Adversarial Machine Learning and Cybersecurity: Risks, Challenges, and Legal Implications


Adversarial Machine Learning and Cybersecurity

Risks, Challenges, and Legal Implications

Micah Musser

April 2023

Artificial intelligence systems are rapidly being deployed in all sectors of the economy, yet significant research has demonstrated that these systems can be vulnerable to a wide array of attacks. How different are these problems from more common cybersecurity vulnerabilities? What legal ambiguities do they create, and how can organizations ameliorate them? This report, produced in collaboration with the Program on Geopolitics, Technology, and Governance at the Stanford Cyber Policy Center, presents the recommendations of a July 2022 workshop of experts to help answer these questions.

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