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AI is advancing rapidly at the cognitive tasks that make up knowledge work, raising fears among firms, policymakers, and, not least, workers of a “China shock” for white-collar jobs. Neil Thompson will present new research on whether those fears are warranted.

AI is advancing rapidly at the cognitive tasks that make up knowledge work, raising fears among firms, policymakers, and, not least, workers of a “China shock” for white-collar jobs. Neil Thompson will present new research on whether those fears are warranted.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Join us for a premier one-day event that brings together leading experts in experimentation and causal inference, spanning researchers and industry professionals. This is your chance to explore the latest trends, breakthrough methodologies, and real-world applications shaping the field. Engage in thought-provoking discussions, gain fresh insights, and connect with a dynamic community driving data science and decision-making innovation!
This event is in-person only.
Note: If your ticket type is sold out, please click here to sign up for the waitlist. If tickets become available, an email will be sent to those on the waitlist. They will be available on a first-come, first-served basis.
General Admission: $200
Non-Stanford Faculty/Staff: $75
Non-Stanford Student/Postdoc: $35
Stanford Faculty/Staff/Student/Postdoc: free
| Time | Session Title | Speaker(s) |
|---|---|---|
| 9:30 - 10:00am | Registration & Coffee | |
| 10:00 - 10:15am | Opening Remarks | Guido Imbens, Stanford Data Science Faculty Director, and Applied Econometrics Professor |
| 10:15 - 11:45am | Session 1: | Session Chair: Stefan Wager |
| 10:15 - 10:45am | Reevaluating Causal Estimation Methods with Data from a Product Release | Eleanor Dillon, Principal Researcher, Microsoft |
| 10:45 - 11:15am | Unraveling Disease: How Do We Learn Causality in Drug Discovery? | Emily Fox, SVP of AI and Machine Learning, insitro, Professor, Stanford University |
| 11:15 - 11:45am | Doing the Right Thing Faster: Causal Measurement at Airbnb | Navin Sivanandam, Head of Core Data Science, Airbnb |
| 11:45am - 12:45pm | Lunch | |
| 12:45 - 1:30pm | Poster Session & Networking Coffee | Downloadable Poster Map |
| 1:30 - 3:00pm | Session 2: | Session Chair: Emma Brunskill |
| 1:30 - 2:00pm | Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference | Anastasios Angelopoulos, Postdoctoral Scholar, UC Berkeley |
| 2:00 - 2:30pm | Disentangling Goals from Beliefs | Benjamin Van Roy, Professor, EE and MS&E, Stanford University |
| 2:30 - 3:00pm | Evaluating AI: From Overfitting to Agents | Ludwig Schmidt, Assistant Professor, Computer Science and Data Science, Stanford University, and Technical Staff Member, Anthropic |
| 3:00 - 3:15pm | Break | |
| 3:15 - 4:45pm | Session 3: | Session Chair: Yiqing Xu |
| 3:15 - 3:45pm | A Causal Perspective on Evaluating LLMs | Sean Taylor, Data Scientist, OpenAI |
| 3:45 - 4:15pm | Evaluating Interventions in Panel Data Settings | Susan Athey, Economics of Technology Professor, Stanford University |
| 4:15 - 4:45pm | Five Lessons Learned from A/B Testing at Scale | James McQueen, Principal Applied Scientist, Amazon |
| 4:45 - 6:00pm | Reception |