How AI Recommendation Algorithms Learn Bias from User Behaviour

AI Ethics with Fexingo: Bias, Safety, and Responsible Artificial Intelligence · Jul 28, 2026 · 7m

In this episode of AI Ethics with Fexingo, Lucas and Luna explore how recommendation algorithms inherit bias from user behavior patterns. They anchor the discussion on a 2025 study from the Algorithmic Justice League, which found that YouTube's recommendation engine served 30% more political and conspiracy content to male user profiles than female ones. They dig into the feedback loops that amplify gender, race, and class biases, and discuss what platforms like YouTube are doing—and failing to do—to address it. A concrete look at how your clicks shape algorithmic fairness. #AIEthics #Bias…