AI Learns From Wikipedia — So What Happens When Wikipedia Is Biased?

Donate: 🙏 https://www.buymeacoffee.com/slobodnipoI In this highlight, Eugene Garvin warns that artificial intelligence is only as reliable as the sources it absorbs — and he says one of the biggest hidden influences is Wikipedia. He argues that search engines and AI systems often pull their first-layer summaries from Wikipedia, meaning any built-in editorial bias can spread far beyond the encyclopedia itself. Garvin points to criticism from Larry Sanger, Wikipedia’s co-founder, and uses an example involving Google Gemini to illustrate how certain political terms can be pre-labeled as unacceptable before real debate even begins. His broader point is that this is not just about one website. It’s about how bias becomes automated, then reappears as “neutral” machine output — shaping what millions of people think is true before they ever examine an original source. Full epizode: https://www.youtube.com/playlist?list=PLJTy3oXCzHShsVuJ-zfiGnx96nuR-BNWB WEB: https://slobodnipodcast.hr/?p=1483