Simons' book explores the political implications of algorithmic prediction and argues for regulation to ensure machine learning strengthens democracy. The article suggests that while algorithms can entrench biases and homogenize culture, they are not inscrutable or inevitable. As human creations, they can be made differently, offering hope for a more equitable and diverse future.
Key takeaways:
- The article discusses how recommendation algorithms, like those used by Netflix, not only suggest content based on user preferences but also influence what content gets produced, often leading to a homogenization of culture.
- Author Kyle Chayka's book, "Filterworld: How Algorithms Flattened Culture", is highlighted for its exploration of how algorithmic recommendations have fundamentally altered various cultural products and created a self-reinforcing blandness in content.
- The book "How Data Happened: A History from the Age of Reason to the Age of Algorithms" by Chris Wiggins and Matthew L. Jones is discussed for its exploration of the history of data and algorithms, and the idea that there is nothing inevitable about the way technology progresses.
- Josh Simons' book, "Algorithms for the People: Democracy in the Age of AI", is mentioned for its focus on how algorithmic power is exercised in a democracy and the need for regulation to ensure that machine learning strengthens the foundations of democracy.