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Critic with public evidence across Culture, work & education.
Maybe you mean this from 2023? www.nytimes.com/2026/06/30/o... "[LLMs] are not reasoning machines. [...] It’s not just that they don’t test their outputs to make sure they’re correct or logical, or that they fail to do so in certain instances. They can’t, and they’ll never be …
I’m excited to share a new paper in Nature that shows how large language models launder the strategic rhetoric of authoritarian states. Paper here: www.nature.com/articles/s41.... A thread.
“In light of the above, the Commission believes that AI companies that steer the outputs of their AI systems toward unexpected objectives, and away from the objectives set by or reasonably expected by users, are likely to deceive.” www.ftc.gov/news-events/...
Even if you're not aligned with everything in the manifesto, the AI Resist List is a great reference if you want to encourage students to think about shaping AI futures. For example, here are projects advocating for worker rights: airesistlist.org#pillar-labor
If you would like to share your thoughts, please use this link (buff.ly/fnANR1x). ACM leadership will take your feedback into account while we develop and implement our AI content strategy over the coming months.
Cool resource from @emilymbender.bsky.social and @nannainie.bsky.social for folks looking to use more precise and less anthropomorphic language. This piece includes a bunch of examples for substitutions to support clearer communication! buttondown.com/maiht3k/arch...
Nice overview of our open-access book, Auditing AI in @the-renovator.bsky.social www.democracyrenovator.com/p/july-13-te... mitpress.mit.edu/978026205172...
I will be at #ACL2026 from July 2--7! I will be giving a keynote at CDL workshop on controlled rearing and hypothesis generation from language models! Tianyang Xu (first author) and I will present work on cross-modal generalization in VLMs on July 7! Paper: aclanthology.org/20…
Are you curious about the environmental impact of AI? Install the AI Impact Tracker to estimate the environmental footprint of your ChatGPT usage, including energy, water, and CO2. chromewebstore.google.com/detail/ai-im... #FAccT2026
CrankGPT. “Just a hand crank, a little computer, and a small stack of speech and language models running locally. Provided the electronics are kept dry and at a reasonable temperature, there’s no reason this thing won’t still work in a thousand years.” [squeezlabs.github.io]
This work was inspired by @tomerullman.bsky.social's “illusion illusion” paradigm (arxiv.org/abs/2412.18613) where VLMs mistake illusion-like images for genuine optical illusions. In both cases, models respond to what a problem looks like rather than what it actually requires.🔮
Anyone trusting a Musk company with anything is a downright idiot at this point, but this (predictable) theft is still funny (source iconomy, link goes to www.axios.com/2026/07/14/s...).
AI fairness folks, help me out? I know that back circa... 2018 or so, there were some handy interactives that had demonstrations of how different definitions of fairness could lead to different model behavior. I'm struggling to track down the links now. Can you point me?
Center = B! 🐝 Cavello (they/them). Left = members they follow (green edges). Right = members who follow them (blue edges). Top = mutual follows (orange edges, slightly larger). Drag any node to reposition; click to open that profile.
