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.
• Principle 2: Commercialization via established businesses creates different economic impacts than commercialization via startups; each pathway requires fundamentally different support.
• Principle 3: Local context matters; what works in Boston won’t necessarily work in Birmingham. 
• Principle 4: Successful commercialization pipelines include interventions at the individual, institutional, and ecosystem level.

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.  

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!

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 https://www.alicoalition.org/.

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.

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.

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. 

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

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 sciencepolicy@fas.org.