a recent New York State audit of NYC's Local Law 144 — designed to ostensibly regulate potential bias and discrimination in automated employment tools — is fairly scathing in its assessment of how implementation and enforcement of the law is going. simply put, LL 144 does not work.

New report from @mbogen.bsky.social & yours truly, on how the big AI companies are trying to make money and what it means for all of us. I am more proud of the title than I have any right to be.

New from CDT: “A Roadmap for Responsible Approaches to AI Memory” by @mbogen.bsky.social & Ruchika Joshi explores how AI systems store, recall, and use info—and what that means for privacy, transparency, and user control. cdt.org/insights/a-r...

[NeurIPS '25] Our oral slot and poster session on "Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research" are tomorrow, December 4! [https://arxiv.org/abs/2412.06966] Oral: 3:30-4pm PST, Upper Level Ballroom 20AB Poster 1307: 4:30:-7:30pm PST, Exhibit Hall C-E

The CFPB proposed a new rule where it would no longer recognize disparate impact liability when enforcing the Equal Credit Opportunity Act. This would eliminate a key protection against discrimination in access to credit, including when AI is involved. www.federalregister.gov/documents/20...

🚨Call for policy proposals If AI adoption is not slowing down, policy governing safety and security practices needs to speed up. This is where you come in.

AI companies are starting to build more and more personalization into their products, but there's a huge personalization-sized hole in conversations about AI safety/trust/impacts. Delighted to feature @mbogen.bsky.social on Rising Tide today, on what's being built and why we should care:

AI companies are starting to promise personalized assistants that “know you.” We’ve seen this playbook before — it didn’t end well. In a guest post for @hlntnr.bsky.social’s Rising Tide, I explore how leading AI labs are rushing toward personalization without learning from social media’s mistakes

Personalization is political. Very excited to share a piece I co-authored with @mbogen.bsky.social as a Google Public Policy Fellow @cendemtech.bsky.social! cdt.org/insights/its...

From CDT’s @mbogen.bsky.social: “As #AI companies are racing to put out increasingly advanced systems, they also seem to be cutting more and more corners on safety, which doesn’t add up.” www.ft.com/content/8...

To truly understand AI’s risks & impacts, we need sociotechnical frameworks that connect the technical with the societal. Holistic assessments can guide responsible AI deployment & safeguard safety and rights. 📖 Read more: cdt.org/insights/ado...

CDT’s Amy Winecoff + @mbogen.bsky.social new explainer dives into the fundamentals of hypothesis testing, how auditors can apply it to AI systems, & where it might fall short. Using simulations, we show its role in detecting bias in a hypothetical hiring algorithm. cdt.org/insights/hyp...

NEW REPORT: CDT AI Governance Lab’s’s Assessing AI reportAudits looks at the rise of complex automated systems which demand a robust ecosystem for managing risks and ensuring accountability. cdt.org/insights/ass... cc: @mbogen.bsky.social

@upturn.org is hiring for a research associate! Excellent opportunity to work with some fantastic folks! www.upturn.org/join/researc...

howdy! the Georgetown Law Journal has published "Less Discriminatory Algorithms." it's been very fun to work on this w/ Emily Black, Pauline Kim, Solon Barocas, and Ming Hsu. i hope you give it a read — the article is just the beginning of this line of work. www.law.georgetown.edu/georgetown-l...