We work on eliminating AI harms and accelerating imagination and creation of new technologies and tools addressing the needs of our communities. Our interdisciplinary works range from building state-of-the-art language technologies for some of the world’s most ignored languages to documenting the exploited workers fueling AI systems.
Our work has two main goals:
To mitigate, disrupt, eliminate, and slow down the harms caused by AI technology, and to create spaces that allow us to imagine otherwise.
We use quantitative and qualitative methodologies to equip historically marginalized groups with data to advocate for change.
Centering the experiences of data workers in machine learning by using the Workers' Inquiry approach to uncover opportunities for collaborative knowledge exchange and collective organizing. Go to https://data-workers.org to find zines, reports, documentaries, podcasts and more created by 16 data workers from 4 continents.
Analyzing the impacts of South African apartheid using computer vision techniques and satellite imagery. Read our NeurIPS paper and this MIT Tech Review article, and check out our dataset and visualizations.
Analyzing the history of Black protests in the US and Canada using machine learning methods. Read our papers on Sociological Science and Mobilization to learn more.
We expose the real harms of AI systems while countering AI hype.
Creating natural language processing tools, and using mixed methods (quantitative and qualitative) approaches to analyze the impacts of social media platforms on neglected countries and languages. Watch our short documentary on the topic.
AI is fueled by the artists, writers and “zombie trainers” (see below) supplying training and evaluation data without consent or compensation. Vulnerable populations like refugees and gig workers are hired as data workers under exploitative working conditions (see Data Workers Inquiry). These same vulnerable populations are also the first to experience the harms of AI systems, whether it is through automated weapons or surveillance systems (see Surveillance Watch). This page has more of our research on the inequities fueled by AI systems.
Image: Leo Lau & Digit / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/
Big tech companies are throwing money at artificial general intelligence (AGI), with CEOs telling us that it will come, bringing with it utopia, any day now (for the measly price of SEVEN TRILLION DOLLARS according to Sam Altman). How did AGI come to be a dominant goal in AI? What motivates the drive to attempt to build it? This page is dedicated to answering this question, starting with our paper, "The TESCREAL Bundle: Eugenics and the Promise of Utopia through Artificial General Intelligence," which you can read on First Monday. Image is Clarote & AI4Media / Better Images of AI / Power/Profit / CC-BY 4.0
Uncovering the hype behind AI and what we can do about it. In The AI Con, Emily M. Bender and Alex Hanna offer a sharp, witty, and wide-ranging take-down of AI hype across its many forms.
Showing the extent to which vulnerable populations like refugees are both exploited laborers fueling “AI” systems and those most harmed by them. Read our papers and articles to learn more.
Focusing on how algorithmic management and workplace surveillance allows corporations like Amazon to steal wages, intensify poor working conditions, and evade responsibility.
This interactive map reveals the intricate connections between surveillance companies, their funding sources and affiliations. Notice missing entries? Submit them on the website. Used the tool for your work, or have other feedback? Let us know!
Examining who benefits from "AI" systems and who is harmed (e.g. read AI for Whom?, AI Art and Its Impact on Artists, AI and Inequality in Hiring).
Artificial Intelligence has too much hype. In this stream, linguist Prof. Emily M. Bender and sociologist Dr. Alex Hanna break down the AI hype, separate fact from fiction, and science from bloviation. They're joined by special guests and talk about everything, from machine consciousness to science fiction, to political economy to art made by machines.
New technological futures reflective of everyone being able to see themselves centered design, safety, joy, and beyond margins.
This project seeks to develop “sovereign” language technologies for East African languages, through community-centered design and governance practices that facilitate content creation and adaptation for online knowledge repositories (OKRs).
Counteracting the "one giant model for everything" approach by BigTech, by empowering small, community-rooted organizations around the world building task specific models serving their needs. Read this interview and our paper.
Broad, near-future speculative pieces designed to de-center dominant narratives about technology and challenge us all to realize that things can be different. These are not alternative realities, they are possible futures.
Be sure to also check out our companion zine workshop series.
Counteracting the "one giant model for everything" approach by BigTech by empowering small, community-rooted organizations around the world building task-specific models serving their needs. Check out the Huniki Federation website for more.
The Imagining Possible Futures workshop series creates space to imagine otherwise. Both online and in-person, we imagine alternative futures in the form of drawings, poetry, prose, multimedia pieces, and more. You can check out our collection of zines in our zine library.
Want to participate in a future workshop? Check out our event calendar, and be sure to follow us on bluesky and instagram for updates.
Be sure to check out our companion Possible Futures blog series here.
We have partnered with lesan.ai and Whose Knowledge? to work on language tech in a manner that does not steal data from communities and supports locally relevant content creation (read how Lesan outperforms Google, and this Deutsche Welle article on the AI language gap).
We build frameworks for non-exploitative community rooted in our research practice.
What does it mean to conduct AI research which works for communities? Read DAIR's Research Philosophy to learn more.
Guidelines for ethical data annotation and release practices without exploiting workers and stealing data.
Creating guidelines for designing AI systems that center the needs of specific communities.
Enabling workers to fight back against AI and automation at work.
Stay tuned for tools, resources, and political education for both unions in the bargaining contract process and workers who want to push back against automation technology.
