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Resistance AI Workshop
Suzanne Kite · Mattie Tesfaldet · J Khadijah Abdurahman · William Agnew · Elliot Creager · Agata Foryciarz · Raphael Gontijo Lopes · Pratyusha Kalluri · Marie-Therese Png · Manuel Sabin · Maria Skoularidou · Ramon Vilarino · Rose Wang · Sayash Kapoor · Micah Carroll

Fri Dec 11 07:00 AM -- 05:30 PM (PST) @
Event URL: https://sites.google.com/view/resistance-ai-neurips-20 »

It has become increasingly clear in the recent years that AI research, far from producing neutral tools, has been concentrating power in the hands of governments and companies and away from marginalized communities. Unfortunately, NeurIPS has lacked a venue explicitly dedicated to understanding and addressing the root of these problems. As Black feminist scholar Angela Davis famously said, "Radical simply means grasping things at the root." Resistance AI exposes the root problem of AI to be how technology is used to rearrange power in the world. AI researchers engaged in Resistance AI both resist AI that centralizes power into the hands of the few and dream up and build human/AI systems that put power in the hands of the people. This workshop will enable AI researchers in general, researchers engaged in Resistance AI, and marginalized communities in particular to reflect on AI-fueled inequity and co-create tactics for how to address this issue in our own work.

We will use the main/webinar Zoom + livestream for most events, with interactive events taking place on a separate auxiliary/breakout Zoom or gather.town. Please see our workshop site for details: https://sites.google.com/view/resistance-ai-neurips-20/schedule
See also our welcome doc here for further detail, including community guidelines and where each activity can be found: http://bit.ly/rai-welcome

Author Information

Suzanne Kite (N/A)
Mattie Tesfaldet (McGill University & MILA)

Mattie Tesfaldet (they/them) is a computer vision and machine learning researcher, artist, and DJ based in Montréal, Canada. They are pursuing their PhD at McGill University and Mila researching generative models for visual content creation, specifically, looking for novel and interesting ways images and videos can be represented with neural networks. Outside of academia, they like to apply their research with the aim of exploring the intersection of human creativity and artificial intelligence. Particularly, developing new AI-based mediums for communication, expression, and sharing of visual imagery.

J Khadijah Abdurahman (Columbia)
William Agnew (University of Washington)
Elliot Creager (University of Toronto)
Agata Foryciarz (Stanford)
Raphael Gontijo Lopes (Google Brain)
Pratyusha Kalluri (Stanford University)
Marie-Therese Png (University of Oxford)
Manuel Sabin (Berkeley)
Maria Skoularidou (University of Cambridge)
Maria Skoularidou

I hold a 4-year Bachelor of Science in Informatics and 2-year Master of Science in Statistical Science both from Athens University of Economics and Business and a PhD in probabilistic machine learning from MRC-Biostatistics Unit, University of Cambridge. I am a Postdoctoral Associate with the Intestate of M.I.T. andHarvard under EWSC research fellowship. My fields of interest lie in theory of probabilistic machine learning, theory and methodology of Bayesian high-dimensional problems, information theory and generative modelling with applications to genomics and healthcare

Ramon Vilarino (Experian DataLabs)
Rose Wang (Stanford)
Sayash Kapoor (Princeton University)
Micah Carroll (UC Berkeley)

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