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Share The true value of AI lies more in thorough testing and evaluation than in clever coding or prompting. — Dr. Shea Brown on AI auditing through the scientific method
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The true value of AI lies more in thorough testing and evaluation than in clever coding or prompting. — Dr. Shea Brown on AI auditing through the scientific method
In this deep dive, host Iman Mossavat sits down with Dr. Shea Brown—physicist, former astrophysics professor, and founder of BABL AI—for a sharp look at AI accountability. Brown shares his journey from studying the cosmos to interrogating AI systems, spotlighting how scientific skepticism must carry over into today’s tech landscape. At BABL AI, he leads efforts to audit and govern AI to ensure it serves human interests—especially in high-stakes areas like hiring, credit scoring, and public services. With real-world examples and hands-on audit methods, Brown explains how AI systems often fail silently and how risk-based auditing can surface hidden harms. Mossavat brings the conversation to the classroom, underscoring the need to train students not just to build AI, but to test it critically. The episode challenges tech optimism with grounded insight—and highlights a future where regulation, education, and responsible innovation must work hand in hand.
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By Podcasts 4 BrainportIn this deep dive, host Iman Mossavat sits down with Dr. Shea Brown—physicist, former astrophysics professor, and founder of BABL AI—for a sharp look at AI accountability. Brown shares his journey from studying the cosmos to interrogating AI systems, spotlighting how scientific skepticism must carry over into today’s tech landscape. At BABL AI, he leads efforts to audit and govern AI to ensure it serves human interests—especially in high-stakes areas like hiring, credit scoring, and public services. With real-world examples and hands-on audit methods, Brown explains how AI systems often fail silently and how risk-based auditing can surface hidden harms. Mossavat brings the conversation to the classroom, underscoring the need to train students not just to build AI, but to test it critically. The episode challenges tech optimism with grounded insight—and highlights a future where regulation, education, and responsible innovation must work hand in hand.
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