{"id":159489,"date":"2026-08-04T15:34:16","date_gmt":"2026-08-04T23:34:16","guid":{"rendered":"https:\/\/xira.com\/p\/2026\/08\/04\/new-site-from-suffolk-law-dean-andrew-perlman-catalogs-ai-policies-at-128-law-schools\/"},"modified":"2026-08-04T15:34:16","modified_gmt":"2026-08-04T23:34:16","slug":"new-site-from-suffolk-law-dean-andrew-perlman-catalogs-ai-policies-at-128-law-schools","status":"publish","type":"post","link":"https:\/\/xira.com\/p\/2026\/08\/04\/new-site-from-suffolk-law-dean-andrew-perlman-catalogs-ai-policies-at-128-law-schools\/","title":{"rendered":"New Site From Suffolk Law Dean Andrew Perlman Catalogs AI Policies At 128 Law Schools"},"content":{"rendered":"

The post New Site From Suffolk Law Dean Andrew Perlman Catalogs AI Policies At 128 Law Schools<\/a> appeared first on Above the Law<\/a>.<\/p>\n

When law school AI policies have made news, it has usually been because they were controversial. UC Berkeley School of Law\u2019s restrictive policy, which I wrote about in May<\/a>, drew national attention for barring generative AI from nearly every stage of producing graded work.<\/p>\n

But a new website launched by Andrew Perlman<\/a>, dean of Suffolk University Law School, reveals how widespread and varied these policies have become. The site, AI in Legal Education: Law School Policy Archive<\/a>, catalogs public AI policies, teaching strategies, and curricular programs from 128 of the 196 U.S. law schools, organized into eight topic areas and derived from the schools\u2019 own published documents.<\/p>\n

For each school, the archive links to the underlying source, including student handbooks, honor codes, dean\u2019s memoranda, strategy statements and program pages. Each source is also labeled by its status: in effect, interim, pilot, proposed, guidance, or completed\/limited.<\/p>\n

The full dataset is downloadable as a spreadsheet, and Perlman invites readers to submit policies, corrections and omissions.<\/p>\n

Perlman, long one of legal education\u2019s most prominent voices on innovation and technology, is transparent about the site\u2019s scope and limitations \u2013 and about how he built it.<\/p>\n

\"\"<\/a><\/p>\n

Andrew Perlman<\/p>\n<\/div>\n

The site\u2019s methodology section says that ChatGPT Sites was used extensively to research and construct the archive, with ChatGPT locating many of the public sources, organizing them into topic categories, and helping draft the summaries<\/p>\n

Perlman, the site says, has not manually reviewed or independently confirmed every reference or summary, and readers should consult the linked original sources.<\/p>\n

It is, in other words, an AI-assembled archive documenting how law schools regulate AI.<\/p>\n

The site notes that a school\u2019s absence from a topic does not mean it lacks a policy, and schools governed by university-wide AI rules may not appear at all.<\/p>\n

The inventory excludes generic university policies, individual syllabi, admissions-only rules, and journal policies.<\/p>\n

What the Data Shows<\/strong><\/h3>\n

The site makes all of the underlying data downloadable. So, in keeping with the meta-ness of an AI-generated inventory of AI policies, I downloaded the data and asked AI to help me analyze it. Since Perlman used ChatGPT to create the site, I enlisted its competitor Claude to evaluate it.<\/p>\n

The spreadsheet I downloaded, current as of Aug. 2, 2026, contains 279 topic records spanning eight subjects at 128 law schools. \u00a0Here is how the subjects break down, showing the number of schools catalogued in each:<\/p>\n