Gwen Hassan, Patrick Henz and Anthony Rhem on the Compliance and Ethics Risks of AI [Podcast]

By Adam Turteltaub Oh, Artificial Intelligence. So much promise, and so much risk. What’s a compliance and ethics professional to do? Start by listening to this podcast about the chapter “Managing the Ethics and Compliance Risks of Artificial Intelligence” in the 2025 edition of The Complete Compliance & Ethics Manual. We spoke with the article’s co-authors, Gwen Hassan (chief compliance officer at Unisys), Dr. Anthony J. Rhem (CEO and principal consultant at A.J. Rhem & Associates), and Patrick Henz (special advisor for compliance, Latin America, for Mitsubishi Heavy Industries Americas). They explain that when we speak of AI we aren’t talking about one technology but a wide range of them. Generative Ai may be getting the most attention but there is also natural language processing, neural networks, expert systems, machine learning and many more. As a result, compliance teams need to understand what form of AI is being used at their organization. When it comes to legal and regulatory frameworks to serve as guidance, it is probably best to look to Europe, which has taken a much more active approach than the US. The United States has just a patchwork of state laws. On the federal level, an executive order from the previous administration has been rescinded by the current one, leaving no national guidance. Despite the legal vacuum, there ae still risks such as bias to manage. As a result organizations need to have clear guidance on what AI can and cannot be used for. There should also be a risk assessment framework that includes: Assessing the data risk Understanding the model Assessing cybersecurity and compliance risk Evaluating ethical risk Continuous monitoring and updating Listen in to learn more about how to manage the possibilities and risks of AI. Then be sure to check out the 2025 edition of The Complete Compliance & Ethics Manual. Listen now Sponsored by Bluesight, providing industry-leading privacy monitoring with fast, reliable patient data violation detection.

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