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
Paul Bloomfield appears only in passing reference within the course materials, cited tangentially in discussions of experimental validity and construct design for AI systems. Without fuller context from the excerpts, his specific contribution to the seminar's concerns—whether methodological, philosophical, or critical—remains unclear, though his invocation suggests engagement with questions about how to rigorously test claims made by universal learning systems. His presence alongside the "Stochastic Parrots" framework indicates potential interest in epistemological standards for evaluating AI capabilities.
Mentioned in 1 reading
Appears alongside
People mentioned in the same passages — sorted by co-occurrence weight.
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