Adio on the working conditions of many thousands of people, mainly in the lower-wage areas of the global south, whose task it is to filter massive data sets for machine learning and software applications that we use every day, by labelling images and flagging harmful content. Adio discusses the sometimes desperate challenges that these people face, and the work that DAIR is doing to bring the issues to public awareness and advocate for fair treatment of the humans who make AI possible.

Raesetje talks about her work on spatial apartheid in South Africa, and how her experience defining and collecting the data sets needed to map a community might translate to Canada's own policy ecosystem.

Adio discusses the invaluable contributions of data workers in the Global South, his advocacy for an inclusive AI ecosystem rooted in a commitment to equity and decoloniality, and the need for a more comprehensive and socially responsible approach to AI that recognizes the intersection of technology, labour, and ethics.

This talk examines the challenges faced by platform laborers around the world, including unfair compensation, job insecurity, and data rights violations. Additionally, they explore the community-rooted AI research that's being done at The DAIR Institute.

Alex and Emily join Charlie Jane Anders and Annalee Newitz to discuss why the Turing Test is so influential in both fiction and reality – and why it is completely wrong.

Alex and Emily join Cayden Mak to help make sense of the inescapable hype of all things “Artificial Intelligence.” What’s being oversold? What are the actual threats? And what exactly are we talking about when we say A.I.? Hype or not, the advancement of technology in the workplace has strong implications for workers which some unions and communities are already organizing to protect themselves against.

Alex and Emily on: limited and general artificial intelligence, the distinction between 'hallucinating' and failing at the goals people set for it, how widespread the BS is, and more.

Mila joins the podcast to talk both about her life as a sociologist and computer scientist researching data workers, but also her experience as a woman, migrant, and mother and containing those identities alongside and within her work.

Timnit joins Paris Marx to talk about misleading framings of artificial intelligence, her experience of getting fired by Google in a very public way, and why we need to avoid getting distracted by all the hype around ChatGPT and AI image tools. (TWSU's most-listened to episode of 2023!)

Timnit talks to the UMass-Amherst based podcast Reimagining the Internet about how we can build just, useful machine learning tools while saying no to harmful AI.

Alex and Mystery AI Hype Theater 3000 co-host Emily M. Bender talk to Luiza Jarovsky about the dangers of overhyped language models and chatbots, and the privacy and fairness implications of badly applied AI technologies.

Timnit describes the #TeamHuman, community rooted AI research philosophy.

Dylan speaks about how AI encodes human biases at Seattle's Museum of History and Industry.

Alex moderated and Krystal participated in this keynote talk at the 2023 ACM conference on Fairness, Accountability and Transparency, in conversation with data workers.

Alex joins ACLUM executive director Carol Rose and Technology for Liberty program director Kade Crockford to talk about how algorithms can deepen existing structural inequities and how both AI and tech writ large can be built more inclusively.

Asme talks about his work on AI ethics for DAIR and language technology for Lesan in this lecture series for the Architectural Association School of Architecture.

Alex, Mila and Dylan join the Unsettling Knowledge Inequities podcast to talk about the implications of widespread, uncritical use of artificial intelligence and machine learning technologies, particularly in replicating and worsening existing inequities.

Timnit and Adrienne talk to KQED Forum about the exploited workers whose underpaid and precarious labor powers artificial intelligence technologies.