Hidden Influences

You don’t choose what you see on the internet. Algorithms choose for you. We spend 12 billion hours a day browsing the internet. And in the background, sophisticated recommender systems silently decide what appears on our feeds, what we click next, and what we think we want. These invisible algorithms direct our entertainment, news, shopping, friendships, dates—even our sense of identity.

Algorithmic recommender systems are some of the internet’s most closely guarded secrets. This book pulls back the curtain, showing why they’re so seductive and how they influence your beliefs, desires, and behavior. This book tells you how they work and gives you tools to reclaim your agency.

Dr Luca Belli, co-founder and former research lead for Twitter's Machine Learning Ethics, Transparency and Accountability team, has been on the front lines of how recommender systems work and impact society. In this book, he lays out who uses this powerful technology to shape our world, and exactly how they do it.

About the book

In a world drowning in content, recommendation engines are the gatekeepers. They actively influence culture, democracy, privacy, and how we see each other. If you care about what you read, see and believe—and why—you need to understand recommendation systems.

What's inside

 • Where algorithms hide in streaming platforms, social apps, dating services, online stores, and news feeds
 • How algorithms algorithms use small tweaks in your behavior to reveal intimate truths
 • Why recommendation systems amplify extremism
 • How AI makes algorithmic recommenders even stealthier
 • Reclaiming your time and attention

About the reader

This book is written for all audiences. No advanced technical knowledge is required.

About the author

Luca Belli is an AI researcher specializing in recommender systems and responsible machine learning. He is the AI Safety Lead at Spring Health and founded Sator Labs, a Responsible AI consultancy. Previously, he led research on recommender systems at Twitter’s META team, focusing on algorithmic amplification, and he was an AI Visiting Fellow at NIST. He has provided advice to the European Commission’s decision making on regulating recommender systems. He holds a PhD in Mathematics from Tor Vergata University in Rome.