A lawsuit is seeking to force the Trump administration to disclose its framework for testing the safety of AI models, amid concerns that the rules may be biased or inadequate. According to Protect Democracy, the framework could potentially be "corrupt," with officials from the Office of the National Cyber Director, the Office of Science and Technology Policy, the Treasury Department, and the Commerce Department potentially favoring rapid deployments for AI firms that Trump likes.
As AI technology advances and cybersecurity risks escalate—OpenAI's model hacking Hugging Face is the most obvious recent example—the public can't afford to blindly trust Trump to act in good faith when choosing which frontier models should be rigorously tested, Protect Democracy said. And perhaps even worse, the public cannot know if new vulnerabilities discovered in the real world are due to agencies failing to complete a proper review, running outdated or ineffective tests, missing important checks, or missing steps that align with the latest mitigation strategies advanced by leading AI safety experts.
US Representative Greg Casar (D-Tx.) has accused Trump of "completely failing to keep us safe from the dangers of AI" while taking "millions from AI billionaires." Casar said that Trump's approach to AI safety is "asleep at the wheel" and that he is "too busy cashing in to protect our jobs or national security." California state Senator Josh Becker has also urged the court to grant Protect Democracy's request, noting that California is considering a bill that would establish a process for independent organizations to set baselines for AI safety standards.
The lawsuit highlights the need for greater transparency and accountability in the development and deployment of AI systems. As AI becomes increasingly integrated into our daily lives, it is essential that we have a clear understanding of how these systems are being tested and evaluated for safety. The public deserves to know what's in the framework, and it's time for the Trump administration to come clean.
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