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Benjamin Laufer

@laufer.bsky.social
289 followers 204 following 91 posts

PhD student at Cornell Tech. bendlaufer.github.io

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Benjamin Laufer @laufer.bsky.social · 28/09/2026
I became curious how many research articles in general-interest science journals mention “AI safety.”
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Benjamin Laufer @laufer.bsky.social · 15/09/2026
Every time I put a hot coffee in a car cupholder, I make a small decision: which way should the hole in the lid face? Forward seems risky when you brake. Backward seems risky when you accelerate. Sideways seems plausible. But I wondered what the optimal direction is, and whether we can find it.
Image of a to-go coffee cup with lid opening oriented backwards.
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LSE Methodology @lsemethodology.bsky.social · 21/08/2026
💡 We're hiring for an Assistant Professor in Computational Social Science Read more and apply before 11 October 👉️ www.lse.ac.uk/methodology/...
LSE Department of Methodology hiring — Assistant Professor in Computational Social Science; applications close 11 October 2026; apply at www.jobs.lse.ac.uk and follow @lsemethodology.
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Johan Ugander @jugander.bsky.social · 18/08/2026
New work out in PNAS studying what values were amplified on X (in Oct 2024), led by @ziv-e.bsky.social, paper here: www.pnas.org/doi/10.1073/... coverage below!
pnas.org
Value misalignments in X’s feed algorithm is a reflection of value tensions in engagement | PNAS
Social media feed algorithms rank content that is purported to be preferred by users, but the engagement behaviors that drive these algorithms are ...
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Kenny Peng @kennypeng.bsky.social · 18/08/2026
New York City 8th graders choose from 900+ high schools to apply to, in a process that’s spawned Facebook groups and dozens of expensive consulting services. Our new paper shows how application behavior leads to disparities, and how to effectively intervene. 🧵 www.nature.com/articles/s44...
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Benjamin Laufer @laufer.bsky.social · 12/08/2026
As a researcher, every day I think about questions I don’t have the answer to. It used to be that most of them just weren’t worth answering because they’d take too much time and resources. I think AI is changing that. Here’s one example: what is the best way to cut an onion?
Diagram showing the model of an onion as concentric layers, and showing intuition for horizontally cutting the half-onion at about 20% of its height.
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University of Washington Information School @ischool.uw.edu · 07/08/2026
Incoming Assistant Professor Ben Laufer recently published a new paper in PNAS. Laufer, Jon Kleinberg & Hoda Heidari explore incentive effects of AI safety regulation using a mathematical model. (1/2) Check out the study: www.pnas.org/doi/10.1073/... @pnas.org @laufer.bsky.social
"The backfiring effect of weak AI safety regulation." Screenshot of article published by the Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS). July 20, 2026. Full text available at https://www.pnas.org/doi/10.1073/pnas.2509768123.
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University of Washington Information School @ischool.uw.edu · 05/08/2026
We look forward to welcoming you to our faculty!
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Benjamin Laufer @laufer.bsky.social · 04/08/2026
I am delighted to share that I'll be joining the University of Washington Information School as an Assistant Professor!
University of Washington campus
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Benjamin Laufer @laufer.bsky.social · 29/07/2026
In a new @fastcompany.com op-ed, I connect recent developments involving Anthropic, Kimi K3, and the EU AI Act to a question from my research: how do rules aimed at one company change the behavior of others in the AI supply chain? www.fastcompany.com/91580189/sho...
fastcompany.com
Should AI companies be able to outsource safety?
Rules aimed only at downstream applications can make AI products less safe. Policymakers should hold both model makers and the companies building on them accountable.
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Science X / Phys.org @sciencex.bsky.social · 20/07/2026
Weak AI rules aimed only at downstream companies may make products less safe than no regulation at all. The model suggests general AI providers can then offload safety costs. doi.org/hcb642
techxplore.com
Weak AI regulation may be worse than none at all, researchers say
A new modeling study finds that weak AI regulation may be worse than no regulation at all when it comes to the safety of AI products and services.
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Gizmodo @gizmodo.com · 21/07/2026
Weak AI Regulation Is Worse Than No Regulation, Researchers Claim gizmodo.com/weak-ai-regulation-is-w…
gizmodo.com
Weak AI Regulation Is Worse Than No Regulation, Researchers Claim
Game theory says the best AI safety regulation is strict and targets everyone in the supply chain, according to the paper.
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Cornell Tech @cornelltech.bsky.social · 21/07/2026
Weak AI regulation may backfire, making products less safe than no regulation at all, according to research from Cornell Tech, Cornell Bowers, and Carnegie Mellon. The study finds that thoughtfully designed AI regulation can improve safety outcomes: bit.ly/4fazlNS
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Benjamin Laufer @laufer.bsky.social · 21/07/2026
One intuition behind many AI policy proposals is that downstream AI applications -- the companies deploying AI in healthcare, finance, education, customer service, etc. -- should bear responsibility for ensuring safety. Our paper asks: What incentives does that create for the firms building AI?
Illustrative example of our game-theoretic model. This numeric instance of the game consists of one general-purpose producer and three domain-specialists. Each player has a different utility in performance-safety space which dictates the path of development. Within this setting, the no-regulation game (Upper Left) reveals the players’ investment efforts when no floor is imposed on safety. Regulating the domain-specialist alone (Upper Right) exhibits backfiring for all three domains, meaning the regulated safety level is lower than it would be without regulation. In this particular example, the same floor is assumed for all three domain-specialists. Regulating the generalist alone (Lower Left) improves the safety level slightly across all three domains, compared to no-regulation. Finally, a regime that targets both generalists and specialists with regulation (Lower Right) is able to 1) retain the improved safety performance from regulating the generalist, 2) improve the safety level of least-safe domain-specialist, while 3) avoiding backfiring. The purpose of this figure is to visualize the model’s incentive mechanisms; none of these panels represent real regulations.
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Data Science Institute @dsi-uchicago.bsky.social · 22/01/2026
Join us on Monday, January 26th for a Computer Science and DSI Joint Colloquium! Featuring Ben Laufer, PhD candidate at Cornell University, on ‘AI Ecosystems: Structure, Strategy, Risk, and Regulation’ datascience.uchicago.edu/events/ben-l...
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JHU Computer Science @jhucompsci.bsky.social · 22/01/2026
Join us next week for a seminar with @cornelltech.bsky.social’s @laufer.bsky.social! Learn more about his upcoming talk here: www.cs.jhu.edu/event/cs-sem...
Computer Science Seminar Series. AI Ecosystems: Structure, Strategy, Risk, and Regulation. January 29, 2025. 228 Malone Hall. Refreshments available 10:30 a.m. Seminar begins 10:45 a.m. Benjamin Laufer, Cornell Tech.
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Rafael M Batista @rafmbatista.bsky.social · 25/09/2025
Saw Ben presenting this today. It’s really neat work. Ben is finishing up his PhD at Cornell (advised by Jon Kleinberg) and is currently on the job market
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Marcelo Rinesi @marcelorinesi.bsky.social · 14/08/2025
This is quite clever and useful (read the full thread + the paper). I think/hope it opens up the path to a parallel study of their evolution on the epistemic/semantic space (i.e. what things they get better/worse at over time, what the utility gradients... 1/ via @tedunderwood.me
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Benjamin Laufer @laufer.bsky.social · 14/08/2025
In a new paper with @didaoh and Jon Kleinberg, we mapped the family trees of 1.86 million AI models on Hugging Face — the largest open-model ecosystem in the world. AI evolution looks kind of like biology, but with some strange twists. 🧬🤖
The 2500th, 250th, 50th, and 25th largest model families on Hugging Face. They show varying numbers of generations (between 3 and 8) and different edge types, including adapters, finetunes, merges, and quantizations.
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Benjamin Laufer @laufer.bsky.social · 03/06/2025
I am finding that AI chatbots and language models are rapidly changing my own personal research practices – and my own ethical judgments about the appropriateness of the use of AI.
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Benjamin Laufer @laufer.bsky.social · 25/04/2025
Excited to speak at Princeton @princetoncitp.bsky.social next week!
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Lily Xu @lilyxu.bsky.social · 25/04/2025
I'm hiring for a machine learning data scientist & research assistant for summer 2025! Join me on a project on invasive species management with an innovative startup doing on-the-ground removal of environmentally destructive invasive animals. Paid, full-time w/ possibility to extend.
I'm hiring for a machine learning data scientist & research assistant for summer 2025!

Join me in working on a project on invasive species management, by predicting species risk and planning capture strategies. This work will be in partnership with an innovative startup that is working directly to capture environmentally destructive invasive species in the US.

This project will be working with a US-based conservation partner to build predictive machine learning models and design harvest strategies for the removal of invasive animal species. The primary goal is to develop usable ML models and optimization tools to inform practical environmental decision-making on the ground.

There will also be opportunities to extend this work into a research publication for a top-tier AI venue.

The project would be:
Paid, full-time internship for summer 2025
Possibility of extension beyond the summer (part-time or full-time)
Remote, but candidates should be authorized to work in the US
Supervised by Lily Xu, assistant professor at Columbia University

Ideal candidate background will include:
Strong background in CS, data science, and/or applied math
Experience developing machine learning models
Excellent coding skills in Python
Excellent writing and interpersonal communication skills
Genuine interest in conservation/sustainability
Nice to have: background in optimization methods
Nice to have: experience with GIS and geospatial data
Candidates would ideally have already completed an undergraduate degree, but exceptional undergrads will also be considered.

How to apply:
Please send a CV and 3–5 paragraphs of your background/interests via email to <lily.x@columbia.edu> with the subject line "Application: ML for invasive species management". 

Applications will be reviewed on a rolling basis.
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Kenny Peng @kennypeng.bsky.social · 02/04/2025
4) The “most common dog” in NYC is a Yorkshire Terrier named Bella. Jack Russel Terriers are often “Jack” and Charles Spaniels “Charlie.” Huskies are always named Luna—the reason for which is unclear (?).
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Benjamin Laufer @laufer.bsky.social · 02/04/2025
This was a lot of fun
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Benjamin Laufer @laufer.bsky.social · 31/03/2025
I am in Boston, excited to give a talk at northeastern tomorrow 11am! “Regulation along the AI Development Pipeline for Fairness, Safety and Related Goals”
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Kenny Peng @kennypeng.bsky.social · 18/03/2025
(1/n) New paper/code! Sparse Autoencoders for Hypothesis Generation HypotheSAEs generates interpretable features of text data that predict a target variable: What features predict clicks from headlines / party from congressional speech / rating from Yelp review? arxiv.org/abs/2502.04382
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Sophie Greenwood @sjgreenwood.bsky.social · 10/03/2025
Please repost to get the word out! @nkgarg.bsky.social and I are excited to present a personalized feed for academics! It shows posts about papers from accounts you’re following bsky.app/profile/pape...
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Divya Shanmugam @dmshanmugam.bsky.social · 18/12/2024
We have a new review on generative AI in medicine, to appear in the Annual Review of Biomedical Data Science! We cover over 250 papers in the recent literature to provide an updated overview of use cases and challenges for generative AI in medicine.
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Benjamin Laufer @laufer.bsky.social · 13/12/2024
🪩New paper🪩 (WIP) appearing at @neuripsconf.bsky.social Regulatable ML and Algorithmic Fairness AFME workshop (oral spotlight). In collaboration with @s010n.bsky.social and Manish Raghavan, we explore strategies and fundamental limits in searching for less discriminatory algorithms.
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Arvind Narayanan @randomwalker.bsky.social · 02/12/2024
* Emerging scholars — a 2-year staff position in tech policy for candidates who have Bachelor’s degrees. It's an unusual program that combines classes, 1-on-1 mentoring, and work experience with real-world impact. Apply by Jan 10. citp.princeton.edu/programs/cit...
citp.princeton.edu
Emerging Scholars in Information Policy - Center for Information Technology Policy
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Meredith Whittaker @meredithmeredith.bsky.social · 02/12/2024
📢NEW: 'Open' AI systems aren't open. The vague term, combined w frothy AI hype is (mis)shaping policy & practice, assuming 'open source' AI democratizes access & addresses power concentration. It doesn't. @smw.bsky.social, @davidthewid.bsky.social & I correct the record👇 nature.com/articles/s41...
nature.com
Why ‘open’ AI systems are actually closed, and why this matters - Nature
A review of the literature on artificial intelligence systems to examine openness reveals that open AI systems are actually closed, as they are highly dependent on the resources of a few large corpora...
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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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Raj Movva @rajmovva.bsky.social · 30/11/2024
genAI has made us more suspicious that emails, cover letters, artworks, etc. are produced by AI. this shift forces us to change our behavior in order to prove our human-ness: a "burden of authenticity". waking my account up to share a recent blog post on the subject: rajivmovva.com/2024/11/08/g...
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Benjamin Laufer @laufer.bsky.social · 26/11/2024
I passed my “A Exam” yesterday meaning I am officially a “PhD Candidate” rather than a “PhD Student.” (Huge title change, I know.) Thanks to everybody who has supported me along the way!
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Seth Lazar @sethlazar.org · 19/11/2024
Hey! @friedler.net made a FAccT starter pack: bsky.app/starter-pack...
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Benjamin Laufer @laufer.bsky.social · 17/11/2024
Hi to my new connections. Is Bluesky taking off? I’m excited!!
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Benjamin Laufer @laufer.bsky.social · 05/12/2023
In a new essay for @knightcolumbia.org with Helen Nissenbaum, we offer an account of what's wrong with social media, and what's at stake. We also discuss generative AI and, broadly, the problems posed by untrustworthy algorithmic systems.
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Richard Reisman @rreisman.bsky.social · 05/12/2023
Great paper! "…algorithmic amplification is problematic because...it chokes out trustworthy processes that we have relied on for guiding valued societal practices and for selecting, elevating, and amplifying content” via @laufer.bsky.social, Helen Nissenbaum knightcolumbia.org/content/algo...
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Benjamin Laufer @laufer.bsky.social · 02/11/2023
I am in Boston giving a talk tomorrow at Harvard’s EconCS seminar (1:30pm). The talk is on genAI/ML technologies billed as "general-purpose". I'll discuss: which purposes, why and how? It's ongoing work with Hoda Heidari and Jon Kleinberg. HMU if you're around to meet, etc!
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Emily Tseng @emtseng.bsky.social · 08/10/2023
Recently migrated colleagues: I’m on the job market! I’ll have a PhD from Cornell IS in 2024. My lab will explore how tenets of social responsibility can be realized in computer science + engineering. I’m open to TT faculty positions and research-oriented industry roles. More about me: emtseng.me
emtseng.me
Emily Tseng
Emily studies computing and technology design.
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Deb Raji @rajiinio.bsky.social · 04/10/2023
Not sure who is on here these days, but I wrote a thing! Even for those determined to look far into the future, it's critically important to engage with what we're seeing now with AI & it's most urgent impacts. Too often, that complex reality is simply ignored! www.theatlantic.com/technology/a...
theatlantic.com
AI’s Present Matters More Than Its Imagined Future
Let’s not spend too much time daydreaming.
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Dr Abeba Birhane @abeba.blacksky.app · 29/09/2023
New paper from Pratyusha Ria Kalluri, William Agnew, Myra Cheng, Kentrell Owens, Luca Soldaini, & I! The Surveillance AI Pipeline: arxiv.org/abs/2309.15084 We unearth how computer vision research powers Surveillance AI through analysis of 3 decades of CV papers from CVPR & downstream patents 1
arxiv.org
The Surveillance AI Pipeline
A rapidly growing number of voices have argued that AI research, and computer vision in particular, is closely tied to mass surveillance. Yet the direct path from computer vision research to...
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Alexandre Klein @alexandreklein.bsky.social · 29/09/2023
(Call for applications) History of Science, pre-1850, Assistant Professor, Department of History, Cornell University histoiresante.blogspot.com/2023/09/post... #histSTM
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Andrew Selbst @aselbst.bsky.social · 20/09/2023
Talk of AI regulation has certainly ramped up this summer! In a paper now out in Penn Law Review, s010n.bsky.social and I explain why the intervention by the Federal Trade Commission to address AI discrimination would be both useful and legal. ssrn.com/abstract_id=... A 🧵from Solon and me… 1/
ssrn.com
Unfair Artificial Intelligence: How FTC Intervention Can Overcome the Limitations of Discrimination ...
The Federal Trade Commission has indicated that it intends to regulate discriminatory AI products and services. This is a welcome development, but its true sign
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