Curiosity Lab: The Certainty Trap: What AI Reveals About How We Misuse Probabilistic Systems
March 8, 2026
- 3:00 pm - 4:00 pm ET
Virtual
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Alum Michael Bagalman ’87 will lead this Curiosity Lab examining large language models not as sentient systems or unreliable tools, but as probabilistic technologies that reflect a deeper challenge: how organizations demand certainty from inherently uncertain processes. Drawing on decision science, Michael’s talk will use examples from forecasting, experimentation, and statistical inference to explore how fluent model outputs can hide uncertainty, reward confident answers over calibrated ones, and blur accountability. Rather than focusing on how to make AI more trustworthy, the session will consider why building better decision-making under uncertainty matters far beyond AI itself.
**Headshot created using AI
