Expert attention map

The Who's Who of AI

What credible people across AI noticed, why it matters, and where the field is converging or disagreeing.

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5 experts · 17 posts · 16d ago
Ted Underwood Matthew Kirschenbaum Laura K. Nelson Andrea Lathrop D. Hicks
Multiple readings Concern & critique · 1 Policy & governance · 1 Opportunity & adoption · 1
Ted Underwood: I think it is possible to have this cake while eating it, thus: a) LLM text is often cogent and well-written. It is clearer and more concise than 99% of human text. (I used to teach writing.) b) Wh…
Ted Underwood: I do not want to read an email that the sender didn't write, or a blog post that they commissioned from model X--even if in my own work I find value in that same model. My rejection is not a judgem…
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4 experts · 6 posts · 18d ago
Grace Lindsay Laura K. Nelson Joao Barbosa Sam Barrett, PhD
Multiple readings Research & technical analysis · 2 Building & implementation · 1
Grace Lindsay: Teaching "AI use" in college (not related to teaching how AI is built) is silly because 1.) the tools are meant to be user friendly with minimal training and 2.) they change so often your education…
Sam Barrett, PhD: I disagree. Maybe they are designed to be user friendly but I don't think that means effective use is easy or comes for free. It requires developing mental habits, intuitions and a kind of theory o…
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2 experts · 5 posts · 7d ago
Maria Antoniak Laura K. Nelson
Laura K. Nelson: "RAG improves technical quality, in particular factual accuracy, and prompt engineering steers social representation as requested." I've seen enough similar results, I'm ready to take a stand: We c…
Maria Antoniak: Both? But agreed that it’s frustrating to see people often reporting on unrealistic or non-expert usages alone. It devalues the capabilities of the actual humans engaging in these tasks.
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