What U.S. Members Think About Regulating AI

With the rapid proliferation of AI systems, public policymakers and industry leaders are calling for clearer guidance on governing the technology. The majority of U.S. IEEE members express that the current regulatory approach to managing artificial intelligence (AI) systems is inadequate. They also say that prioritizing AI governance should be a matter of public policy, equal to issues such as health care, education, immigration, and the environment. That’s according to the results of a survey conducted by IEEE for the IEEE-USA AI Policy Committee.

We serve as chairs ofthe AI Policy Committee, and know that IEEE’s members are a crucial, invaluable resource for informed insights into the technology. To guide our public policy advocacy work in Washington, D.C., and to better understand opinions about the governance of AI systems in the U.S., IEEE surveyed a random sampling of 9,000 active IEEE-USA members plus 888 active members working on AI and neural networks.

The survey intentionally did not define the term AI. Instead, it asked respondents to use their own interpretation of the technology when answering. The results demonstrated that, even among IEEE’s membership, there is no clear consensus on a definition of AI. Significant variances exist in how members think of AI systems, and this lack of convergence has public policy repercussions.

Overall, members were asked their opinion on how to govern the use of algorithms in consequential decision-making and on data privacy, and whether the U.S. government should increase its workforce capacity and expertise in AI.

The state of AI governance

For years, IEEE-USA has been advocating for strong governance to control AI’s impact on society. It is apparent that U.S. public policy makers struggle with regulation of the data that drives AI systems. Existing federal laws protect certain types of health and financial data, but Congress has yet to pass legislation that would implement a national data privacy standard, despite numerous attempts to do so. Data protections for Americans are piecemeal, and compliance with the complex federal and state data privacy laws can be costly for industry.

Numerous U.S. policymakers have espoused that governance of AI cannot happen without a national data privacy law that provides standards and technical guardrails around data collection and use, particularly in the commercially available information market. The data is a critical resource for third-party large-language models, which use it to train AI tools and generate content. As the U.S. government has acknowledged, the commercially available information market allows any buyer to obtain hordes of data about individuals and groups, including details otherwise protected under the law. The issue raises significant privacy and civil liberties concerns.

Regulating data privacy, it turns out, is an area where IEEE members have strong and clear consensus views.