What would be the standard operating conditions for a system advertised as a “universal algorithm for learning and acting in any environment” [127]? How could experiments designed to test the functionality of such a system have construct va…Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell, 2021. “On the dangers of stochastic parrots: Can language models be too big?” FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, …
Paul Bloomfield
philosopher · 2 mentions across 1 reading
In this course
Without a clear Wikipedia entry or direct substantive excerpts, Bloomfield appears as a passing reference in a discussion of construct validity and experimental design for AI systems. The citation context suggests engagement with questions about how we verify whether large language models and learning systems actually possess the capabilities they claim, a concern central to critical AI scholarship. This invocation likely supports arguments about the epistemological limits of testing universal learning systems, appearing within or near the influential "Stochastic Parrots" framework that challenges whether scale alone confers genuine understanding.
Mentioned in 1 reading
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Abeba Birhane 1Alison Bashford 1Angelina McMillan-Major 1Bethany Biron 1Edwin Black 1Emily M. Bender 1Emmanuel Kahembwe 1Lesley Hall 1Lucy Bland 1Margaret Mitchell 1Max Tegmark 1Philippa Levine 1Tawana Petty 1Timnit Gebru 1Vinay Uday Prabhu 1Yoshua Bengio 1Ben Goertzel 1Iris van Rooij 1Jack Germain 1Nitasha Tiku 1Sam Altman 1Toby Ord 1