I’ve been reading about the artificial intelligence/machine learning (AI/ML) wars revolving around the use of so-called “black-box” algorithms–too complex for humans, even their inventors, to understand. Such algorithms are increasingly used to make decisions that affect you, but if you can’t understand, or aren’t told, why a machine predicted your graduate-school readiness, or which drug a doctor should prescribe for you, etc, you’d likely be dissatisfied and want some kind of explanation. Being told the machine is highly accurate (in some predictive sense) wouldn’t suffice. A new AI field has grown up around the goal of developing (secondary) “white box” models to “explain” the workings of the (primary) black box model. Some call this explainable AI, or XAI. The black box is still used to reach predictions or decisions, but the explainable model is supposed to help explain why the output was reached. (The EU and DARPA in the U.S. have instituted broad requirements and programs for XAI.) Continue reading
Monthly Archives: March 2022
PSA2022: Call for Contributed Papers
Twenty-Eighth Biennial Meeting of the Philosophy of Science Association
November 10 – November 13, 2022
Submissions open on March 9, 2022 for contributed papers to be presented at the PSA2022 meeting in Pittsburgh, Pennsylvania, on November 10-13, 2022. The deadline for submitting a paper is 11:59 PM Pacific Standard Time on April 6, 2022.
Contributed papers may be on any topic in the philosophy of science. The PSA2022 Program Committee is committed to assembling a program with high-quality papers on a variety of topics and diverse presenters that reflects the full range of current work in the philosophy of science. Continue reading