Eran Kahana Keynote Speaker

AI, Cybersecurity and Intellectual Property Attorney
Fellow at Stanford Law School & Advisory Board Member at Stanford Law School Artificial Intelligence Law Society
Adjunct Professor of Law at the University of Minnesota Law School

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Eran Kahana's Biography

Eran Kahana is an AI, cybersecurity, and intellectual property lawyer. He is currently a fellow at Stanford Law School where he researches and lectures on issues on the intersection of AI and the law. He is also a member of the Advisory Board of Stanford Law School’s Stanford Artificial Intelligence & Law Society, an Adjunct Professor of Law at the University of Minnesota Law School, a member of the a member of the Scientific Council of the Israeli Association for Ethics in Artificial Intelligence, and co-author of The Law of Artificial Intelligence and Smart Machines, a publication of the American Bar Association.

Kahana is a frequent presenter at Stanford Law School’s annual Digital Economy Conference, most recently at Stanford Law School’s Center for Responsible Quantum Technology, and frequent instructor for regional and national continuing legal education providers including Bloomberg Law, Lawline, TRT, Rossdale, and Minnesota CLE. At the University of Minnesota, he teaches Artificial Intelligence and the Law. He has also been interviewed on AI, cybersecurity, privacy, and technology law by Bloomberg Law, BBC, Canadian Broadcasting Corporation (CBC) radio, KABC radio, Minnesota Public Radio, Twin Cities Business magazine, Star Tribune, Minnesota Lawyer, TheStreet.com, Quartz magazine, and Stanford University Radio, KZSU FM.

AI: Separating Fact from Fiction, Myth from Reality

As game changing AI is touted to be, it remains poorly defined, is vulnerable to dramatic, fearful, unrealistic, misguided expectations, and challenging for regulators. This talk aims to remedy that. It clarifies what AI really is, surveys its economic impact, common uses, looks at legal tensions, and the emerging regulatory landscape.

Generative AI and Ethics

The revolutionary potential of generative AI is felt across multiple industries, driving transformative change. But there is a hidden cost. This talk delves into the implications of adopting generative AI, including the emerging ethical concerns and essential best practices for successful integration.

Privacy Risks in Generative AI Deployments

The deployment of generative AI models poses significant privacy risks, including the potential for sensitive data exposure and biased decision-making. As generative AI systems process and generate vast amounts of data, they inevitably create new attack surfaces for malicious actors to exploit, compromising individual privacy and trust. Furthermore, the lack of transparency and explainability in generative AI models can lead to unforeseen privacy consequences, making it essential to implement robust privacy controls and risk mitigation strategies. This talk examines the risks and proposes practical mitigation strategies.

Quantum Governance, National Security, and Geopolitics

Quantum computing promises to break free from the chains of classical computing, leading to groundbreaking capabilities in drug discovery, cryptography and expanding the capabilities of AI. But there are significant challenges that can stand in the way. This talk explores these challenges, specifically as they lay in the critical intersection of quantum governance, national security, and geopolitics.