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