📣📣New release! “Parables of AI in/from the Majority World” is an anthology that brings together original stories about the everyday experiences of living with AI-based systems. https://datasociety.net/library/parables-of-ai-in-from-the-majority-world-an-anthology/ 1/6
🐦🔗: https://twitter.com/datasociety/status/1600539324445081614
hey, it's my official pub date! and the other bad website is doing its thing, letting me know that I'm #1 in "music appreciation," which is definitely what the book is about
FB algorithms classify race, gender, and age of people in ad images and make delivery decisions based on the predictions. Images of Black folks are shown more to B users; images of children are delivered more to women; images of young women reach older men.
🐦🔗: https://twitter.com/sapiezynski/status/1584884796718972928
Today, technical experts hold the tools to conduct system-scale algorithm audits, so they largely decide what algorithmic harms are surfaced. Our #cscw2022 paper asks: how could *everyday users* explore where a system disagrees with their perspectives? http://hci.st/end-user-audit 🧵
🐦🔗: https://twitter.com/michelle123lam/status/1584585389313904650
