Jim Dempsey and Jonathan Spring on Adversarial Machine Learning and Cybersecurity

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Risks associated with the rapid development and deployment of artificial intelligence are getting the attention of lawmakers. But one issue that may not be getting adequate attention by policymakers or by the AI research and cybersecurity communities is the vulnerability of many AI-based systems to adversarial attack. A new Stanford and Georgetown report, “ Adversarial Machine Learning and Cybersecurity: Risks, Challenges, and Legal Implications ,” offers a stark a reminder that security risks for AI-based systems are real and recommends actions that developers and policymakers can take to address the issues. Lawfare Senior Editor Stephanie Pell sat down with two of the report’s authors,…