The last decade has seen the increased use of machine learning and data science to make decisions—from figuring out which YouTube video to recommend to deciding whom to give a loan, automated decisions are now everywhere. However, as deployment of these decision-making systems has increased so too have concerns about the transparency of the component algorithms and the fairness of their outcomes. This topic was the subject of the New Approaches to Fairness in Automated Decision Making scientific session at the 2020 American Association for the Advancement of Science (AAAS) Annual meeting in Seattle, Washington one month ago. The session was moderated by Computing Community Consortium (CCC) Director Ann Schwartz Drobnis and included: Sampath […]

The Computing Community Consortium (CCC) is proud to be a part of the American Association for the Advancement of Science (AAAS) 2020 Annual Meeting taking place February 12-16, 2020 in Seattle, Washington. This year the CCC is supporting five scientific sessions at the AAAS Annual Meeting in addition to two communications and outreach opportunities. Learn more about each of the sessions below. New Approaches to Fairness in Automated Decision Making Friday, February 14th 8:00 – 9:30 AM Synopsis: Critical decisions are increasingly being made by machine-learning algorithms based on massive data trails that people all leave behind. Such decisions affect issues from college admissions and bank loans, to sentencing and police deployment. Concerns have been raised […]

The Computing Community Consortium (CCC) recently released the Algorithmic and Economic Perspectives on Fairness workshop report. It is the output of the CCC’s 1.5-day Economics and Fairness visioning workshop that took place in May 2019, in Cambridge, Massachusetts. The workshop was organized by David C. Parkes (Harvard University, CCC Council) and Rakesh Vohra (University of Pennsylvania), with the support of the CCC’s Fairness and Accountability Task Force. It brought together computer science researchers with backgrounds in algorithmic decision-making, machine learning, and data science with policy makers, legal experts, economists, and business leaders to discuss methods to ensure economic fairness in a data-driven world. The report highlights the current trends and uses of algorithmic […]