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Government,
Administrative/Regulatory

Jan. 16, 2020

The right way to regulate artificial intelligence: The decision-based approach

The regulatory focus must not be on hypothetical conundrums such as hyper-technical and uber-esoteric debates over the “proper” definition of AI which invariably rests on meaningless academic and technical distinctions.

Bradford K. Newman

Partner
Baker & McKenzie LLP

Email: Bradford.Newman@bakermckenzie.com

Bradford Newman is the founder and co-chair of the AI and Blockchain Subcommittee of the ABA and leader of Baker McKenzie's AI practice. Recognized by the Daily Journal in 2019 as one of the Top 20 AI attorneys in California, Bradford has been instrumental in proposing federal AI workplace and IP legislation that in 2018 was turned into a United States House of Representatives Discussion Draft bill. In 2023, he was invited to testify before the United States Senate as an expert on AI and the Future of Work. He is frequently called upon to teach judges and lawyers AI CLE courses on a national level, has been an invited AI lecturer at the nation's top law and business schools, and has developed AI oversight and corporate governance best practices designed to ensure algorithmic fairness.

For several years, I have extolled the ever-more urgent need for the federal government to regulate Artificial Intelligence. My initial call for regulation and its rationale, made by way of a 2015 Tech Crunch article, was viewed in many quarters as premature. I persisted. In 2018, I published the architectural framework for proposed AI legislation that I call The Artificial Intelligence Data Protection Act. The response this time was different. A United States Represe...

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