Bias Mitigation approach from the lens of Independent Audit of AI systems by ForHumanity

Algorithmic Bias is a widely debated subject currently. Algorithmic Bias essentially is the scenario wherein the algorithm systematically prejudices individuals/ groups in its results. This may be caused by the data, the algorithm, and the outcome impact. Bias caused by algorithm is perceived to be harmful with COMPAS (being one of the most quoted example)
A lot of research and discussions are exploring ideas towards Bias mitigation.

We, at ForHumanity, have done our research on Bias Mitigation from the lens of Independent Audit of AI systems. We recently released first of the three parts on Bias Mitigation in Data Sets. Here is the link https://forhumanity.center/s/biasInDa...

In this webinar we are discussing the thoughts, approaches and contextual merits in adopting our proposed approach in Independent Audit of AI Systems.

Panelist: Shea Brown, Ryan Carrier, Merve Hickok, and Adam Leon Smith

Moderator: Sundar Narayanan