SSTI’s recent TBED Community of Practice webinar took up a practical question raised by the White House Office of Science and Technology Policy report, Science: A New Golden Age: if federal science policy shifts, what changes will universities, commercialization, and regional innovation organizations need to make?
The presentation outlined a research system that could look considerably different from the one that has developed since Vannevar Bush’s Science, the Endless Frontier. The new report’s ideas include providing more support directly to individual researchers, experimenting with alternatives to traditional peer review, expanding the role of independent research organizations, placing greater emphasis on commercialization and domestic manufacturing, and using artificial intelligence to accelerate scientific discovery.
But much of the webinar discussion centered not on whether the research system could be improved, but on what these ideas would mean in practice. The webinar participants focused on several practical issues: how researchers funded independently of universities would gain access to laboratories and equipment, whether efforts to reduce administrative burdens could inadvertently eliminate important research safeguards, how greater emphasis on commercialization might affect basic research, and whether moving discoveries into the marketplace would actually result in more manufacturing and jobs remaining in the United States.
The report’s emphasis on putting researchers ahead of institutions was a topic of much interest. The report argues that lengthy grant processes, administrative requirements, and an incremental funding culture can make it harder for researchers, particularly younger scientists, to pursue promising ideas. Among its recommendations are expanded fellowships, longer-term and more flexible funding, and greater independence for early-career researchers.
The appeal of that approach was clear, but the group quickly moved to a practical question: what does it actually mean to fund a scientist rather than an institution? Researchers still need somewhere to work. Universities and research organizations generally provide laboratories, sophisticated equipment, graduate students, research staff, information technology, compliance systems, and other infrastructure. That raised the possibility that universities might effectively become providers of facilities and services to independently funded researchers, potentially changing the relationship between scientists and their institutions. In other words, changing who gets the check could also change who provides the lab, hires the staff, manages compliance, and supports the research.
There was considerable sympathy during the webinar for the report’s call to reduce the administrative burden on researchers. Much of that burden comes from preparing proposals, complying with federal requirements, and managing awards. But several participants questioned whether everything researchers experience as bureaucracy should be treated the same way. Requirements governing human subjects, animal research, financial accountability, and invention reporting exist for reasons beyond administrative compliance. Simplifying the system requires distinguishing requirements that no longer provide sufficient value from safeguards that remain necessary. One participant suggested a relatively straightforward way of reducing the burden associated with grant applications: make greater use of short preliminary pitches before asking researchers to prepare full proposals. Some federal programs already use versions of this approach. Agencies could screen promising concepts first and invite full proposals from a smaller group, saving researchers and reviewers considerable time.
The report also proposes alternatives to conventional peer review, including “Golden Ticket” reviewers who could advance promising proposals that might otherwise be rejected and portfolio approaches that would allow agencies to spread risk across groups of investments. Those ideas raised another question: would changing the decision-making process actually encourage more risk-taking, or simply introduce a different set of preferences, risks and biases? Some emerging approaches resemble venture capital investment committees more than traditional scientific peer review, ut those committees can also be more conservative when deciding where to invest.
The report’s emphasis on translating discoveries into use was especially relevant to the TBED CoP audience. There was general agreement that researchers benefit from understanding who might use their work, what problems industry is trying to solve, and where a discovery might eventually fit in the market. The discussion became more complicated, however, when it turned to basic research and the distinction between discovery, innovation, and translation. Fundamental university research often advances knowledge incrementally over many years. The eventual commercial opportunity may not be apparent when the original work is conducted. Companies and entrepreneurs can later combine discoveries from multiple sources in ways that result in significant new technologies. That makes market signals useful, but potentially problematic if applied too broadly. Some participants in the webinar commented that greater attention to potential applications could strengthen translation, but shifting resources away from basic research in favor of projects with readily identifiable commercial outcomes could weaken the innovation pipeline. For researchers seeking federal support, however, the ability to explain potential impact and relevance may become increasingly important, even when commercialization is not the immediate objective.
One of the discussion’s most relevant points for the TBED community concerned what happens after a technology successfully leaves the laboratory. One participant offered a concrete example: Small technology companies may build prototypes in the United States, only to move production overseas when they cannot find affordable or accessible domestic manufacturing options. That experience highlights a limitation of focusing exclusively on university technology transfer. More disclosures, patents, licenses, and startups do not necessarily translate into domestic manufacturing and jobs if companies cannot find competitive ways to produce their products in the United States.
The challenge of keeping manufacturing and jobs onshore also points toward a potentially larger role for economic development and innovation organizations. Small companies may sometimes look overseas not because appropriate U.S. manufacturing capabilities do not exist, but because entrepreneurs do not know how to find them. Regional TBED organizations could help by identifying manufacturers, suppliers, facilities, and technical capabilities and connecting them with emerging technology companies. Better matchmaking could help companies scale domestically while strengthening regional supply chains and industry clusters. Commercialization depends on more than a university and a company. It can require entrepreneurs, capital, manufacturers, suppliers, customers, workforce organizations, community colleges, and public-sector partners.
The discussion of artificial intelligence was notably cautious. The report sees significant potential for AI to accelerate discovery, automate experimentation, analyze increasingly complex scientific data, and change how research is conducted and communicated. AI could also help bring together information that has traditionally been difficult to connect. At the same time, AI should not be treated as a solution to every problem in the research system. Its ultimate effects on university research, industrial R&D, and regional innovation ecosystems remain difficult to predict. One potentially useful application for the TBED community emerged from the earlier discussion about domestic manufacturing. Matching researchers and startups with manufacturers, suppliers, technical expertise, facilities, and other regional resources can be difficult because organizations often describe similar capabilities in very different ways. AI-enabled discovery and matchmaking tools could make those connections easier, potentially helping regions retain more of the economic activity associated with locally developed technologies.
The Aug. 18 discussion suggested considerable agreement with several of the report's objectives, including reducing unnecessary administrative burdens, experimenting with research funding approaches, improving connections between researchers and markets, strengthening commercialization, and making better use of AI. The harder questions concern implementation. Many of the report's ideas remain proposals, and the real test will be whether they strengthen the current research system or redraw the relationships among researchers, universities, government, and industry in ways that create new problems.
Perhaps the most important question raised by the webinar is whether the next era of U.S. science policy will treat the path from discovery to economic impact as part of science policy itself. If it does, TBED organizations may be especially well positioned to make that system work in practice: connecting discovery to companies, production capacity, workers, capital, and regional markets.