ΑΙhub.org
 

Radical AI podcast: featuring Sarah Myers West


by
16 June 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 Sarah Myers West about “Racism and Sexism in AI Technology? Navigating Systems of Power”.

Racism and sexism in AI technology? Navigating systems of power with Sarah Myers West

Can you separate technology from power? Is technology ever objective? How do we build technology that meets the needs of everyone? To answer these questions and more The Radical AI Podcast welcomes Dr Sarah Myers West to the show. Dr Sarah Myers West is a postdoctoral researcher at the AI Now Institute. Her research centers on the critical study of technology and culture, with an emphasis on historical and ethnographic methods. Dr West is currently working on a project that addresses the politics of diversity and inclusion in technological communities by exploring the nexus of artificial intelligence, gender, and intersectionality. She received her doctoral degree from the Annenberg School for Communication and Journalism at the University of Southern California in 2018, where her dissertation examined the cultural history and politics of encryption technologies from the 1960s to the present day. 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 :

Maryna Viazovska’s proofs of sphere packing formalized with AI

  27 Apr 2026
Formalization achieved through a collaboration between mathematicians and artificial intelligence tools.

Interview with Deepika Vemuri: interpretability and concept-based learning

  24 Apr 2026
Find out more about Deepika's research bridging the gap between data-driven models and symbolic learning.

As a ‘book scientist’ I work with microscopes, imaging technologies and AI to preserve ancient texts

  23 Apr 2026
Using an array of technologies to recover, understand and preserve many valuable ancient texts.

Sony AI table tennis robot outplays elite human players

  22 Apr 2026
New robot and AI system has beaten professional and elite table tennis players.

Causal models for decision systems: an interview with Matteo Ceriscioli

  21 Apr 2026
How can we integrate causal knowledge into agents or decision systems to make them more reliable?

A model for defect identification in materials

  20 Apr 2026
A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.

‘Probably’ doesn’t mean the same thing to your AI as it does to you

  17 Apr 2026
Are you sure you and the AI chatbot you’re using are on the same page about probabilities?

Interview with Xinwei Song: strategic interactions in networked multi-agent systems

  16 Apr 2026
Xinwei Song tells us about her research using algorithmic game theory and multi-agent reinforcement learning.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence