🌶 David Gray Widder

@davidthewid.bsky.social

3163 Followers 631 Following

Assistant Prof at UT Austin's iSchool. Big Tech, political economy, AI hype, AI in War trying to help computer ppl think more critically about computer, including me exCornell/CMU/NASA/MSR/IntelLabs. davidwidder.me

Graphic from DARPA grant solicitation saying "demonstrating the prediction that a boy approaching a soldier may hand him an object, based on previously observed cases".
Screenshot from Cornell Newsletter that says: "Marx to lead new center for entrepreneurship, innovation Matt Marx will be the new vice provost for entrepreneurship, innovation and external engagement and lead the Cornell Center for Entrepreneurship and Innovation."
Gdoc interface file title: ~~David's Texas Era!!!~~ (6 year research plan)
A light blue poster with black text and dark purple title with same info about meet up as found on this website: https://aisupplychainresearchandhci.wordpress.com/how-could-ai-supply-chain-research-shape-hci-inquiries-and-vice-versa/
Page 1 of agenda item here: https://www.utsystem.edu/sites/default/files/offices/board-of-regents/board-meetings/agenda-book-full/2-2026AB.pdf
screenshot of entirely empty monday, entirely full Tuesday weekly calendar
a screencap of the LPE logo - white text on background of crowd of people from above with a few umbrellas
City of Austin Utilities email shaming me for using 1200% more electricity this week than last. With a blue bar chart showing this.
magazine article with headline "the machines are taking over" with facing BW photo of reflected female operator peering toward old looking computer
Cartoon work man in suit with robot firing worker operating machinery with caption "Science has learned how to eliminate the misery, monotony and drudgery of your job. You're fired!"
Front page of CACM opinion article linked in post.
David smiling wearing a burnt orange Texas Research t-shirt holding a burnt orange Texas coffee mug. He is indoors, standing to the right of a plant and in front of a window with the williamsburg bridge behind.
Lucy, David and Joan seated, tbe last two listening while Lucy talks with her hands.
Inha in black dress and white shirt posing for photo with david in white shirt and pink shorts in front of black statue with gold chinese characters. they are doing the two finger peace sign and smiling.
Yellow slide with big title "Big isn't open!", Big in bold and open in red. Subtitle "Who Big serves, how Big threatens Open, and small ways forward." Byline: "David Gray Widder • Berkeley Open Source AI Convening • 12 August 2025"
David Gray Widder is a postdoctoral fellow at Cornell University in the Digital Life Initiative, an affiliate of the Data & Society Research Institute, and an incoming assistant professor in the School of Information at the University of Texas at Austin. Nathan Kim is a PhD student in the School of Information at the University of Michigan, and a Research Intern at the Distributed AI Research Institute. With special thanks to Brian Chen, Max von Thun, Vera Franz, Paul Ohm, Jack Corrigan, Seda Gürses, James Ravenscroft, Erie Meyer, Tejas Narechania, Inha Cha, Julie Widder, Adam Pickersgill, Freddy Reiber, Agathe Balayn, Stephanie T. Nguyen, and unnamed government personnel for their advice at various stages of preparing this report. This report should not be construed to represent their own views, or that of their institutions. Any errors are solely those of the authors. Your questions and ideas are welcome! Correspondence to: david.g.widder@gmail.com <EUAISF logo> This work was supported by the European AI & Society Fund as part of their Global Market Power fellowship program. We are grateful to Crunchbase for access to their data.
3 heat maps of the world, one for each Big Cloud company. Amazon visibly invests a higher % of its deals in India, Google in Brazil and lesser in india, Microsoft in China.
Two very large heat maps, each with Developer Services, As a Service, Cloud, Data, Internet Infra, and Hardware on the Y axis, and the Big Cloud companies alongside NVidia, Apple, Meta, Accel and Sequoia Capital on the Y axis. The temperature of each sell measures % of time that investor is the sole or lead investor respectively, and broadly show that AI supply chain companies are more likely to be dependent on Big Cloud investor as their sole or lead investor than other investors.
Split bar chart with red and blue bars per investor, showing that Google and Microsoft invest via Accelerator programs more than their other investments, whereas the reverse is true for Amazon. Of course, accelerators invest only through accelerator programs, and the biggest VCs make no accelerator investments. Other Big Tech companies have no recorded accelerator investments.
The first bar graph in the report, showing google having the most investments (3501), Microsoft second (1681) and then Amazon (745), all way more than other “Magnificent Seven” big tech companies and way way more than all other investors, and in the same range of other bars representing Big VC and Active Accelerators.
The cover of the report, with dark blue title "How Big Cloud becomes Bigger" with "Bigger" in bold, and subtitle in light blue "Scrutinizing Google Microsoft and Amazon's investments", and light grey author line "David Gray Widder and Nathan Kim" on light grey page background with three clouds: white, dark grey, and very dark grey getting bigger and going towards the top right until they're off the page.
Screenshot of a gmail inbox with advertisement reading "Google Cloud Startups: Scale with $200k, on us"
conference schedule on Third Day - online only, 31 july, 2025, full text here: https://ialiis.birzeit.edu/conference/en/
Conference program with spiky artwork and title "Engineering Destruction: Militarization and the War Economy", and details: "29-31 July at Birzeit University and Online, Hall 243, Institute of Law Annex Building".
A green flier with title "From Tech Lash to Text Fash: Strategic Reflections on a Decate of Collective organizing in Computing" with a QR code and link (same as one in body of post) and with blurb and details: Hybrid Workshop @ Aarhus Tuesday August 19, 8:30-11:30 am EST / 2:30-5:30 pm CEST Computing is a field plagued with presentism, oriented towards the new in ways that limit our design and research practices - as well as our capacity to understand and collectively respond to emerging crises. To improve our sensemaking and strategizing about today's crises, this workshop explores what Tamara Kneese has deemed the last decade's shift from "techlash" to "tech fash". What have we learned from the era of misinformation and bias, of "surveillance capitalism" and tech worker organizing that can inform our struggle against the increasing power of a techno-fascist oligarchy? We will also look towards previous generations of computing professionals and activists, who likewise sought to address the harms of emerging automated systems and the complicity of computing within violent, imperialist projects. This workshop will create space for participants to explore these questions collectively, bridging past and present moments in an effort to devise strategies moving forward."
tooooo many tabs
Basic Research, Lethal Effects: Military AI Research Funding as Enlistment David Gray Widder Digital Life Initiative, Cornell University Sireesh Gururaja School of Computer Science, Carnegie Mellon University Lucy Suchman Department of Sociology, Lancaster University Abstract In the context of unprecedented U.S. Department of Defense (DoD) budgets, this paper examines the recent history of DoD funding for academic research in algorithmically based warfighting. We draw from a corpus of DoD grant solicitations from 2007 to 2023, focusing on those addressed to researchers in the field of artificial intelligence (AI). Considering the implications of DoD funding for academic research, the paper proceeds through three analytic sections. In the first, we offer a critical examination of the distinction between basic and applied research, showing how funding calls framed as basic research nonetheless enlist researchers in a war fighting agenda. In the second, we offer a diachronic analysis of the corpus, showing how a ‘one small problem’ caveat, in which affirmation of progress in military technologies is qualified by acknowledgement of outstanding problems, becomes justification for additional investments in research. We close with an analysis of DoD aspirations based on a subset of Defense Advanced Research Projects Agency (DARPA) grant solicitations for the use of AI in battlefield applications. Taken together, we argue that grant solicitations work as a vehicle for the mutual enlistment of DoD funding agencies and the academic AI research community in setting research agendas. The trope of basic research in this context offers shelter from significant moral questions that military applications of one’s research would raise, by obscuring the connections that implicate researchers in U.S. militarism. Keywords: artificial intelligence; US Department of Defense; military; funding; investment, war
text: The first camp, which I associate with the external critics, holds that AI is fake and sucks.
Screenshot of Nature website of linked article with title "https://www.nature.com/articles/s41586-024-08141-1" and abstract: This paper examines ‘open’ artificial intelligence (AI). Claims about ‘open’ AI often lack precision, frequently eliding scrutiny of substantial industry concentration in large-scale AI development and deployment, and often incorrectly applying understandings of ‘open’ imported from free and open-source software to AI systems. At present, powerful actors are seeking to shape policy using claims that ‘open’ AI is either beneficial to innovation and democracy, on the one hand, or detrimental to safety, on the other. When policy is being shaped, definitions matter. To add clarity to this debate, we examine the basis for claims of openness in AI, and offer a material analysis of what AI is and what ‘openness’ in AI can and cannot provide: examining models, data, labour, frameworks, and computational power. We highlight three main affordances of ‘open’ AI, namely transparency, reusability, and extensibility, and we observe that maximally ‘open’ AI allows some forms of oversight and experimentation on top of existing models. However, we find that openness alone does not perturb the concentration of power in AI. Just as many traditional open-source software projects were co-opted in various ways by large technology companies, we show how rhetoric around ‘open’ AI is frequently wielded in ways that exacerbate rather than reduce concentration of power in the AI sector.
I study how people building "artificial intelligence" think about the downstream harm their work makes possible. I examine how three overlapping logics shape their thoughts, and our future: 1 Al Supply Chains fracture power and responsibility for downstream harms, enabling ignorance for engineers who want it and complicating resistance for those who don't. 2. Hierarchies of epistemic power narrow tech ethics discourse and limit interventions. 3. Political economic power concentrates resources & control, and limits worker agency. Across 16 peer-reviewed publications in venues from Big Data and Society to CSCW to Nature, I draw on 110+ interviews, fieldwork at Intel, Microsoft and NASA, computational tools, and feminist science and technology studies to examine software engineering ideas and practice. I put critical ideas in popular engineering and computing research venues, and have mentored 9 junior researchers beginning critical work. My writing helps others teach about tech critically: my papers are on 11 syllabi across information science, philosophy, media studies, gender studies, and computer science. I enable better tech policy: my work is cited in 11 white papers, from the Roosevelt Institute to the Royal Society, and in 6 regulatory comments by advocates from Mozilla to the ACLU. I support wider critical technology discourse in 28 invited talks, and by discussing my work with Wired and the New York Times. My agenda will provide epistemic and political economic tools to resist tech harms, and spur new practices, pedagogy, and policy for a broader critical turn in the computing field.