ΑΙhub.org
 

Radical AI podcast: featuring Raziye Buse Çetin


by
17 December 2021



share this:

Raziye Buse Çetin
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 Raziye Buse Çetin about decolonial AI.

Decolonial AI 101

What is Decolonial AI? How can we apply a postcolonial lens to AI design?

In this episode we interview Raziye Buse Çetin about colonial, decolonial, and postcolonial AI – and the newly-released Decolonial AI Manyfesto.

Buse is an AI policy and ethics researcher and consultant. Her work revolves around ethics, impact, and governance of AI systems. She combines her lived experience with her interest in postcolonial studies, intersectional feminism and science and technology studies (STS) to develop critical thinking about AI technologies and narratives around it.

Follow Buse on Twitter @BuseCett.

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.



tags: ,


The Radical AI Podcast

            AIhub is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

‘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.

2026 AI Index Report released

  15 Apr 2026
Find out what the ninth edition of the report, which was published on 13 April, says about trends in AI.

Formal verification for safety evaluation of autonomous vehicles: an interview with Abdelrahman Sayed Sayed

  14 Apr 2026
Find out more about work at the intersection of continuous AI models, formal methods, and autonomous systems.

Water flow in prairie watersheds is increasingly unpredictable — but AI could help

  13 Apr 2026
In recent years, the Prairies have seen bigger swings in climate conditions — very wet years followed by very dry ones.

Identifying interactions at scale for LLMs

  10 Apr 2026
Model behavior is rarely the result of isolated components; rather, it emerges from complex dependencies and patterns.

Interview with Sukanya Mandal: Synthesizing multi-modal knowledge graphs for smart city intelligence

  09 Apr 2026
A modular four-stage framework that draws on LLMs to automate synthetic multi-modal knowledge graphs.

Emergence of fragility in LLM-based social networks: an interview with Francesco Bertolotti

  08 Apr 2026
Francesco tells us how LLMs behave in the social network Moltbook, and what this reveals about network dynamics.



AIhub is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence