In this episode of The RegulatingAI Podcast, Sanjay Puri speaks with Naresh Dulam, SVP at J.P. Morgan Chase, about the regulatory voids in today’s AI landscape. From biased data to unexplainable black boxes, Naresh reveals what’s missing—and what must change. 🎯 Key Takeaways: The 3 critical policy gaps in AI today: explainability, bias, and accountability Why relying on a developer's goodwill is no longer sustainable The case for outcome-based, risk-tiered regulation Real-world examples from financial services and beyond 📺 Watch now to understand what’s broken—and how we fix it.  Resources Mentioned:  https://www.linkedin.com/in/naresh-dulam/   Timestamps: 00:00 Introduction 01:33 AI Regulatory Gaps 03:46 Three Main Problems with AI 06:01 AI Explainability Issues 09:10 AI Bias and Fairness 12:37 Who's Accountable for AI Mistakes 17:30 Outcome-Based Regulation 19:40 EU vs US AI Regulation 23:45 Financial Services AI Rules 28:11 Innovation vs Safety 31:35 Open Source AI Discussion 39:05 AI Impact on Jobs 42:10 Career Advice for AI Era 45:50 Lightning Round Questions 46:58 Conclusion

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