Experimentation, Causal Inference, and AI: Sean Taylor of OpenAI and VC Jesse Robbins at Data Council 2025
Heavybit by Jesse Robbins and Sean Taylor · · Article
"AI provides an opportunity to radically improve how we do things."
I interviewed Sean Taylor of OpenAI ahead of Data Council 2025 on experimentation, causal inference, and why AI generates more questions that need empirical answers.
Sean Taylor and I previewed the Data Science and Algorithms track for Data Council 2025. The conversation focuses on experimentation, causal inference, and the practical frameworks data teams use to drive product decisions.
We also covered Hadley Wickham, Timothy Chan, Joe Powers, and Bryan Bischof as featured speakers.
I sat down with Sean Taylor of OpenAI at Heavybit to preview the Data Science and Algorithms track for Data Council 2025. Our conversation focused on experimentation, causal inference, and the practical frameworks data teams use to drive product and business decisions.
We covered the featured speakers: Hadley Wickham on generative AI in data science workflows, Timothy Chan of Statsig on experimentation at scale, Joe Powers of Intuit on Bayesian A/B testing, and Bryan Bischof of Hex on ML engineering. I framed the conference as a rare opportunity for isolated data science practitioners to validate their work by “peeking over each other’s shoulders.”
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