ΑΙhub.org
 

Radical AI podcast: featuring Jenn Wortman Vaughan


by
06 October 2020



share this:


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.

Designing for Intelligibility: building responsible AI with Jenn Wortman Vaughan

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:

About Radical AI:

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.




The Radical AI Podcast

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

It’s tempting to offload your thinking to AI. Cognitive science shows why that’s a bad idea

  08 May 2026
Increased offloading to new tools has raised the fear that people will become overly reliant on AI.

Making AI systems more transparent and trustworthy: an interview with Ximing Wen

  07 May 2026
Find out more about Ximing's work, experience as a research intern, and what inspired her to study AI.

Report on foundation model impacts released

  06 May 2026
Partnership on AI publish a progress report on post-deployment governance practices.

Forthcoming machine learning and AI seminars: May 2026 edition

  05 May 2026
A list of free-to-attend AI-related seminars that are scheduled to take place between 5 May and 30 June 2026.

AI for Science – from cosmology to chemistry

  01 May 2026
How AI is transforming science, from a day conference at the Royal Society
monthly digest

AIhub monthly digest: April 2026 – machine learning for particle physics, AI Index Report, and table tennis

  30 Apr 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

The Machine Ethics podcast: organoid computing with Dr Ewelina Kurtys

In this episode, Ben chats to Ewelina about the uses of organoids and energy saving computing, differences between biological neurons and digital neural networks, and much more.

#AAAI2026 invited talk: Yolanda Gil on improving workflows with AI

  28 Apr 2026
Former AAAI president on using AI to help communities of scientists better streamline their research.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence