Hosted by Dylan Doyle-Burke and Jessie J Smith, Radical AI is a podcast featuring the voices of the future in the field of artificial intelligence ethics. In this episode Jess and Dylan chat to Jenn Wortman Vaughan about building responsible AI.
What are the differences between explainability, intelligibility, interpretability, and transparency in Responsible AI? What is human-centered machine learning? Should we be regulating machine learning transparency?
To answer these questions and more we welcome Dr Jenn Wortman Vaughan to the show. Jenn is a Senior Principal Researcher at Microsoft Research. She has been leading efforts at Microsoft around transparency, intelligibility, and explanation under the umbrella of Aether, their company-wide initiative focused on responsible AI. Jenn’s research focuses broadly on the interaction between people and AI, with a passion for AI that augments, rather than replaces, human abilities.. Full show notes for this episode can be found at Radical AI.
Listen to the episode below:
Hosted by Dylan Doyle-Burke, a PhD student at the University of Denver, and Jessie J Smith, a PhD student at the University of Colorado Boulder, Radical AI is a podcast featuring the voices of the future in the field of Artificial Intelligence Ethics.
Radical AI lifts up people, ideas, and stories that represent the cutting edge in AI, philosophy, and machine learning. In a world where platforms far too often feature the status quo and the usual suspects, Radical AI is a breath of fresh air whose mission is “To create an engaging, professional, educational and accessible platform centering marginalized or otherwise radical voices in industry and the academy for dialogue, collaboration, and debate to co-create the field of Artificial Intelligence Ethics.”
Through interviews with rising stars and experts in the field we boldly engage with the topics that are transforming our world like bias, discrimination, identity, accessibility, privacy, and issues of morality.
To find more information regarding the project, including podcast episode transcripts and show notes, please visit Radical AI.