Malachi demystifies the sophisticated recommendation engines that seem to know what we want before we do. He explains the difference between collaborative filtering and content-based filtering, illustrated through case studies of YouTube, Netflix, TikTok, and Amazon's recommendation systems. The episode examines how these algorithms shape not just what content we consume, but what content gets created. Malachi addresses the concerning implications of filter bubbles and echo chambers while exploring the tension between algorithmic efficiency and human values. Through personal experiments and stories, he offers insights on maintaining agency in an increasingly algorithm-driven world.Click here to browse handpicked Amazon finds inspired by this podcast series! https://amzn.to/4l8knJihttps://www.quietperiodplease.com/This content was created in partnership and with the help of Artificial Intelligence AI

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