The hidden influences behind the algorithms that run our lives with Luca Belli

In this episode, I speak with Luca Belli about his forthcoming Manning book, “Hidden Influences,” which explains how algorithmic recommendation systems work from socio-technical and ethical perspectives rather than teaching readers to build them. Belli describes how recommenders and users shape each other, why debates about societal harms (including misinformation) often lack nuance, and why “working properly” is hard to define because value is personal and difficult to measure, leading platforms to optimise for engagement as a proxy with harmful side effects like clickbait. Drawing on his background in math, data science, and his work at Twitter, where he co-founded a machine learning ethics, transparency, and accountability team, he outlines the book’s framework-based, timeless structure and its coverage of moderation, measurement, societal impacts, and individual and policy responses.

https://www.manning.com/books/hidden-influences

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