The Radical AI Podcast
Un pódcast de Radical AI
Categorías:
91 Episodo
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Stay Radical: A Final Goodbye from Dylan and Jess
Publicado: 9/8/2023 -
Twitter vs. Mastodon with Johnathan Flowers
Publicado: 26/4/2023 -
More than a Glitch, Technochauvanism, and Algorithmic Accountability with Meredith Broussard
Publicado: 22/3/2023 -
The Limitations of ChatGPT with Emily M. Bender and Casey Fiesler
Publicado: 1/3/2023 -
ChatGPT: What is it? How does it work? Should we be excited? Or scared? with Deep Dhillon
Publicado: 25/1/2023 -
Sounds, Sights, Smells, and Senses: Let’s Talk Data with Jordan Wirfs-Brock
Publicado: 30/11/2022 -
How to Stay Safe Online with Seyi Akiwowo
Publicado: 26/10/2022 -
Data Privacy and Women’s Rights with Rebecca Finlay
Publicado: 28/9/2022 -
Digital Lethargy with Tung-Hui Hu
Publicado: 31/8/2022 -
Should the Government use AI? with Shion Guha
Publicado: 27/7/2022 -
Envisioning a Decolonial Digital Mental Health with Sachin Pendse, Munmun De Choudhury, and Neha Kumar
Publicado: 29/6/2022 -
Visualizing Our Lives Through Data with Jaime Snyder
Publicado: 25/5/2022 -
Let’s Talk About Sex: Digital Pornography and LGBTQIA+ Censorship w/ Alex Monea
Publicado: 27/4/2022 -
New Year, New You: Welcome Back to the Radical AI Podcast
Publicado: 20/4/2022 -
Measurementality #7: Why AI Registries are Critical for Metrics of Accountability with Sara Jordan and Anand Rao
Publicado: 19/12/2021 -
Decolonial AI 101 with Raziye Buse Çetin
Publicado: 8/12/2021 -
Design Justice 101 with Sasha Costanza-Chock
Publicado: 3/11/2021 -
What Causes AI to Fail? with the AI Today Podcast
Publicado: 15/10/2021 -
Measurementality #6: Authentic Accountability for Successful AI with Yoav Schlesinger
Publicado: 11/10/2021 -
Predicting Mental Illness Through AI with Stevie Chancellor
Publicado: 6/10/2021
Radical AI is a podcast centering marginalized or otherwise radical voices in industry and the academy for dialogue, collaboration, and debate regarding the field of Artificial Intelligence Ethics and the relationship between the humanities and machine learning.