In this enlightening episode, we delve deeper than the usual buzz surrounding AI’s perils, focusing instead on the tangible problems emerging from the use of machine learning algorithms across Europe. We explore “suspicion machines” — systems that assign scores to welfare program participants, estimating their likelihood of committing fraud. Join us as Justin and Gabriel share insights from their thorough investigation, which involved gaining access to one of these models and meticulously analyzing its behavior. Leave us a comment Changelog++ members save 3 minutes on this episode because they made the ads disappear. Join today! Sponsors: Changelog News – A podcast+newsletter combo that’s brief, entertaining & always on-point. Subscribe today. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. Featuring: Gabriel Geiger – TwitterJustin-Casimir Braun – TwitterDaniel Whitenack – Twitter, GitHub, Website Show Notes: Article - “Inside the suspicion machine” The methodology behind Justin and Gabriel’s report Something missing or broken? PRs welcome!