9. Fair synthetic data and ethical algorithms: the fairness conversation with Paul Tiwald, Head of Data Science at MOSTLY AI

Paul Tiwald has been part of the MOSTLY AI team since the beginning. He is the mastermind behind the team's research into fairness and the idea of fair synthetic data. In this episode, you will hear about: what it's like to work in the field of artificial intelligence (spoiler: it's really fun!)how the idea of fair synthetic data came uphow to create machine learning models that are private and fair by designwhy is it so challenging to remove bias from an algorithmwhat are proxy variables, and why are they dangerouswhat is the definition of fairness, and why do we need one in the first placehow should companies start implementing fairness and ethical approaches into their AI developmentwhy it's impossible to fix bias without fair synthetic data and algorithmic fairness