The rapid rise of AI has set off a flurry of legal and regulatory activity. There is no single AI law to follow. Instead, there are overlapping circles of regulation, where privacy, cybersecurity, consumer protection, employment, and IP laws all continue to apply alongside newer AI-specific rules. Europe has its EU AI Act, but the U.S. has no federal equivalent yet. In its place is an emerging patchwork of more than 150 state AI laws, and the picture shifts every few months as new legislation and guidelines arrive. For engineers and tech companies, it can feel impossible to know what applies and where the real risks lie.
Shannon Yavorsky is a data lawyer who co-leads the Cyber, Privacy and Data Innovation group and the AI practice at the international law firm Orrick. She advises companies across sectors from health technology to financial services on how to develop and deploy AI responsibly amid this evolving regulatory environment.
In this episode, Shannon joins Kevin Ball to make sense of that landscape. They discuss how to map the concentric circles of regulation that actually apply to you, the risk spectrum separating a low-stakes manufacturing tool from a high-stakes system making loan or healthcare decisions, the problem of shadow AI and why recorded meetings can become a litigation liability, how to build an AI governance program, and more.
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