After a federal watchdog found a staff of two overseers insufficient to vet 27,000 research awards for ties to adversaries, namely China, the Pentagon says computers will now screen military-funded academics, including artificial intelligence experts.

The move has stakeholders urging not to lean too hard on algorithms to distinguish, for instance, a scientist-spy sharing secret nano-energy plans with China from a Chinese professor publishing AI safety studies. Hanging in the balance lies troops’ technological edge, veteran intelligence officials and academics say.

AI’s confusion over the timing and nature of research partnerships may obscure real espionage if humans are not the ultimate judge of foreign influence, they warn, with some academics fearing an AI-work slop redux of the “China Initiative,” where the first Trump administration charged dozens of ethnic Chinese scientists with espionage, only to drop nearly all charges.

“Automated vetting tools are extremely useful for vetting large datasets and identifying patterns of concern. But those tools are for decision support to help the people, the human analysts, assess context and intent,” said David Cattler, who, until September, led the Defense Counterintelligence and Security Agency, which screens personnel seeking security clearances.

The renewed focus on academic research security comes as tensions between the U.S. and China over AI intensify, with China ramping up both the development of low-cost AI models and its alleged exploitation of U.S. models.

The U.S. intelligence community’s annual threat assessment reports that China “aims to displace the U.S. as the global AI leader by 2030,” in part, “by using its sizeable talent pool, extensive datasets, government funding and burgeoning global partnerships.”

Partnership is a complicated term in military “fundamental research” — studies that are publishable, rather than proprietary or classified, with potential defense applications.

For instance, mere co-authorship with a China-based scientist does not suffice to deny a U.S. researcher money, according to evolving academic research rules targeting foreign influence. Rather, to make the call, the Pentagon must assess each academic’s disclosures of external funding sources and affiliations.

According to a recently-declassified May 2025 inspector general report, such disclosures went unchecked because the Pentagon had not “requested additional government full-time equivalent employees to thoroughly review… and to conduct oversight of over 27,000 academic research awards.”

Defense News first obtained the report and the Pentagon’s response to a draft version through an open records request.

When asked about additional staffing, a Pentagon official pointed to orders in a January research security directive for the Chief Digital and AI Office (CDAO) to identify “automated vetting and continuous monitoring capabilities” and create a common research grant database.

The mandate also calls for a year-long “damage assessment” of selected research transactions, including cases that the House Select Committee on China flagged, in part, using AI tools.

A September GOP-led Committee report alleged that the Pentagon subsidized 1,400 academic papers published between June 2023 and June 2025 involving partnerships with the Chinese government.

The Pentagon said in an emailed statement on Thursday that the department “is committed to protecting the integrity of U.S. research while fostering international collaboration. Our approach leverages advanced analytical tools to augment human expertise, ensuring a rigorous and fair review process.”

Machines Make the Same Mistakes

Several university representatives, who requested anonymity due to the sensitivity of policy discussions, note that AI-assisted risk assessments have, in the past, drawn false assumptions about U.S.-China research collaborations.

For instance, the AI-aided GOP House report mislabeled the state-backed Wuhan National Laboratory for Optoelectronics as the sponsor of a collection of nine essays, whereas the Wuhan lab supported only one essay that involved no U.S. authors or federal funding.

The report also mistook a Chinese military-affiliated author’s publication on single-electron transistors for a DOD-funded project, when it merely referenced work funded by the U.S. military.

House Select Committee officials declined to comment on the cases.

Averting foreign interference “is not as easy as just having better AI capacities, because we know that some of those AI mistakes were the same human mistakes that led to inaccurate charges brought against researchers under the China Initiative,” Toby Smith, senior vice president for government relations and public policy at the Association of American Universities, said after learning of the AI gaffes.

About 30% of the China Initiative’s 77 cases involved academics not disclosing Chinese partnerships or funding sources, though disclosure was often not required, or no such partners or funding existed.

A jury found only one professor, Harvard nanochemist Charles Lieber, guilty, after he lied to Pentagon investigators about his participation in a Chinese talent recruitment program.

Smith said that relying on proxies — such as co-authorship, affiliation or nationality — to deduce security concerns led investigators to confuse co-authorship with direct interaction or shared data access, and to misinterpret historical ties as active partnerships.

“AI systems trained on bibliometric data,” or citation analytics, “and affiliation records can inherit the same flawed assumptions that underpinned the China Initiative,” he said. “The core lesson from the China Initiative is that identifying genuine research security risk requires judgment, context and proportionality — qualities that automated systems should support, not replace.”

Gisela Perez Kusakawa, executive director of the Asian-American Scholar Forum, said that the Pentagon has not communicated the types of data that the new AI tools will collect, use and share, nor sought community feedback, heightening concerns about ethnic profiling.

In an emailed statement, the Pentagon responded, “It is the standard practice of the department to not provide specifics regarding the criteria and weighting for threat assessments conducted, whether by manual or automated process.”

Kusakawa said, “We should be making sure that our research environment is welcoming, that we are encouraging these talents, especially in AI, to come to the United States and, frankly, have family in the United States, and make this a country that they contribute to and invest their and their children’s future in.”

Increasingly, that AI talent is not coming. Statistics suggest that Chinese AI experts are staying in China, even as America has managed to keep earlier expats.

Of about 100 Chinese-origin AI scholars who were researching at U.S. institutions in 2019 — when their papers were accepted at the world’s most elite AI conference, NeurIPS — 87% remained stateside as of 2025, according to Carnegie Endowment for International Peace figures.

At the same time, the share of Chinese home-grown talent not moving abroad has skyrocketed since 2019, based on an Economist tally of similar data. In 2019, about 30% of NeurIPS authors educated in China were still in China. By 2022, that population had jumped to 58%, and up to 68% in 2025.

‘Key’ Financial Disclosures Were Missing

To ensure that no country has a stranglehold on general knowledge, “the goal cannot be to close the U.S. research system altogether,” said Cattler, the former Defense Counterintelligence and Security Agency director and now founder of consultancy Ironhelm Works. “The goal must be to ensure that collaboration strengthens national security rather than inadvertently weakening it.”

Last year’s inspector general report concluded that Pentagon agencies that partner with academic institutions “could be at an increased risk of exposure to foreign influence” because military units were “missing key documents” that can help discern scientists’ foreign financial sources, outside employers and other details related to potential conflicts.

For instance, about 80% of Air Force funding transactions sampled in the report were missing documents that can reveal problematic relationships. Also, the Air Force and the Defense Advanced Research Projects Agency — which bankrolled the Internet’s inventors — told evaluators that they had not, as required, annually checked that researchers named in progress reports were not involved in banned talent recruitment programs.

In response to questions about the screening lapses, the Pentagon said in an emailed statement that the department “is aware of the OIG’s findings in the report and the impacted directorates are working with [the Office of the Undersecretary for Defense and Engineering] to address the items identified.”

Jeffrey Stoff, a Chinese linguist and intelligence community analyst for 18 years who resigned in 2021 due to frustration with research security, maintains that DOD still needs more human expertise in language, culture and the minutiae of research restrictions.

“AI can and should be used for unsophisticated, labor-intensive tasks,” such as cross-referencing foreign organizations in financial disclosure forms against the names of blacklisted parties, but humans still need to inspect AI’s work, as not all nefarious ties are machine-readable, said Stoff, who now advocates for tighter safeguards as head of the nonprofit Center for Research Security and Integrity.

Cattler, giving more credit to AI, said that the scale of research collaboration demands that the Pentagon upgrade its approach to clocking potential spies.

With such a large population of research institutions and affiliated scientists, as well as a bombardment of often duplicative alerts, automation “improves the signal within that noise and can help orient the humans on really important matters,” he said.

“Sometimes people are deliberately deceptive when they are processed, and that could happen in a human exchange just as much as it could happen in something that a computer can see, but together, a human review and a computer review are incredibly powerful.”

Aliya Sternstein is an investigative journalist who covers technology, cognition and national security. She is also a research analyst at Georgetown Law. Her writing on the intersection of public health and constitutional rights has appeared in the Stanford Law Review, Arizona Law Review, and other law and health academic journals.