Unlike small, “narrow AI” models built for specific tasks and trained using curated datasets, systems that are advertised as having “broad general knowledge and domain expertise” require models with upwards of hundreds of billions of parame…As detailed by a number of scholars, both the environmental impacts and the unsafe outputs of these systems disproportionately affect marginalized groups like racial and gender minorities, disabled people, and citizens of developing countri…
Emily Bender
scientist · 2 mentions across 1 reading
In this course
Emily Bender is a computational linguist and AI researcher known for critical work on the social and environmental harms of large language models, particularly their disproportionate impacts on marginalized communities. The course readings cite her scholarship to ground arguments about how scale in AI systems (hundreds of billions of parameters) creates not just technical problems but deeply political ones—concentrated in the labor, environmental, and safety costs borne by already vulnerable populations. Her work appears to anchor the seminar's concern that "Pandaemonium Architecture" isn't merely a technical phenomenon but a structure of dispossession.
Mentioned in 1 reading
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