Vicarious Risk and the AI Revolution
Dr. Grant Fuller discusses vicarious risk and AI adoption in the finance industry.
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Podcast Description
QuantSpeak podcast host, Dan Tudball is joined by Dr. Grant Fuller, CEO and Founder of Irithmics. Dr. Fuller discusses the latest advancements in vicarious risk and if the finance industry is fully sold on AI.
Topics & Timestamps
[00:00 - 02:16] Opening, Introductions, Panel Preview, AI as Analogy, Guest Bio
[02:16 - 04:46] Vicarious Risk Explained, Evolution Since Pandemic, Academic Collaboration
[04:46 - 07:43] Definition of Vicarious Risk, Real-World Analogies, Behavioral Implications
[07:43 - 12:07] Machine Patterns vs. Human Patterns, Data Aggregation, Decision-Making Shifts
[12:07 - 14:12] Technology Progress, Expansion, How AI Measures Vicarious Risk
[14:12 - 19:11] Anticipating Anticipations, Activism, ESG, AI’s Role in Shaping Perception
[19:11 - 23:25] Influence of AI on Human Interaction, Language Models, Reinforcement Learning, Social Impact
[23:25 - 28:00] Early Career at RiskMetrics, Hypotheticals with Modern AI, Data Transparency, Open Source
[28:00 - 32:55] Human Skills vs. AI, Loss of Drudge Work, Value of Apprenticeship, Data Quality
[32:55 - 38:13] Prompt Engineering, Importance of Fundamentals, Trust, Human-AI Collaboration
[38:13 - 47:26] Feedback Loops, Isomorphic Risk, Behavioral Herding, Reflexivity, Technical Analysis
[47:26 - 52:04] AI, Agency, Manipulation Concerns, Free Will, Optimized Influence
[52:04 - 57:05] Performative Models, Black-Scholes, Echo Chambers, Feedback in Markets, Isomorphism
[57:05 - 68:35] AI in Coding, Career Advice for Quants, Adapting to Change, Staying Curious & Closing Remarks.
Disclaimer
Podcasts are for informational purposes only and provided “as is” without any representation or warranty from Fitch Learning of any kind. Comments or statements expressed by speakers may not be those of the Fitch Learning. Fitch Learning is not providing advice or recommendations. Fitch Learning, its directors, officers, or employees do not accept any liability for any loss arising from the use of information.