AI Fairness 360 (AIF360) is a comprehensive open-source toolkit of metrics to check for unwanted bias in datasets and machine learning models, and state-of-the-art algorithms to mitigate such bias throughout the AI application lifecycle. Containing over 30 fairness metrics and 9 state-of-the-art bias mitigation algorithms developed by the research community, it is designed to translate algorithmic research from the lab into actual practice. Here’s IBM’s press release.
- Goodbye World
- House Judiciary Committee’s Articles of Impeachment
- Implied Constitutional Powers in the Founding Era
- Witness written statements in first Judiciary Committee impeachment hearing
- The Trump-Ukraine Impeachment Inquiry Report
- Negotiating the American Constitution (1787-1789) Coalitions, Process Rules, and Compromises
- Measuring Law Faculty Scholarly Impact by Citations: Reliable and Valid for Collective Faculty Ranking
- Is There a Case for Statistical Precedent?
- When Courts Should Ignore Statutory Text
- Beck’s The Parts We Skip: A Taxonomy of Constitutional Irrelevancy
Just in case you don't get it: The views expressed are solely those of the blog post author and should not be attributed to anyone else, meaning they do not necessarily represent the views of any organization that the post author is affiliated with or with the views of any other author who publishes on this blog.
- 239,590 hits