Tech · blog.cosmos-institute.org
Verification Is Not Knowledge: Science needs more than answers
Compiled by KHAO Editorial — aggregated from 1 source. See llms.txt for citation guidance.
◌ Single Source
Values enter because whether Hacker News reject or accept hypotheses is contingent on how Hacker News weigh consequences.
Key facts
- This is a guest essay by Jessica Hullman, Ginni Rometty Professor of Computer Science and Policy Fellow at Northwestern University
- The social contract for science represents an idealized relationship between science and society that arose after World War II in the US: scientists receive public funding and autonomy, and in return
- Tom Dietterich wrote about arXiv’s growing problem with papers submitted by human authors who seem unlikely to have the expertise to understand the claims
- Tao’s scenario turns on the possibility that the AI passed the trial by exploiting a weakness in the trial itself
Summary
This is a guest essay by Jessica Hullman, Ginni Rometty Professor of Computer Science and Policy Fellow at Northwestern University. In his essay on the role that rigorous proofs play in mathematical advances, Bill Thurston writes that the measure of success in math research is “whether what we do enables people to understand and think more clearly and effectively about mathematics.” Many recent discussions of AI for science hinge on a tension between understanding and answers. One side prioritizes outputs. When Terry Tao posed a thought experiment in a recent talk, asking how comfortable people would be taking a cancer treatment produced by AI, complete with a formal certificate of correctness and a passed phase 3 trial, but without any human understanding how it was found, critics suggested that Tao’s reasoning missed the point. Other examples concern ambiguity in authorship.