iiinova — where your digital self keeps evolving

Miranda Bogen @mbogen.bsky.social · 30/07/2026

The LinkedIn slip has gotten out of hand, but @klonick.bsky.social’s prediction of how this will play out are well worth heeding

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Jen Fifield @jenafifield.bsky.social · 30/06/2026

NEW: The Trump administration has shut down a controversial Homeland Security tool it had touted as a way to find noncitizens who’d illegally registered to vote, @propublica.org has learned. 🧵

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Kevin Bankston @handle.invalid · 09/06/2026

We didn't get the data portability we wanted for social networks in time to matter. Now the same fight's shaping up around AI. In my 1st guest post for @mbogen.bsky.social's AI policy newsletter Elicitation, I lay out what real AI portability would look like. elicitation.substack.com/p/dont-let-p...

elicitation.substack.com

Don’t let perfect be the enemy of portable

For real AI data portability, we need importability

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logan koepke @jlkoepke.bsky.social · 04/06/2026

🧵 How do companies in highly regulated domains actually test their AI systems for and mitigate discrimination? Our new @upturn.org paper at @facct.bsky.social w/ Emily Black, @mbogen.bsky.social, @s010n.bsky.social, and @wesleydeng.bsky.social, tries to answer this question: arxiv.org/abs/2606.02957

The Fair Lending Model: How the Longest-Running Algorithmic
Fairness Programs Work in Practice
EMILY BLACK∗, New York University, USA
MIRANDA BOGEN∗, Center for Democracy & Technology, USA
LOGAN KOEPKE∗, Upturn, USA
SOLON BAROCAS, Microsoft Research, USA
WESLEY DENG, Carnegie Mellon University, USA
MINGWEI HSU, Upturn, USA
U.S. financial institutions subject to fair lending laws have been running algorithmic fairness programs for decades. Despite
this long history, remarkably little is known about how these requirements operate in practice. In this paper, we offer the first
empirical account of how financial institutions test for and mitigate algorithmic discrimination on the ground. In doing so, we
shed light on how the regulatory design of fair lending law and regulation have shaped the policies, processes, and practices
of fair lending programs. Drawing on 35 semi-structured interviews with participants across the fair lending ecosystem, we
find that while financial institutions have a floor of fairness practices aimed at preventing discrimination in lending largely
absent in other domains, the specifics of how firms test for discrimination and search for less discriminatory algorithms varies
widely. We also find that regulatory supervision via fair lending examinations has been the key driver of compliance work, but
that the practical impact of fair lending programs often depends on how well they can navigate competing business incentives,
perceived legal tensions, and regulatory uncertainty. Ultimately, our findings highlight the unique role that supervisory
authority has played in successfully fostering fair lending practices—a regulatory design feature that is distinct from other
areas of civil rights law and almost completely absent from recent policy proposals for dealing with algorithmic discrimination.
CCS Concepts: • Social and professional topics → Computing / technology policy

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Miranda Bogen @mbogen.bsky.social · 01/05/2026

📄 New research from my team at @cdt.org together with @dhadfieldmenell.bsky.social's lab at @csail.mit.edu finds that benign fine-tuning of foundation models leads to unpredictable safety drift — with big implications for AI governance. Report below, academic research here: arxiv.org/abs/2604.24902

cdt.org

Out of Tune: Fine-Tuning Foundation Models Leads to Unpredictable Safety Drift

Conclusionpted-models" href="#revisiting-ai-governance-and-policy-for-adapted-models" class="toc-anchor">Revisiting AI Governance and Policy for Adapted Modelssafety-behavior-in-high-stakes-domains" h...

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Mor Naaman @informor.bsky.social · 11/03/2026

🥁🥁🥁 Newly out from us today in Science Advances: “Biased AI Writing Assistants Shift Users’ Attitudes on Societal Issues”. Large Language Models are providing users with autocomplete writing suggestions on many platforms. Could these suggestions shift users’ own attitudes? (spoiler: YES) (1/7)

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Miranda Bogen @mbogen.bsky.social · 28/01/2026

I've been surprised just how little we've been talking about privacy implications of frontier AI beyond training data. tl;dr -- the architecture of AI systems will matter a lot, and developers can act now to do better. New piece in @technologyreview.com: www.technologyreview.com/2026/01/28/1...

technologyreview.com

What AI “remembers” about you is privacy’s next frontier

Agents’ technical underpinnings create the potential for breaches that expose the entire mosaic of your life.

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Miranda Bogen @mbogen.bsky.social · 16/01/2026

It's happening. OpenAI is piloting ads in ChatGPT. openai.com/index/our-ap... In introducing ads to ChatGPT, OpenAI is starting down a risky path. (1/5)

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Nathalie Maréchal, PhD @nathaliemarechal.net · 16/01/2026

And sure enough, OpenAI just announced it would be introducing ads to ChatGPT. Good thing @mbogen.bsky.social & I wrote about the incentives this would create for AI companies, and how those incentives were likely to shape the user experience. TL;DR: it's not great! #itsthebusinessmodel

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logan koepke @jlkoepke.bsky.social · 08/01/2026

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.

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Nathalie Maréchal, PhD @nathaliemarechal.net · 07/01/2026

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.

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Center for Democracy & Technology @cdt.org · 12/12/2025

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...

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A. Feder Cooper @afedercooper.bsky.social · 03/12/2025

[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! [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

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Miranda Bogen @mbogen.bsky.social · 14/11/2025

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...

federalregister.gov

Equal Credit Opportunity Act (Regulation B)

The Consumer Financial Protection Bureau (Bureau or CFPB) is issuing a proposed rule for public comment that amends provisions related to disparate impact, discouragement of applicants or prospective ...

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Federation of American Scientists @scientistsorg.bsky.social · 16/10/2025

🚨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.

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Helen Toner @hlntnr.bsky.social · 22/07/2025

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:

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Miranda Bogen @mbogen.bsky.social · 21/07/2025

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

open.substack.com

Personalized AI is rerunning the worst part of social media's playbook

The incentives, risks, and complications of AI that knows you

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Center for Democracy & Technology @cdt.org · 11/04/2025

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...

ft.com

OpenAI slashes AI model safety testing time

Testers have raised concerns that its technology is being rushed out without sufficient safeguards

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Center for Democracy & Technology @cdt.org · 16/01/2025

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

Graphic for CDT AI Gov Lab's report, "Assessing AI: Surveying the Spectrum of Approaches to Understanding and Auditing AI Systems." Illustration of a collection of AI "tools" and "toolbox" – a hammer and red toolbox – and a stack of checklists with a pencil.

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logan koepke @jlkoepke.bsky.social · 18/11/2024

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...

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