Ethics in Data Science: Auditing OpenAI's GPT for hiring bias
As firms race to adopt generative AI to get an edge over competitors, reporters are designing experiments to measure the harms these technologies pose to consumers.
In this talk, Leon Yin will share the background, methodology, and findings for a recent data-driven investigation into hiring bias in OpenAI's GPT. By reproducing a classic discrimination audit, Yin and his co-authors (Davey Alba and Leonardo Nicoletti) reveal GPT's racial and gender biases against names when asked to rank equally qualified candidates for the same role.
Leon Yin is an award-winning investigative journalist at Bloomberg News. He builds datasets and develops methods to measure technology's impact on society. He writes Inspect Element, a practitioner's guide to auditing algorithms. In 2023, the series "Still Loading" received a Philip Meyer Award, recognizing the best uses of social science methods in journalism. Leon got his start in news at The Markup.
ÀÏÍõÂÛ̳ welcomes the full participation of all individuals in all aspects of campus life. Should you wish to request a disability-related accommodation for this event, please contact the event sponsor/coordinator. Requests should be made as early as possible.