ΑΙhub.org
 

Radical AI podcast: the limitations of ChatGPT with Emily M. Bender and Casey Fiesler


by
09 March 2023



share this:
Photos of Emily and Casey with text The Limitations of ChatGPT

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, Dylan and Jess unpack the limitations of ChatGPT with Emily M. Bender and Casey Fiesler.

Listen to the episode below:


The limitations of ChatGPT

In this episode, we unpack the limitations of ChatGPT. We interview Dr Emily M. Bender and Dr Casey Fiesler about the ethical considerations of ChatGPT, bias and discrimination, and the importance of algorithmic literacy in the face of chatbots.

Emily M. Bender is a Professor of Linguistics and an Adjunct Professor in the School of Computer Science and the Information School at the University of Washington, where she has been on the faculty since 2003. Her research interests include multilingual grammar engineering, computational semantics, and the societal impacts of language technology. Emily was also recently nominated as a Fellow of the American Association for the Advancement of Science (AAAS).

Casey Fiesler is an associate professor in Information Science at University of Colorado Boulder. She researches and teaches in the areas of technology ethics, internet law and policy, and online communities. Also a public scholar, she is a frequent commentator and speaker on topics of technology ethics and policy, and her research has been covered everywhere from The New York Times to Teen Vogue.

Follow Emily on Twitter @emilymbender or emilymbender@dair-community.social on Mastodon.

Follow Casey on Twitter @cfiesler or cfiesler@hci.social on Mastodon or @professorcasey on TikTok.

If you enjoyed this episode please make sure to subscribe, submit a rating and review, and connect with us on twitter at @radicalaipod.

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 :

#RoboCup2026 – humanoid league knockout stages

  06 Jul 2026
Find out who won the small, middle and large divisions in Incheon.

#RoboCup2026 – humanoid league day 2

  03 Jul 2026
Find out the latest from day two of the competition.

#RoboCup2026 – humanoid league day 1

  02 Jul 2026
In the first of our round-ups from the humanoid league we introduce the competition, and report some preliminary results.

Adaptive parallel reasoning: the next paradigm in efficient inference scaling

  02 Jul 2026
A detailed analysis of recent progress in the field of parallel reasoning.

Scientists develop new method to generate protein datasets for training AI

  01 Jul 2026
AI is only as good as the data used to train it, and in some areas of protein engineering, the right data is hard to come by.

What’s coming up at #RoboCup2026?

  29 Jun 2026
Find out what's in store at this year's international competition.

AI model used to generate complete models of proteins in motion

  26 Jun 2026
Researchers have used a neural network to create all-atom models of proteins, as well as the dynamic movements that govern their function.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence