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
Regulating AI: Innovate Responsibly