Lina Khan, who chaired the Federal Trade Commission under the Biden administration, is now advocating for a much tougher approach to holding AI company leaders legally accountable. According to The Register, she pointed to a precedent rooted in the 1934 Securities Exchange Act, the foundational law that established personal criminal liability for executives who knowingly deceived the public or investors.
Khan's argument rests on the premise that overstated claims or misleading statements made by some AI lab leaders, whether about their systems' actual capabilities or the risks they pose, could fall under a legal framework similar to the one historically used against financial fraud. She suggests that administrative fines alone, often treated as an acceptable cost of doing business by large tech firms, are no longer sufficient to deter problematic conduct.
The stance is consistent with Khan's tenure at the FTC, which was marked by an unusually assertive posture toward major technology companies on competition and consumer protection issues. Since leaving the agency, she has continued to publicly push for stronger oversight of the AI sector, arguing that industry self-regulation remains inadequate given the risks posed by increasingly powerful systems being deployed at scale.
While the proposal does not yet amount to a concrete legislative initiative, it reignites an already heated debate in the United States over the limits of current AI oversight, pitting advocates of stricter government intervention against defenders of a lighter regulatory touch for innovation. Invoking a law nearly a century old also highlights the broader challenge regulators face in adapting existing legal tools to novel technologies, in the absence of a dedicated federal framework for artificial intelligence.