Data Skeptic

Anas Buhayh breaks down the S'mores framework—a radical approach to algorithmic pluralism where YOU choose which recommender serves your content.Horror fan? Soul-funk enthusiast? There's an algorithm for that.Listen now 🎧 open.spotify.com/episode/3BCenL…

Cory Zechmann, shares 16 years of wisdom on the art of "algatorial" curation—where human expertise meets machine learning.Why does TikTok work so well? What's the CODE framework? How do we balance discovery with familiarity? 🎧 open.spotify.com/episode/3pCBUK…

💼 AI-powered job matching sounds great... but can you trust the recommendations?Roan Schellingerhout discusses explainable recommender systems for recruitment—and why "healthy friction" might actually help users make better decisions.Listen 🎧 open.spotify.com/episode/5aXhhs…

Václav Blahut from seznam.cz explains "inverse recommendation"—finding the right users for niche content instead of the usual approach.A clever repurposing of two-tower models that gives long-tail content a fighting chance.Dive in 🎧 open.spotify.com/episode/6zB80r…

@ek8terina (@MIT) talks strategic learning in rec sys 🎯
The paradox: algorithmic "protest movements" can actually HELP platforms by providing clearer signals
We explore game theory, coordinated user behavior, and the platform vs. user arms race open.spotify.com/episode/358hGx…