High Signal: Data Science | Career | AI12 Mai

Episode 39: The 100-Year Lead: What Baseball Teaches Us About the Future of AI

Chris Fonnesbeck, veteran analyst for the Yankees and Mets and creator of the open-source Bayesian modeling library PyMC, joins to unpack why baseball has been a leading indicator for data science and analytics for over a century, and why builders and AI leaders need to pay attention now. The reason it has led is simple: huge incentives and a culture that treats decisions as quantifiable. With wins worth about eight to ten million dollars apiece and front offices built around probabilistic reasoning, baseball has had every reason to push the methods further and faster than industry.

The skillset and culture that built this lead is what AI teams now need to adopt more of: probabilistic thinking, hierarchical models, integrating expert judgment, reasoning carefully under uncertainty, and increasingly causal inference. The conversation traces the throughline from those early statistical innovations to the decisions driving multi-million dollar contracts today, with concrete patterns AI builders can take back to their own work: how to handle small samples and high stakes, why outcomes are the wrong thing to measure, what changes when you push uncertainty all the way through your model, and why robust causal inference needs to be the next frontier.

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Episoder(41)

Episode 41: The Verification Crisis: Why Trust Is the New Bottleneck in AI

Noah Smith, economist and author of Noahpinion, joins High Signal to look at what AI is already changing… and what it isn’t. The conversation moves beyond the usual productivity hype to ask harder que...

18 Jun 53min

Episode 40: The Economic Reality of AI: Friction, Talent, and the Future of the Firm

Steve Tadelis, Professor of Economics at UC Berkeley and former senior economist at eBay and Amazon, joins High Signal to bridge the gap between economic theory and the high-stakes reality of data sci...

26 Mai 58min

Episode 38: Why AI Won’t Fix Your Data Culture, It Will Only Amplify It (And What To Do About It)

Noah Bruegmann, President of Data CRT, joins High Signal to discuss how to move your data function from a cost center to a strategic "value center". He explains how AI amplifies your existing data cul...

16 Apr 45min

Episode 37: Engineered Intelligence and The Data Science Problem in AI

Jordan Morrow, SVP of Data & AI Transformation at AgileOne and the "Godfather of Data Literacy," joins High Signal to discuss the shift from being "data-driven" to becoming "AI-enabled." Jordan warns ...

2 Apr 46min

Episode 36: AI and the Judgment Problem in Data Science

Dawn Woodard (Distinguished Engineer, LinkedIn), Andrés Bucchi (LATAM Airlines), and Jeremy Hermann (CEO & Co-Founder, Delphina) join High Signal for a deep dive into the shifting architecture of data...

19 Mar 1h 3min

Episode 35: Beyond Online Experimentation: Generative Software That Optimizes Itself

Martin Tingley, Head of Windows Experimentation at Microsoft and former Head of the Experimentation Platform Analysis Team at Netflix, talks about why humans are the bottleneck in experimentation, and...

5 Mar 55min

Episode 34: Duolingo and the Future of Personalized Education with AI

Bozena Pajak, VP of Learning at Duolingo, joins High Signal to discuss the evolution of AI at Duolingo: from personalized difficulty models to the current generative frontier where AI characters provi...

10 Feb 45min