Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy Angelina Wang, Sayash Kapoor, Solon Barocas, Arvind Narayanan. https://predictive-optimization.cs.princeton.edu Executive summary sotto: il punto 3 è radicale ma coerente con l’evidenza empirica raccolta dagli autori (e, se non sbaglio, simile con quanto espresso in questa lista da Daniela Tafani riguardo l’uso di AI per prevedere esiti sociali). 1. Predictive optimization is a distinct type of automated decision making that has proliferated widely. It is sold as accurate, fair, and efficient. 2. We identify a recurring set of flaws that apply broadly to predictive optimization, are hard to fix technologically, and negate its claimed benefits. 3. Any application of predictive optimization should be considered illegitimate by default unless the developer justifies how it avoids these flaws. Qui il paper completo, che è un work in progress : https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4238015 A