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Emma Pierson

@emmapierson.bsky.social
2K followers 210 following 52 posts

Assistant professor of CS at UC Berkeley, core faculty in Computational Precision Health. Developing ML methods to study health and inequality. "On the whole, though, I take the side of amazement." people.eecs.berkeley.edu/~emmapiers…

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Emma Pierson @emmapierson.bsky.social · 01/09/2026
Excited to join Transluce (transluce.org) part-time as a senior research fellow! (I'll remain full-time faculty at Berkeley.)
transluce.org
Transluce
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Emma Pierson @emmapierson.bsky.social · 28/08/2026
Paper: rdcu.be/fCyq6 Joint work led by @mfranchi.bsky.social and with @nkgarg.bsky.social and @wendyju.bsky.social!
rdcu.be
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Emma Pierson @emmapierson.bsky.social · 28/08/2026
New paper in Nature Communications! We show you can map out urban flooding by using vision-language models to detect floods in large-scale street scene datasets. In New York City, our method identifies flooded neighborhoods, home to 100k people, that current methods miss. 1/
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Emma Pierson @emmapierson.bsky.social · 22/06/2026
New piece in The Atlantic! We always hear that AI will cure cancer, and I would immediately benefit if it did. Still, I argue that racing ahead on generalist AI models creates unclear benefits for cancer that are outweighed by broader societal harms. Gift link: www.theatlantic.com/technology/2...
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Emma Pierson @emmapierson.bsky.social · 21/06/2026
My piece is not "pro-cancer". I have a very high risk of cancer, and have watched family members die of it. The piece argues that pushing AI forward at this speed creates unclear benefits for cancer that are outweighed by broader societal harms. Gift link - www.theatlantic.com/technology/2...
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Gabriel Agostini @gsagostini.bsky.social · 01/05/2026
Excited to see MIGRATE recognized in the IPUMS awards! Huge thanks to @emmapierson.bsky.social, @nkgarg.bsky.social, and our coauthors. Our work primarily aims to make spatiotemporal data more trustworthy and accessible to researchers, just like IPUMS. Read the paper to request data access!
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Marissa Kumar Gerchick @mkgerchick.bsky.social · 14/04/2026
The Tech Team at ACLU is hiring! We are looking for a Data Scientist with expertise in NLP and AI ethics to work on using language tech to support ACLU's mission. Come help us tackle questions about how AI systems can be carefully applied to support the public interest. www.aclu.org/careers/appl...
aclu.org
Careers at ACLU
Join our team! We’re looking for committed, passionate people for open roles at the ACLU.
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Emma Pierson @emmapierson.bsky.social · 14/04/2026
Our lab, within the Berkeley EECS department, is hiring a postdoc! More info and quick application form: forms.gle/4CcESe1TGFoo... Apply by May 1! Please reshare :)
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Emma Pierson @emmapierson.bsky.social · 08/04/2026
New paper: "In Your Own Words"! We: - develop a framework to identify themes in free-text survey data - show its benefits on a new dataset of how people self-describe their race, gender, and sexual orientation - release this data for research! See @jennyshwang.bsky.social's thread below :)
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Emma Pierson @emmapierson.bsky.social · 23/03/2026
We have a new piece in Nature Health led by @dmshanmugam.bsky.social, @sidhikabalachandar.bsky.social, and a wonderful team of coauthors on how to move towards a world in which race is not used in clinical algorithms!
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Emma Pierson @emmapierson.bsky.social · 18/03/2026
Congratulations to @gsagostini.bsky.social, whose recent Nature Comms paper releasing a fine-grained migration dataset (www.nature.com/articles/s41...) just won a student paper award at the American Association of Geographers Annual Meeting!
nature.com
Inferring fine-grained migration patterns across the United States - Nature Communications
This study releases a very high-resolution migration dataset that reveals trends that shape daily life: rising moves into high-income neighborhoods, racial gaps in upward mobility, and wildfire-driven...
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Emma Pierson @emmapierson.bsky.social · 26/02/2026
Our paper, "What's in My Human Feedback", received an oral presentation at ICLR! Our method automatically+interpretably identifies preferences in human feedback data; we use this to improve personalization + safety. Reach out if you have data/use cases to apply this to! arxiv.org/pdf/2510.26202
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Cornell Tech @cornelltech.bsky.social · 05/02/2026
New research is offering new insight on how Americans move — all the way to the neighborhood level. A new dataset, MIGRATE, maps annual moves with 4,600‑times more detail than standard public data, revealing patterns hidden in county‑level reporting: bit.ly/49XSD6w
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Emma Pierson @emmapierson.bsky.social · 05/02/2026
Paper: nature.com/articles/s4146 7-025-68019-2 Cornell Chronicle article: news.cornell.edu/stories/2026... Data access: migrate.tech.cornell.edu Joint work led by the geospatial wizard @gsagostini.bsky.social and with great coauthors Rachel Young, Maria Fitzpatrick, and @nkgarg.bsky.social!
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Emma Pierson @emmapierson.bsky.social · 05/02/2026
Now out in Nature Communications - we have released a migration dataset that is - 4000x more granular than existing public data - highly correlated with Census data - being used by >100 academic, govt, and non-profit teams all over the world See @gsagostini.bsky.social's thread!
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Emma Pierson @emmapierson.bsky.social · 04/02/2026
This work is led by the wonderful James Diao, with a great team of coauthors: @rajmovva.bsky.social, Lingwei Cheng, @kkado.bsky.social, Aashna Shah, @neil-r-powe.bsky.social, Kadija Ferryman, and Raj Manrai!
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Emma Pierson @emmapierson.bsky.social · 04/02/2026
See the paper - jamanetwork.com/journals/jam... - for more details, including sensitivity analyses, replication of prior gold-standard surveys, etc! Full survey questions, data, and code: github.com/epierson9/ra...
jamanetwork.com
Public Opinion on Use of Race in Clinical Algorithms
This survey study assesses public opinion and preferences among US adults regarding the use of race in clinical algorithms.
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Emma Pierson @emmapierson.bsky.social · 04/02/2026
Finding #4: Respondents were 4x more likely to be uncomfortable if clinicians used race without asking...yet <10% reported ever being told their race was used. This suggests the way we communicate about the use of race may not foster trust, and raises concerns in light of calls for transparency.
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Emma Pierson @emmapierson.bsky.social · 04/02/2026
Finding #3: Respondents were more comfortable with the use of race than with widely-proposed alternatives like zipcode or income. Said one respondent: "What does my paycheck have to do with a genetic mutation?" Don't assume switching to these factors will automatically improve trust.
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Emma Pierson @emmapierson.bsky.social · 04/02/2026
Finding #2: However, a substantial minority of respondents were not comfortable with use of race, and Black + Hispanic respondents were less comfortable than white and Asian respondents. This raises complex ethical and algorithmic questions about how to weigh these clashing preferences.
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Emma Pierson @emmapierson.bsky.social · 04/02/2026
Finding #1: Most respondents were comfortable with the use of race in at least some circumstances. This highlights a gap between calls to eliminate uses of race in medicine and public opinion.
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Emma Pierson @emmapierson.bsky.social · 04/02/2026
We have a new paper in JAMA Internal Medicine! Patient race is widely used in medical algorithms...but it's unclear how patients feel about this. We conduct the first nationally-representative YouGov survey to find out, producing four findings with practical clinical implications. 1/
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Emma Pierson @emmapierson.bsky.social · 20/01/2026
Thanks to Kara Manke at Berkeley News for this profile of our lab's recent work on fairer decision-making in healthcare and policing! news.berkeley.edu/2026/01/20/a...
news.berkeley.edu
AI has a bias problem. Can we build something smarter? - Berkeley News
UC Berkeley computer scientist Emma Pierson believes we can use AI to improve our healthcare and criminal justice systems — but only if we design these algorithms with an eye toward equality.
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Emma Pierson @emmapierson.bsky.social · 29/11/2025
Thanks - super-interesting, and actually very relevant to some other work we're doing as well. Will pass along!
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Emma Pierson @emmapierson.bsky.social · 24/11/2025
We're excited about applications of our test to other datasets that have 1) perceptions of race, gender, etc and 2) multiple observations of the same person. This work is led by the wonderful Nora Gera, in a great start to her PhD! Full paper: www.science.org/doi/epdf/10....
science.org
Testing for racial bias using inconsistent perceptions of race
You have to enable JavaScript in your browser's settings in order to use the eReader.
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Emma Pierson @emmapierson.bsky.social · 24/11/2025
See the paper for many robustness checks and discussion of nuances! Our finding persists when using alternate outcomes, statistical models, subsets of the data, and controls satisfying the criteria above. 5/
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Emma Pierson @emmapierson.bsky.social · 24/11/2025
A benefit of our test is that it doesn't require us to control for all factors legitimately influencing searches. We only have to control for things that influence both searches and perceived race, vary for the same person across stops, and don't themselves suggest bias. 4/
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Emma Pierson @emmapierson.bsky.social · 24/11/2025
9% of drivers stopped multiple times have inconsistently perceived race across different stops - most perceived as both white + Hispanic. When perceived as Hispanic, the same driver is likelier to be searched/arrested. This gap is substantial (24% of overall search rate). 3/
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Emma Pierson @emmapierson.bsky.social · 24/11/2025
Tests for racial bias often compare how two people of different races are treated. But two people typically differ in many ways besides race. So instead of comparing two different people, we study the *same person over time*, as perceptions of their race change. 2/
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Emma Pierson @emmapierson.bsky.social · 24/11/2025
We have a new paper in Science Advances proposing a simple test for bias: Is the same person treated differently when their race is perceived differently? Specifically, we study: is the same driver likelier to be searched by police when they are perceived as Hispanic rather than white? 1/
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Divya Shanmugam @dmshanmugam.bsky.social · 17/10/2025
New #NeurIPS2025 paper: how should we evaluate machine learning models without a large, labeled dataset? We introduce Semi-Supervised Model Evaluation (SSME), which uses labeled and unlabeled data to estimate performance! We find SSME is far more accurate than standard methods.
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Erica Chiang @ericachiang.bsky.social · 14/10/2025
selfishly i wish we could keep divya in our lab forever but i guess it would be a disservice to the rest of the world 😅 she’s been such a wonderful mentor to me—i’ve learned a lot from how thoughtful, creative, and knowledgeable she is about everything. she’s also super funny and amazing at baking 🤭
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Emma Pierson @emmapierson.bsky.social · 14/10/2025
Meeting Divya 5 years ago was one of the biggest strokes of luck in my faculty career - she is a brilliant scientist who has been foundational to so many of our lab's projects, and any institution would be lucky to hire her.
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Emma Pierson @emmapierson.bsky.social · 22/08/2025
Apply here - aprecruit.berkeley.edu/JPF05028 by 11/15, but review of applications is ongoing so sooner is better! (Application deadline currently says 9/15 but will be extended).
aprecruit.berkeley.edu
Postdoctoral Employee - Artificial Intelligence - Electrical Engineering and Computer Sciences Department
University of California, Berkeley is hiring. Apply now!
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Emma Pierson @emmapierson.bsky.social · 22/08/2025
Broad project areas include: 1) language modelling methods for scientific discovery (building on our recent work - arxiv.org/abs/2502.04382) 2) using language models to support equity (ai.nejm.org/doi/full/10....) both in collaboration with health+social scientists. 2/3
arxiv.org
Sparse Autoencoders for Hypothesis Generation
We describe HypotheSAEs, a general method to hypothesize interpretable relationships between text data (e.g., headlines) and a target variable (e.g., clicks). HypotheSAEs has three steps: (1) train a ...
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Emma Pierson @emmapierson.bsky.social · 22/08/2025
🚨 New postdoc position in our lab at Berkeley EECS! 🚨 (please reshare) We seek applicants with experience in language modeling who are excited about high-impact applications in the health and social sciences! More info in thread 1/3
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Raj Movva @rajmovva.bsky.social · 05/08/2025
📢New POSITION PAPER: Use Sparse Autoencoders to Discover Unknown Concepts, Not to Act on Known Concepts Despite recent results, SAEs aren't dead! They can still be useful to mech interp, and also much more broadly: across FAccT, computational social science, and ML4H. 🧵
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Emma Pierson @emmapierson.bsky.social · 07/07/2025
SF fog coming up to swallow us in time lapse.
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Emma Pierson @emmapierson.bsky.social · 27/06/2025
Honored to win a #CHIL2025 best paper award for our work modeling inequality in disease progression, led by @ericachiang.bsky.social! To the NIH: health inequality remains a vital topic to support the health of all Americans. As we prove, failing to account for it biases estimates for everyone.
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Allison Koenecke @allisonkoe.bsky.social · 23/06/2025
For folks at @facct.bsky.social, our very own @cornellbowers.bsky.social student @emmharv.bsky.social will present the Best-Paper-Award-winning work she led on Wednesday at 10:45 AM in the "Audit and Evaluation Approaches" session! In the meantime, 🧵 below and 🔗 here: arxiv.org/abs/2506.04419 !
arxiv.org
A Framework for Auditing Chatbots for Dialect-Based Quality-of-Service Harms
Increasingly, individuals who engage in online activities are expected to interact with large language model (LLM)-based chatbots. Prior work has shown that LLMs can display dialect bias, which occurs...
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molly conger @socialistdogmom.bsky.social · 14/06/2025
assassinations, handcuffing a senator at press conference, marines detaining a civilian, and a military parade for the president’s birthday. rough week for democracy.
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Divya Shanmugam @dmshanmugam.bsky.social · 14/06/2025
and... here is the actual GIF 🙈
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Emma Pierson @emmapierson.bsky.social · 01/05/2025
The first paper of @ericachiang.bsky.social's PhD, just accepted at #CHIL2025, proposes a model of disease progression which estimates and accounts for 3 types of health disparities to more accurately measure disease severity. See her full thread below!
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Emma Pierson @emmapierson.bsky.social · 26/04/2025
Thanks, Megan!! This is kind :) hope you’re doing well.
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Emma Pierson @emmapierson.bsky.social · 25/04/2025
The US government recently flagged my scientific grant in its "woke DEI database". Many people have asked me what I will do. My answer today in Nature. We will not be cowed. We will keep using AI to build a fairer, healthier world. www.nature.com/articles/d41...
nature.com
My ‘woke DEI’ grant has been flagged for scrutiny. Where do I go from here?
My work in making artificial intelligence fair has been noticed by US officials intent on ending ‘class warfare propaganda’.
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Emma Pierson @emmapierson.bsky.social · 24/04/2025
A pleasure to join the Tech Policy Press podcast with @natematias.bsky.social, @geomblog.bsky.social, and @justinhendrix.bsky.social to defend the consensus that AI bias is an important concern.
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Emma Pierson @emmapierson.bsky.social · 02/04/2025
Lab had dogathon! Seminal dog discoveries ensued.
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Emma Pierson @emmapierson.bsky.social · 28/03/2025
This work is led by @gsagostini.bsky.social, who gets more excited about geospatial data than anyone I've ever met, and with Rachel Young, Maria Fitzpatrick, and @nkgarg.bsky.social. Paper: arxiv.org/abs/2503.20989 Website (and data): migrate.tech.cornell.edu Thread: bsky.app/profile/gsag...
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Emma Pierson @emmapierson.bsky.social · 28/03/2025
Migration data is critical in the health, environmental, and social sciences. We're releasing a new dataset, MIGRATE: annual flows between 47 billion pairs of US Census areas. MIGRATE is: - 4600x more granular than existing public data - highly correlated with external ground-truth data 1/2
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Raj Movva @rajmovva.bsky.social · 18/03/2025
💡New preprint & Python package: We use sparse autoencoders to generate hypotheses from large text datasets. Our method, HypotheSAEs, produces interpretable text features that predict a target variable, e.g. features in news headlines that predict engagement. 🧵1/
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