AI Bias & Fairness Series

A good video lecture on an AI topic may be watched by hundreds of thousands of people. But a nice lecture on AI fairness may receive only 10% of such attentions. It is not because it is not important. On the contrary, we keep repeating the same mistakes again and again. As AI is making more critical decisions and larger impacts, the attitude of doing it first and worrying about it later is so outdated. Here is a 5-article series in discussing the topic.

Bias in Clinical Research, Data Science, Machine Learning & Deep Learning

AI Bias

Address AI Bias with Fairness Criteria & Tools

Caveats & Limitations on AI Fairness Approaches

AI Fairness (Approaches & Mathematical Definitions)

AI Governance