The elusiveness of ethics: encoding fairness in an unfair world

A presentation at Melbourne Women in Machine Learning & Data Science in in Melbourne VIC, Australia by Laura Summers

While the problems of data bias and algorithmic bias have hit the mainstream, the mathematical approaches to tackle this problem are mostly restricted to a rarified academic discourse. In this talk you’ll get a birds-eye view of the state of ML Fairness, from checklists and frameworks to developer tools and mathematical definitions of bias and fairness. We’ll wrestle with the elephant in the room: How do we encode fairness into our models when we can’t precisely define our ethics as a society, a team, or sometimes even as individuals?


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