The Radical AI Podcast
A podcast by Radical AI
Categories:
91 Episodes
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Measurementality #5: Intergenerational Collaboration with Sinead Bovell
Published: 9/19/2021 -
Indigenous AI 101 with Jason Edward Lewis
Published: 9/8/2021 -
Casteist Technology and Digital Brahminism with Thenmozhi Soundararajan and Seema Hari
Published: 6/18/2021 -
Measurementality #4: What are we Optimizing for? with Laura Musikanski and Jonathan Stray
Published: 6/16/2021 -
Feminist AI 101 with Eleanor Drage and Kerry Mackereth
Published: 6/2/2021 -
Decentralizing AI with Divya Siddarth
Published: 5/27/2021 -
Killer Robots and Value Sensitive Design with Steven Umbrello
Published: 5/5/2021 -
Measurementality #3: Counting Mental Health and Caregiving in Technology and AI
Published: 5/2/2021 -
Design, Disability, Creativity, and Accessibility with Cynthia Bennett
Published: 4/21/2021 -
Atlas of AI with Kate Crawford
Published: 4/7/2021 -
Defining Bias with Su Lin Blodgett
Published: 3/31/2021 -
Measurementality #2: Children's Data and Sustainability
Published: 3/21/2021 -
Your Computer Is on Fire with Mar Hicks & Kavita Philip
Published: 3/10/2021 -
All Tech is Human Series #9 - Misinformation & Free Expression with Jasmine McNealy & Claire Wardle
Published: 3/3/2021 -
Social Inequality in the Digital Economy with Zanele Munyikwa
Published: 2/24/2021 -
Measurementality #1: Defining What Counts in the Algorithmic Age
Published: 2/14/2021 -
Anti-Trust: Congress and the Tech Lobby with Anna Lenhart
Published: 2/10/2021 -
All Tech is Human Series #8 - Improving Social Media: Content Moderation & Democracy with Sarah T. Roberts & Murtaza Shaikh
Published: 1/27/2021 -
Ability and Accessibility in AI with Meredith Ringel Morris
Published: 1/20/2021 -
2020 Hindsight: The Radical AI Podcast New Years Spectacular!
Published: 12/30/2020
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.