Big Data, Small Data, And AI Oversight With David Sandberg The AI Fundamentalists podcast

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The AI Fundamentalists »
Big data, small data, and AI oversight with David Sandberg

1d ago 49:48

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In this episode, we look at the actuarial principles that make models safer: parallel modeling, small data with provenance, and real-time human supervision. To help us, long-time insurtech and startup advisor David Sandberg, FSA, MAAA, CERA, joins us to share more about his actuarial expertise in data management and AI.
We also challenge the hype around AI by reframing it as a prediction machine and putting human judgment at the beginning, middle, and end. By the end, you might think about “human-in-the-loop” in a whole new way.
• Actuarial valuation debates and why parallel models win
• AI’s real value: enhance and accelerate the growth of human capital
• Transparency, accountability, and enforceable standards
• Prediction versus decision and learning from actual-to-expected
• Small data as interpretable, traceable fuel for insight
• Drift, regime shifts, and limits of regression and LLMs
• Mapping decisions, setting risk appetite, and enterprise risk management (ERM) for AI
• Where humans belong: the beginning, middle, and end of the system
• Agentic AI complexity versus validated end-to-end systems
• Training judgment with tools that force critique and citation
Cultural references:

Foundation, AppleTV
The Feeling of Power, Isaac Asimov
Player Piano, Kurt Vonnegut

For more information, see Actuarial and data science: Bridging the gap.
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Chapters

1. Setting the stage: AI and insurance (00:00:00)

2. Introducing David Sandberg (00:00:24)

3. What AI is for: Speed and judgment (00:04:03)

4. Responsible use, trust, and standards (00:05:28)

5. Actuarial ethics versus data science norms (00:07:10)

6. Human capital and "The Terminator" irony (00:09:58)

7. Big bets on AGI vs real innovation (00:12:01)

8. Decisions, not just processes (00:14:46)

9. AI as prediction: Learn or drift (00:16:42)

10. Big data’s limits and small data wins (00:19:25)

11. Drift, process changes, and guardrails (00:24:06)

12. Humans end-to-end, AI middle-to-middle (00:28:15)

13. Enterprise risk management (ERM) for AI: Centralizing risk (00:34:41)

14. Where humans belong in the loop (00:37:36)

15. Building and validating models that last (00:40:15)

16. Deterministic vs AI models: New governance (00:43:10)

42 episodes

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