Lightning Talk: Leveraging PyTorch 2.0 for Bias Reduction in AI - Christina Zhu, Visier As a software developer, it's staggering to think about the incredible capabilities of AI, but it's vital not to overlook the ethical dimensions that surround its application. One of these ethical dimensions revolves around bias—an issue that, if left unchecked, can inadvertently reinforce societal prejudices and deepen existing inequalities, especially when it comes to inclusivity. I'm excited to explore this topic at this year's PyTorch conference, focusing on the usage of PyTorch 2.0 to reduce bias in AI models. It should be a quick lightning talk with some easy tips on how to do it while training your AI models. The talk aims to underscore the silent challenge of bias in AI. It's an issue I feel warrants more attention, and I hope to contribute to that discussion. My hope is that attendees will walk away with a heightened understanding of bias in AI and the challenges it presents. More critically, I hope to arm them with the knowledge of how tools like PyTorch 2.0 can make a real difference in this fight.