1 hr 13 min
Designing for Intelligibility: Building Responsible AI with Jenn Wortman Vaughan The Radical AI Podcast
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- Technology
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 Radicalai.org.
If you enjoy this episode please make sure to subscribe, submit a rating and review, and connect with us on twitter at twitter.com/radicalaipod
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 Radicalai.org.
If you enjoy this episode please make sure to subscribe, submit a rating and review, and connect with us on twitter at twitter.com/radicalaipod
1 hr 13 min