{"id":31133,"date":"2026-04-20T17:56:27","date_gmt":"2026-04-20T17:56:27","guid":{"rendered":"https:\/\/one.sightlinemg.com\/c4isrnet\/uncategorized\/2026\/04\/20\/after-watchdog-slams-understaffing-ai-to-vet-pentagon-backed-professors-china-ties\/"},"modified":"2026-08-08T16:51:47","modified_gmt":"2026-08-08T16:51:47","slug":"after-watchdog-slams-understaffing-ai-to-vet-pentagon-backed-professors-china-ties","status":"publish","type":"post","link":"https:\/\/one.sightlinemg.com\/c4isrnet\/artificial-intelligence\/2026\/04\/20\/after-watchdog-slams-understaffing-ai-to-vet-pentagon-backed-professors-china-ties\/","title":{"rendered":"After watchdog slams understaffing, AI to vet Pentagon-backed professors\u2019 China ties"},"content":{"rendered":"\n

After a federal watchdog<\/a> 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. <\/p>\n\n\n\n

The move has stakeholders urging not to lean too hard on algorithms to distinguish, for instance, a scientist-spy<\/u><\/a> sharing secret nano-energy plans<\/u><\/a> with China from a Chinese professor publishing AI safety<\/u><\/a> studies<\/u><\/a>. Hanging in the balance lies troops\u2019 technological edge, veteran intelligence officials and academics say. <\/p>\n\n\n\n

AI\u2019s confusion over the timing and nature of research partnerships<\/u><\/a> may obscure real espionage if humans are not the ultimate judge of foreign influence, they warn, with some academics fearing an AI-work<\/u><\/a> slop<\/u><\/a> redux of the \u201cChina Initiative,\u201d<\/u><\/a> where the first Trump administration charged dozens of ethnic Chinese scientists with fraud, only to drop nearly all charges.<\/u><\/a> <\/p>\n\n\n\n

\u201cAutomated 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,\u201d said David Cattler, who, until September, led the Defense Counterintelligence and Security Agency, which screens personnel seeking security clearances. <\/p>\n\n\n\n

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<\/u><\/a> and its alleged exploitation of U.S. models.<\/u><\/a> <\/p>\n\n\n\n

The U.S. intelligence community\u2019s annual threat assessment reports that China \u201caims to displace the U.S. as the global AI leader by 2030,\u201d<\/u><\/a> in part, \u201cby using its sizeable talent pool, extensive datasets, government funding and burgeoning global partnerships.\u201d <\/p>\n\n\n\n

Partnership is a complicated term in military \u201cfundamental research\u201d<\/u><\/a> \u2014 studies that are publishable, rather than proprietary or classified, with potential defense applications. <\/p>\n\n\n\n

For instance, mere co-authorship with a China-based scientist does not suffice to deny a U.S. researcher money, according to evolving<\/u><\/a> academic research rules<\/u><\/a> targeting foreign influence. Rather, to make the call, the Pentagon must assess each academic\u2019s disclosures of external funding sources and affiliations<\/u><\/a>. <\/p>\n\n\n\n

According to a recently-declassified May 2025 inspector general report<\/u><\/a>, such disclosures went unchecked because the Pentagon had not \u201crequested additional government full-time equivalent employees to thoroughly review\u2026 and to conduct oversight of over 27,000 academic research awards.\u201d <\/p>\n\n\n\n

Defense News first obtained the report and the Pentagon\u2019s response to a draft version through an open records request. <\/p>\n\n\n\n

When asked about additional staffing, a Pentagon official pointed to orders in a January research security directive<\/u><\/a> for the Chief Digital and AI Office (CDAO) to identify \u201cautomated vetting and continuous monitoring capabilities\u201d and create a common research grant database. <\/p>\n\n\n\n

The mandate also calls for a year-long \u201cdamage assessment\u201d of selected research transactions, including cases that the House Select Committee on China flagged, in part, using AI tools.<\/u><\/a> <\/p>\n\n\n\n

\"\"
Then-DCSA Director David M. Cattler speaks at the Inaugrual NIPS Signatory Conference in McLean, Virginia, Aug. 1, 2024 (Christopher P. Gillis\/DOD).<\/figcaption><\/figure>\n\n\n\n

A September GOP-led Committee report<\/u><\/a> alleged that the Pentagon subsidized 1,400 academic papers<\/u><\/a> published between June 2023 and June 2025 involving partnerships with the Chinese government. <\/p>\n\n\n\n

The Pentagon said in an emailed statement on Thursday that the department \u201cis 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.\u201d <\/p>\n\n\n\n

Machines Make the Same Mistakes<\/b> <\/h3>\n\n\n\n

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. <\/p>\n\n\n\n

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<\/u><\/a>. <\/p>\n\n\n\n

The report also mistook a Chinese military-affiliated author\u2019s publication on single-electron transistors for a DOD-funded project, when it merely referenced work funded by the U.S. military<\/u><\/a>. <\/p>\n\n\n\n

House Select Committee officials declined to comment on the cases. <\/p>\n\n\n\n

Averting foreign interference \u201cis 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<\/u><\/a>,\u201d Toby Smith, senior vice president for government relations and public policy at the Association of American Universities, said after learning of the AI gaffes. <\/p>\n\n\n\n

About 30% of the China Initiative\u2019s 77 cases<\/u><\/a> involved academics not disclosing Chinese partnerships or funding sources, though disclosure was often not required, or no such partners or funding existed. <\/p>\n\n\n\n

A jury found only one professor, Harvard nanochemist Charles Lieber, guilty<\/u><\/a>, after he lied to Pentagon investigators about his participation in a Chinese talent recruitment program and made other false statements. <\/p>\n\n\n\n

Smith said that relying on proxies \u2014 such as co-authorship, affiliation or nationality \u2014 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. <\/p>\n\n\n\n

\u201cAI systems trained on bibliometric data,\u201d or citation analytics, \u201cand affiliation records can inherit the same flawed assumptions that underpinned the China Initiative,\u201d he said. \u201cThe core lesson from the China Initiative is that identifying genuine research security risk requires judgment, context and proportionality \u2014 qualities that automated systems should support, not replace.\u201d <\/p>\n\n\n\n

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. <\/p>\n\n\n\n

In an emailed statement, the Pentagon responded, \u201cIt 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.\u201d <\/p>\n\n\n\n

Kusakawa said, \u201cWe 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\u2019s future in.\u201d <\/p>\n\n\n\n

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. <\/p>\n\n\n\n

\"Supercomputer
A worker monitors the Shenwei (Sunway) TaihuLight supercomputer at the National Supercomputer Center in Wuxi in eastern China’s Jiangsu province, Aug. 29, 2020. (Chinatopix via AP)<\/figcaption><\/figure>\n\n\n\n

Of about 100 Chinese-origin AI scholars who were researching at U.S. institutions in 2019 \u2014 when their papers were accepted at the world\u2019s most elite AI conference, NeurIPS \u2014 87% remained stateside as of 2025<\/u><\/a>, according to Carnegie Endowment for International Peace figures. <\/p>\n\n\n\n

At the same time, the share of Chinese home-grown talent not moving abroad has skyrocketed since 2019<\/u><\/a>, 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. <\/p>\n\n\n\n

\u2018Key\u2019 Financial Disclosures Were Missing<\/b> <\/h3>\n\n\n\n

To ensure that no country has a stranglehold on general knowledge, \u201cthe goal cannot be to close the U.S. research system altogether,\u201d said Cattler, the former Defense Counterintelligence and Security Agency director and now founder of consultancy Ironhelm Works. \u201cThe goal must be to ensure that collaboration strengthens national security rather than inadvertently weakening it.\u201d <\/p>\n\n\n\n

Last year\u2019s inspector general report<\/u><\/a> concluded that Pentagon agencies that partner with academic institutions \u201ccould be at an increased risk of exposure to foreign influence\u201d because military units were \u201cmissing key documents\u201d that can help discern scientists\u2019 foreign financial sources, outside employers and other details related to potential conflicts. <\/p>\n\n\n\n

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 \u2014 which bankrolled the Internet\u2019s inventors \u2014 told evaluators that they had not, as required, annually checked that researchers named in progress reports were not involved in banned talent recruitment programs. <\/p>\n\n\n\n

In response to questions about the screening lapses, the Pentagon said in an emailed statement that the department \u201cis aware of the OIG\u2019s 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.\u201d <\/p>\n\n\n\n

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

\u201cAI can and should be used for unsophisticated, labor-intensive tasks,\u201d such as cross-referencing foreign organizations in financial disclosure forms against the names of blacklisted parties, but humans still need to inspect AI\u2019s 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. <\/p>\n\n\n\n

Cattler, giving more credit to AI, said that the scale of research collaboration demands that the Pentagon upgrade its approach to clocking potential spies. <\/p>\n\n\n\n

With such a large population of research institutions and affiliated scientists, as well as a bombardment of often duplicative alerts, automation \u201cimproves the signal within that noise and can help orient the humans on really important matters,\u201d he said. <\/p>\n\n\n\n

\u201cSometimes 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.\u201d <\/p>\n","protected":false},"excerpt":{"rendered":"

AI\u2019s confusion over the nature of DOD research partnerships may mask real espionage if humans are not the final judge of foreign influence, experts 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