CliffsList
Is Everything Predictable?: AI, Prediction Markets, and the Philosophy of Foresight at Index Greenpoint

Is Everything Predictable?: AI, Prediction Markets, and the Philosophy of Foresight

A six-week course examines prediction technologies, AI, prediction markets, and forecasting through philosophy, cultural studies, and journalism. The final meeting offers participants the option to present original work at an event open to the public.

AI summary · From the event listing

October 29, 2026 · 6:30 PM – 9 PM

Index Greenpoint, Brooklyn · From $275 ·

Keep your plans in one place. Free account.

Website on Luma

A six-week seminar explores how AI and prediction markets shape the present, drawing on philosophy, cultural studies, and journalism.

AI · From the event listing

Organizer’s description

​In this six-week course, explore works from philosophy, cultural studies, and journalism to understand how technologies that predict the future also shape the present. The age of AI, prediction markets, and real-time data analysis brings predictive reasoning into all corners of human life. Once considered a niche academic interest area, the philosophy and politics of prediction is now relevant to everybody. “Is Everything Predictable?: AI, Prediction Markets, and the Philosophy of Foresight” presents scholarly material on forecasting technologies in a rigorous but highly accessible format. Drawing from a range of sources, we center scholarly texts and deeply-researched journalism that uncover the links between digital calculation, philosophical notions of time and free will, and the reality of living in an age where everything seems reducible to calculation. Guest speakers from academia and tech journalism will round out our seminar sessions, and for our final meeting, students have the option of presenting original research or creative work in an event open to the general public. Syllabus In the early weeks of the course, we read texts from contemporary media studies and political theory that construe prediction and speculation as forms of governance. We also address probabilistic reasoning as a key feature of artificial intelligence and prediction market mechanisms, using frameworks suitable for participants without any background in STEM.

Hosted by Emma Stamm