Sponsors (2)
The bill directs coordinated, near‑term public‑private investment in AI interpretability and adversarial robustness to improve safety and national security, but does so in ways that create legal uncertainty, taxpayer costs, potential advantages for incumbents, proprietary results, and concentrated DHS authority that may divert resources and limit broader oversight.
Researchers, developers, federal employees, and government contractors get clear statutory definitions for AI, adversarial robustness, interpretability, and red‑teaming, reducing legal ambiguity when implementing the Act.
Researchers, developers, federal agencies, and the public gain incentives and prize funding to develop adversarial robustness techniques, which can reduce the risk of malicious manipulation in high‑impact systems.
AI researchers, developers, nonprofits, and regulators receive support for interpretability research and standards through competitions and partnerships, accelerating development of more explainable, reliable, and safer AI systems.
Developers, contractors, and federal agencies face legal uncertainty because broad or contested definitions and a cross‑reference to 15 U.S.C. § 9401 could import ambiguous scope and compliance obligations.
Taxpayers and smaller firms may bear costs without guaranteed public benefit: prize competitions and reliance on contractors can impose taxpayer expense while favoring well‑funded incumbents in procurement and competitions.
Smaller research teams, nonprofits, and basic researchers may be disadvantaged because short timelines (e.g., 270 days) and emphasis on commercially relevant, near‑term deliverables favor incumbents and shallow evaluation over deeper research.
Based on analysis of 6 sections of legislative text.
Directs DHS to run prize competitions to advance AI interpretability and adversarial robustness and authorizes $10M for FY2026–2030.
Official title: Require the Secretary of Homeland Security to carry out prize competitions to advance the science of interpretability and to develop adversarial robustness with respect to artificial intelligence products, and for other purposes.
Introduced December 3, 2025 by Margaret Wood Hassan · Last progress December 3, 2025
Creates a DHS-run program of prize competitions to advance research on AI interpretability and adversarial robustness for commercially used and high‑risk AI systems. It directs the Secretary of Homeland Security to run at least one interpretability competition and at least one adversarial‑robustness competition within 270 days of enactment, requires consultation with federal and private experts, permits multi‑phase competitions and outside contractors/partners, requires a post‑competition report to two congressional committees, and authorizes $10 million for FY2026–2030 to carry out the work.