Prof @ Trent University (Cultural Studies/School of the Environment)
I think, write, and make art about climate change, digital infrastructures, and energy politics.
| Pronouns | She/her |
Power Shift is out!
This keywords project brings together many long-admired energy humanities thinkers in 1 book of very assignable essays. In my entry I (perhaps unsportingly?) refuse to talk much about screen time & instead muse about infrastructure, data sovereignty, and (eventually, a little bit,) bike trails.
Me alegro mucho de que haya una traducción al español de mi fanzine sobre las luchas en los centros de datos. Más recursos para la gente que se está metiendo en buenas peleas con infraestructuras no deseadas y extractivas 💟
https://emmlab.info/Resources_page/Luchar%20contra%20los%20centros%20de%20datos_digital.pdf
Unfortunately JEM doesn't allow for preprint publications, but I'm more than happy to email pdfs to anyone who's interested but doesn't have subscription access via an institution.
Finally: It's short! It includes curses! It doesn't do the false hope thing, but it points to interesting coalitions and tactics for resistance. I hope it will be fun to assign in a lot of classrooms.
And the other dividend here to thinking about AI as trash is that we can examine ways that work/definitely don't work to address other kinds of pollution. Supply chain and policy interventions that address the preconditions for the production of trash might be more productive than focusing only on consumer choices, for example.
Also, on the other side of things, I think it's just really productive to incredibly dismissive of the mass roll out of shitty chat bots. They're trash. We should say so
I've got a new commentary out with the Journal of Environmental Media Studies. It's my attempt to think of genAI as a pollution problem--both environmental and informational.
I borrow from discard studies to think of parallels between genAI + single use plastics. Part of the problem is the way these categories unhelpfully collect + obscure very different kinds of things, which too easily become trash....
https://doi.org/10.1386/jem_00138_1
This commentary discusses the rise of generative machine learning tools (so-called artificial intelligence [AI]) and their joint informational and environmental harms. It takes the argumentative stance that most AI today can be usefully described as a kind of trash, both in terms of the quality of its outputs and its proliferating social and ecological costs. Extending the analogy further, it explores how the AI trash problem is best approached like other discard problems, namely by pursuing policy solutions that address the preconditions for waste rather than relying on individual awareness or moral judgements about consumer behaviours to fix injustices. It concludes with a few directions to this end as well as a call for coalition-making on the part of environmentalists and tech critics.