The Radical AI Podcast
En podkast av Radical AI
Kategorier:
91 Episoder
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Stay Radical: A Final Goodbye from Dylan and Jess
Publisert: 9.8.2023 -
Twitter vs. Mastodon with Johnathan Flowers
Publisert: 26.4.2023 -
More than a Glitch, Technochauvanism, and Algorithmic Accountability with Meredith Broussard
Publisert: 22.3.2023 -
The Limitations of ChatGPT with Emily M. Bender and Casey Fiesler
Publisert: 1.3.2023 -
ChatGPT: What is it? How does it work? Should we be excited? Or scared? with Deep Dhillon
Publisert: 25.1.2023 -
Sounds, Sights, Smells, and Senses: Let’s Talk Data with Jordan Wirfs-Brock
Publisert: 30.11.2022 -
How to Stay Safe Online with Seyi Akiwowo
Publisert: 26.10.2022 -
Data Privacy and Women’s Rights with Rebecca Finlay
Publisert: 28.9.2022 -
Digital Lethargy with Tung-Hui Hu
Publisert: 31.8.2022 -
Should the Government use AI? with Shion Guha
Publisert: 27.7.2022 -
Envisioning a Decolonial Digital Mental Health with Sachin Pendse, Munmun De Choudhury, and Neha Kumar
Publisert: 29.6.2022 -
Visualizing Our Lives Through Data with Jaime Snyder
Publisert: 25.5.2022 -
Let’s Talk About Sex: Digital Pornography and LGBTQIA+ Censorship w/ Alex Monea
Publisert: 27.4.2022 -
New Year, New You: Welcome Back to the Radical AI Podcast
Publisert: 20.4.2022 -
Measurementality #7: Why AI Registries are Critical for Metrics of Accountability with Sara Jordan and Anand Rao
Publisert: 19.12.2021 -
Decolonial AI 101 with Raziye Buse Çetin
Publisert: 8.12.2021 -
Design Justice 101 with Sasha Costanza-Chock
Publisert: 3.11.2021 -
What Causes AI to Fail? with the AI Today Podcast
Publisert: 15.10.2021 -
Measurementality #6: Authentic Accountability for Successful AI with Yoav Schlesinger
Publisert: 11.10.2021 -
Predicting Mental Illness Through AI with Stevie Chancellor
Publisert: 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.