This course aims to teach learners about fairness, accountability, and transparency in automated decision systems. The course covers topics such as automated hiring systems, data equity, diverse balanced ranking, and model development lifecycle. The teaching method involves discussing the challenges and solutions in implementing fair and transparent algorithms. This course is intended for technical students interested in understanding the ethical implications of AI technologies.
KDD TransFAT - Translating Fairness, Accountability, and Transparency - Julia Stoyanovich
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
Intro
The promise of Al
Automated hiring systems
Do these tools work?
Automated Decision Systems (ADS)
Blas in computer systems
Data equity to the rescue!
Diverse balanced ranking
Model development lifecycle
Interpretability to buid trust
Education: technical students
Taught by
Association for Computing Machinery (ACM)
