You don’t choose what you watch next — the algorithm does.
We’re told recommendation systems simply predict our preferences. But modern algorithms don’t just observe behavior. They **shape it**. Every scroll, pause, like, and skip feeds a feedback loop designed to guide attention, amplify certain reactions, and quietly narrow the range of choices you’re exposed to.
In this video, we break down how algorithms actually work — from engagement optimization and A/B testing to feedback loops that influence opinions, habits, and even identity over time. This isn’t a conspiracy theory. It’s an incentive problem. Platforms are rewarded for predictability, and the easiest way to predict humans is to slowly shape them.
Why do feeds become more extreme the longer you stay?
Why does content feel repetitive but still addictive?
And when does “personalization” stop being choice?
This is a deep dive into how algorithms move from predicting users to *engineering behavior* — and why the most powerful systems don’t control people directly. They just guide the first step.
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