Nitzberg When code isn’t law (web)
Citation
Brian Judge, Mark Nitzberg and Stuart Russell. “When code isn’t law: rethinking regulation for artificial intelligence.” Policy and Society, vol. 44, no. 1, January 2025, pages 85 to 97. Oxford University Press. Published online May 29, 2024. https://doi.org/10.1093/polsoc/puae020. Article page: https://academic.oup.com/policyandsociety/article/44/1/85/7684910. Read 2026-11-06.
Bottom line
- A peer-reviewed journal article by three authors at the Center for Human-Compatible AI, UC Berkeley, with Mark Nitzberg among them.
- It says that regulators cannot directly analyze or audit deep learning systems against regulations. It proposes an adapted model of regulation.
Background
The article page in Policy and Society, an Oxford University Press journal. bin/grab.py got an HTTP 403 error from the publisher. The library read the live page. The permissions link on the page marks the article as open access under Creative Commons Attribution (CC BY). This is a profile page. Mark Nitzberg’s entity page lists it; no reading list does.
Key claims
- “This article examines the challenges of regulating artificial intelligence (AI) systems and proposes an adapted model of regulation suitable for AI’s novel features.” (Abstract)
- “Unlike past technologies, AI systems built using techniques like deep learning cannot be directly analyzed, specified, or audited against regulations.” (Abstract)
- “Their behavior emerges unpredictably from training rather than intentional design.” (Abstract)
- The page gives all three authors the affiliation “Center for Human-Compatible AI, University of California—Berkeley, Berkeley, CA, United States”. (author information)
Evidence and method
A peer-reviewed journal article. The library read the title, author information and the start of the abstract.
Limits
- The library did not read the full text.
- The library holds no copy: the publisher refused the download.