The Special Competitive Studies Project (SCSP), a nonprofit, nonpartisan initiative focused on strengthening America's long-term competitiveness in emerging technologies, has filed formal comments urging the Office of Management and Budget (OMB) to revise proposed rule changes that could weaken the research enterprise underpinning American technology leadership. The proposed rules, described as the most sweeping revision in years to federal grants and research award regulations, aim to increase accountability and transparency but risk damaging the innovation engine, according to SCSP President Ylli Bajraktari.
In a recent article, Bajraktari acknowledged that political accountability and scientific expertise are not enemies, but he warned that applied without clear limits, the rule could harm the innovation engine that has been the backbone of America's scientific success. The proposed regulations include several concerning provisions: senior political appointees would review every discretionary award, reviewers would be directed to weigh presidential policy priorities, peer review would be explicitly downgraded to 'advisory,' and agencies could terminate active research awards simply because priorities changed after the work began.
The stakes are measurable, according to SCSP's 2026 Tech Competition Scorecard, which found that China holds a decisive overall lead in robotics for advanced manufacturing, and that the narrow U.S. lead in quantum is eroding under Beijing's coordinated, state-backed strategy. Meanwhile, the federally funded share of national research and development dropped by nearly one-third between 2010 and 2019, and federal AI research spending remains far below the $32 billion annual level recommended by the National Security Commission on Artificial Intelligence. America already faces a funding gap, Bajraktari said, and should not compound it with a confidence gap.
The proposed changes take their cues from a termination-for-convenience model of government contracting, but research grants are different, Bajraktari emphasized. A research grant supports multiyear experiments, doctoral researchers, and laboratory partners using custom equipment and generating data over time. Stopping that work midstream destroys value that reimbursement cannot recover. The losses also reach companies, investors, national labs, and startups that make decisions based on whether federally funded research is stable and merit-driven.
"When award decisions look political rather than technical, or when a grant can vanish because priorities shifted, private partners hedge, talent looks elsewhere, and the whole geometry of innovation weakens," said Bajraktari. SCSP's comments ask OMB to consider four points before finalizing any changes: keep merit at the center, make awards durable, account for the private sector, and assess the competitive impact. Specifically, scientific and technical merit should remain the primary basis for selecting research proposals, with senior appointees playing a legitimate oversight role but not substituting their judgment for expert evaluation. Competitively awarded research grants should not be terminable simply because policy priorities changed after the fact, but only for legal violations, security concerns, or performance failures, with recipients given a chance to respond. Agencies should also consider whether changes will deter co-investment, interrupt commercialization pathways, or push globally mobile talent toward competitors. Finally, major changes to federal research policy should include a technology-competitiveness impact assessment, as OMB's own analysis only counts paperwork costs and misses the national security costs of forgone discoveries and deterred capital.
SCSP also urged OMB to slow down. An October 1 effective date would impose new selection and termination frameworks on fiscal year 2027 awards before agencies have built the procedures to implement them well, Bajraktari said. Visit cset.georgetown.edu to learn more about related research. To read SCSP's full comments, visit scsp.ai.
