and deployed will be manufactured, distributed and installed by start-ups, which will strengthen the U.S. supply chain. This new wave of business activity will propel the U.S. economy for years to come.
  4. Grid modernization is a huge effort that will cost at least $500 billion and likely $1–2 trillion. Investing in technologies that could facilitate modernization will retire risks for grid modernization as the decisions by the various grid operators will be based on testing at an applicable scale. As a result, the GRID facility should help ensure the costs for grid modernization are in the middle of the range rather than at the higher end or above.


The U.S. electric grid is a crucial piece of the nation’s infrastructure. If it fails, critical sectors such as finance, healthcare, transportation, defense, agriculture, and manufacturing are at risk of failure as well. Yet the grid remains unacceptably vulnerable to threats large and small. There is a real danger of attacks on the grid by adversarial nations, and natural disasters can wipe out large sections of the grid for hours, days, or longer. Even factors as seemingly trivial as mylar balloons, small arms fire, and broken tree branches can cause costly damage when they interfere with critical grid components. It is past time to create a more robust and resilient system. Creating a testing ground for innovative solutions in grid operations and technology is an important step: one that will not only shore up a glaring weakness in our national security, but will also boost our economy through shovel-ready construction projects, creation of new and good-paying jobs, and development of intellectual property.

Frequently Asked Questions
What pieces of this proposal are already in place?
The proposed GRID Network would leverage microgrids and other assets already distributed at DOE and DoD sites across the country. By linking these assets through a national-scale user facility, the GRID Network will ensure that these assets are put to their fullest use. The GRID Network would also build on and enhance the grid resilience and modernization efforts that both DOE and DoD have funded over the last 15 years.
How much does the federal government spend on the electric grid? What would additional spending achieve?
The amount the Federal Government spends on grid R&D and modernization varies but has been as high as $750 million and as low as about $50 million. The investment is supplemented by matching funds from private industry, as the grid is largely operated by private companies. There is not currently a federally-funded facility to support testing and scale-up of innovative grid operating models and technologies. Investing in such a facility would accelerate grid modernization and could perhaps cut grid-maintenance costs in the long term.
Why should the federal government take action on grid modernization instead of state or local government? What about the private sector?
Few systems are more complicated than the U.S. electric grid. The U.S. electric grid is managed by more than 3,000 public and private institutions (including generators, operators, and markets). Energy is often transmitted across state lines, which requires cooperation and coordination at multiple levels of government. As such, the private sector as well as state and local government will necessarily be involved in grid modernization. But in light of the importance of the grid to U.S. economic and national security, there are clear and specific roles for the Federal Government. For instance, the Federal Government can assure that new grid technologies and ideas have been tested and certified in order to mitigate risk of implementing those new technologies and ideas. The federal government can also help scale promising innovations quickly. A federally-funded GRID Network would be a key piece—but still only a piece—of a larger national grid-modernization effort.
Is the issue of grid modernization specific to the United States?

The technologies utilized in the U.S. electric grid is typical of electric grids in many other countries, particularly those that developed electricity distribution contemporaneously with the United States. However, the size and geographic diversity of our nation means that the U.S. electric grid is especially large and complex. To an extent, this complexity offers protection since no single attack or incident could impact the entirety of the national grid. However, our grid’s size and complexity also mean that coordinating grid modernization efforts in the United States is far more difficult than in other nations.

The GRID Network could help turn this bug into a feature. The United States has always excelled at out-innovating other countries, particularly for things at large scale. The GRID Network would allow U.S. innovators to field-test technologies and strategies in many different scenarios and conditions, and would help innovators commercialize promising solutions at a pace that other countries simply do not have the capacity to match. The GRID Network could hence address vulnerabilities in the U.S. grid while simultaneously enhancing the international competitiveness of our nation with respect to grid modernization.

What is the first step needed to get the GRID Network off the ground?
The first step is to develop a written plan that can form the basis for the funding requests and appropriations and the follow-on steps needed to establish the GRID Network. The plan would (1) identify the specific activities of the GRID Network, (2) inventory existing facilities and capabilities that could be integrated into the GRID Network, (3) identify new facilities and capabilities that would be needed to achieve GRID Network goals, (4) identify necessary approvals and propose an operating model for the facility, and (5) lay out a detailed roadmap for launching the facility, including conceptual cost, scope and schedule. Development of the plan should be carried out by a contractor and overseen by an interagency group.
What would a less ambitious version of this proposal look like?
The GRID Network could be operated at various scales: for instance, it could be piloted in a small
collection of states before being expanded nationwide. The roles and capabilities of component
test beds could be tailored based on available funding, and the path toward the full facility could
be established in the plan discussed above.

House explores the future of work at the close of the decade

Just before Congress left for the holidays, the House Education and Labor Subcommittee on Higher Education and Workforce Investment held a hearing examining ways to prepare for the future of work. This has become a hot topic this year, particularly as presidential candidate Andrew Yang has incorporated it into his platform and elevated it onto the national debate stage. The issue highlights the societal and economic changes that are underway due to the development of new technologies such as automation and artificial intelligence. These technologies will cause major shifts in the types of tasks performed and skills required in our occupations, as well as the creation of a host of new employment opportunities. However, with this growth, there are concerns that low- and medium-skilled workers could be displaced and left behind. The federal government has a long history of administering job training and reskilling programs for displaced workers but these new technologies present unique challenges.

We asked our scientific community to submit questions and important topics that should be discussed and we provided them as an online resource for Members of the Committee before the hearing. The insightful, data-driven submissions we received included questions about lifelong learning, the expansion of apprenticeships, the decline in funding for workforce development programs, the impact of automation on the workforce, and the roles of the public and private sector in helping workers adapt to the future of work. All of these topics were touched upon during the hearing. Agreement between Members of the Committee and witnesses was most apparent on how the current patchwork of federally-supported workforce development programs are not enough, and that their funding should be increased.

Chairwoman Susan Davis (D, CA-53) opened the hearing by critiquing the lack of federal investment in U.S. workers. She emphasized how the U.S. government spends only 0.1% of its budget on workforce development, while other industrialized nations spend an average of six times more. This can leave valuable workforce programs strapped for cash and harm workers looking for help in landing their next job. In fact, displaced workers are expected to navigate the confusing network of federal programs on their own, needlessly extending their search for assistance and a new job. Chairwoman Davis noted that reskilling alone will be insufficient to prevent worker displacement and that government programs should prioritize lifelong learning.

Ranking Member Lloyd Smucker (R, PA-11) added in his opening statement that the Taskforce on Apprenticeship Expansion was created to reduce the red tape and establish new apprenticeship programs. To understand the complexity of the federal training program landscape, the Government Accountability Office performed a study in 2009 and found that the federal government administers 47 different job training programs in nine different agencies. Many of the current retraining programs target specific categories of workers, such as those who have been laid off as jobs moved overseas or those who are underqualified, instead of targeting the training needs for specific types of work. However, studies like the Taskforce on Apprenticeship Expansion’s 2018 report have found that training and apprenticeship programs focused on developing the skills that local businesses need to succeed are often more effective than their current federal counterparts.

The statement that triggered one of the more compelling exchanges during the hearing came from former Acting Secretary of Labor, Seth Harris. He insisted that the US does not suffer from an inability to find workers with the right skills, often called the “skills gap.” If there was an actual gap between workers’ abilities and the skills needed to succeed in the workforce, wages would dramatically increase for workers with the right skills and employers would spend more money on training their employees to learn those skills. This has not happened. He explained that the skills gap argument blames workers for not knowing what skills would be in demand when choosing an education, instead of acknowledging a systemic disconnect between degree and certification processes and employers’ needs, the lack of apprenticeships, and reduced funding for on-the-job training.

When Representative Mark Takano (D, CA-41) asked what Congress can do to help, Mr. Harris advocated for more transparency in the credentialing system and stronger Trade Adjustment Assistance Community College Career Training (TAACCCT) programs to help people get the right skills to succeed in the workforce. There are thousands of programs that claim to help workers earn certifications in sought-after skills; however, there is little data on which programs are actually effective. More transparency into the success rates of these programs would allow workers to enroll in the best programs for their career plans. The Department of Labor’s TAACCCT program began in 2011 and awards grants to community colleges to improve their curricula “to help adults learn skills that lead to family-sustaining jobs.”

The creation of learning savings accounts for workers was also the subject of vigorous discussion. James Paretti, Treasurer for the Emma Coalition, emphasized that the biggest challenge will be for both employers and employees to understand that some displacement is inevitable and workers must be prepared. Stockpiling funds is one way that workers could automatically save for their future education and weather employment challenges. A variety of learning savings account models have been proposed, with workers, employers, and the government all having the option to contribute funds at assorted levels, similar to the contributions made to retirement accounts.

This hearing covered a lot of ground, but Members have not completed their fact-finding into the future of work. Chairwoman Davis announced that her Committee will be holding another hearing about this critical issue. As Congress prepares to dig deeper into the future of work, we encourage you to email any data-driven questions or workforce topics that should be discussed to