ΑΙhub.org
 

Radical AI podcast: featuring Meredith Ringel Morris


by
25 January 2021



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 Meredith Ringel Morris about ability and accessibility in AI.

Ability and accessibility in AI with Meredith Ringel Morris

What should you know about Ability and Accessibility in AI and responsible technology development? In this episode we interview Meredith Ringel Morris.

Meredith is a computer scientist conducting research in the areas of human-computer interaction (HCI), computer-supported cooperative work (CSCW), social computing, and accessibility. Her current research focus is on accessibility, particularly on the intersection of accessibility and social technologies.

Follow Meredith Morris on Twitter @merrierm.

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

            AIhub is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

#AAAI2026 invited talk: machine learning for particle physics

  01 Apr 2026
How is ML used in the search for new particles at CERN?
monthly digest

AIhub monthly digest: March 2026 – time series, multiplicity, and the history of RoboCup

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

What I’ve learned from 25 years of automated science, and what the future holds: an interview with Ross King

  30 Mar 2026
We launch our new series with a conversation with Ross King - a pioneer in the field of AI-enabled scientific discovery.

A multi-armed robot for assisting with agricultural tasks

and   27 Mar 2026
How can a robot safely manipulate branches to reveal hidden flowers while remaining aware of interaction forces and minimizing damage?

Resource-constrained image generation and visual understanding: an interview with Aniket Roy

  26 Mar 2026
Aniket tells us about his research exploring how modern generative models can be adapted to operate efficiently while maintaining strong performance.

RWDS Big Questions: how do we highlight the role of statistics in AI?

  25 Mar 2026
Next in our series, the panel explores the statistical underpinning of AI.

A history of RoboCup with Manuela Veloso

  24 Mar 2026
Find out how RoboCup got started and how the competition has evolved, from one of the co-founders.

Information-driven design of imaging systems

  23 Mar 2026
Framework that enables direct evaluation and optimization of imaging systems based on their information content.



AIhub is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence