Biden Administration Should Avoid Pursuing Precautionary Rules for AI in Newly Announced Regulatory Review, Says Center for Data Innovation

WASHINGTON— In response to the request for comment from the U.S. Commerce Department’s National Telecommunications and Information Administration (NTIA) on accountability measures for AI systems, Hodan Omaar, senior policy analyst at the Center for Data Innovation, issued the following statement:

The growing chorus raising the alarm about AI systems threatens to lure the Biden administration into embracing rules that steer away from the United States’ historically innovation-friendly approach to the digital economy. Deviating from this path poses a serious risk to U.S. innovation and competitiveness.

Many of the proposals to regulate AI are based on the false premise that AI is fundamentally dangerous and consumers need the government to protect them. The best way to achieve better outcomes for consumers is not to bog down companies using algorithms with new regulations—even the most extensive internal reviews will not be able to predict all potential pitfalls—but rather to hold companies strictly accountable for monitoring their use of algorithms and mitigating potential harms. The administration can achieve this outcome by rigorously enforcing existing laws and regulations and conducting a gap analysis to identify any shortcomings.

If the administration allows the misguided notion that AI is inherently problematic to cloud the discussion on AI regulation, then the United States will become like Europe: aspiring to be an AI leader but in reality being an AI follower.

For more on this issue, see:

• Daniel Castro, “Ten Principles for Regulation That Does Not Harm AI Innovation” (Center for Data Innovation, 2023)
• Daniel Castro, “Critics of Generative AI Are Worrying About the Wrong IP Issues” (Center for Data Innovation, 2023)
• Hodan Omaar, “Where Should U.S. AI Policy Be Headed Next?” (Center for Data Innovation, 2023)
• Hodan Omaar, “U.S. AI Policy Report Card” (Center for Data Innovation, 2022)