The Radical AI Podcast
A podcast by Radical AI
Categorie:
91 Episodio
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Stay Radical: A Final Goodbye from Dylan and Jess
Pubblicato: 09/08/2023 -
Twitter vs. Mastodon with Johnathan Flowers
Pubblicato: 26/04/2023 -
More than a Glitch, Technochauvanism, and Algorithmic Accountability with Meredith Broussard
Pubblicato: 22/03/2023 -
The Limitations of ChatGPT with Emily M. Bender and Casey Fiesler
Pubblicato: 01/03/2023 -
ChatGPT: What is it? How does it work? Should we be excited? Or scared? with Deep Dhillon
Pubblicato: 25/01/2023 -
Sounds, Sights, Smells, and Senses: Let’s Talk Data with Jordan Wirfs-Brock
Pubblicato: 30/11/2022 -
How to Stay Safe Online with Seyi Akiwowo
Pubblicato: 26/10/2022 -
Data Privacy and Women’s Rights with Rebecca Finlay
Pubblicato: 28/09/2022 -
Digital Lethargy with Tung-Hui Hu
Pubblicato: 31/08/2022 -
Should the Government use AI? with Shion Guha
Pubblicato: 27/07/2022 -
Envisioning a Decolonial Digital Mental Health with Sachin Pendse, Munmun De Choudhury, and Neha Kumar
Pubblicato: 29/06/2022 -
Visualizing Our Lives Through Data with Jaime Snyder
Pubblicato: 25/05/2022 -
Let’s Talk About Sex: Digital Pornography and LGBTQIA+ Censorship w/ Alex Monea
Pubblicato: 27/04/2022 -
New Year, New You: Welcome Back to the Radical AI Podcast
Pubblicato: 20/04/2022 -
Measurementality #7: Why AI Registries are Critical for Metrics of Accountability with Sara Jordan and Anand Rao
Pubblicato: 19/12/2021 -
Decolonial AI 101 with Raziye Buse Çetin
Pubblicato: 08/12/2021 -
Design Justice 101 with Sasha Costanza-Chock
Pubblicato: 03/11/2021 -
What Causes AI to Fail? with the AI Today Podcast
Pubblicato: 15/10/2021 -
Measurementality #6: Authentic Accountability for Successful AI with Yoav Schlesinger
Pubblicato: 11/10/2021 -
Predicting Mental Illness Through AI with Stevie Chancellor
Pubblicato: 06/10/2021
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.