Lightnews — Scholar-powered news

Reposted by Emma Harvey

Queer in AI @queerinai.com · 1d

We are launching our Graduate School Application Financial Aid Program (www.queerinai.com/grad-app-aid) for 2025-2026. We’ll give up to $750 per person to LGBTQIA+ STEM scholars applying to graduate programs. Apply at openreview.net/group?id=Que.... 1/5

Grad App Aid — Queer in AI

www.queerinai.com

1 9 6

Reposted by Emma Harvey

Tzu-Sheng Kuo 郭子生 @tskuo.bsky.social · 15d

🌟 If you’re applying to CMU SCS PhD programs, and come from a background that would bring additional dimensions to the CMU community, our PhD students are here to help!

Apply to the Graduate Applicant Support Program by Oct 13 to receive feedback on your application materials:

Carnegie Mellon University School of Computer Science Graduate Application Support Program. Apply by October 13, 2025.

1 5 6

Reposted by Emma Harvey

A. Feder Cooper @afedercooper.bsky.social · 24d

15 days left to submit to the CSLaw '26 main track! (archival and non-archival)!

A. Feder Cooper @afedercooper.bsky.social · Aug 8

The CFP for ACM CSLaw '26 is up! Deadline for main-track papers (archival and non-archival) is September 30!

computersciencelaw.org/2026

2026 - ACM Symposium on Computer Science & Law

CS&Law 2026 5th ACM Symposium on Computer Science and Law March 3–5, 2026 Berkeley, California Computing, software, and the Internet…

computersciencelaw.org

4 6

Reposted by Emma Harvey

Hauke Sandhaus @sandhaus.bsky.social · Sep 5

Join us for NYC Privacy Day 2025 at Cornell Tech, hosted by DLI @nissenbaum.bsky.social and SETS @mantzarlis.com.
We have a great selection of speakers and alongside
talks, we’ll feature student posters + demos.

🔗 Details, registration, and poster submission: dli.tech.cornell.edu/nyc-privacy-...

NYC Privacy Day 2025 | Cornell Tech

NYC Privacy Day hosted at Cornell Tech

dli.tech.cornell.edu

2 2

Reposted by Emma Harvey

travis lloyd (træve) @travislloydphd.bsky.social · Sep 3

I'm at Seattle 4S! I'll be part of the "Risks of 'Social Model Collapse' in the Face of Scientific and Technological Advances" panel Friday morning, discussing online community governance of AI-generated content. Would love to meet others studying AI's impact on the info ecosystem!
#STS #4S

1 2 9

Reposted by Emma Harvey

Gabriel Agostini @gsagostini.bsky.social · Sep 3

Are you a researcher using computational methods to understand cities?

@mfranchi.bsky.social @jennahgosciak.bsky.social and I organize an EAAMO Bridges working group on Urban Data Science and we are looking for new members!

Fill the interest form on our page: urban-data-science-eaamo.github.io

Urban Data Science & Equitable Cities | EAAMO Bridges

EAAMO Bridges Urban Data Science & Equitable Cities working group: biweekly talks, paper studies, and workshops on computational urban data analysis to explore and address inequities.

urban-data-science-eaamo.github.io

1 7 7

Reposted by Emma Harvey

Paper Skygest Team @paper-feed.bsky.social · Aug 19

**Please repost** If you're enjoying Paper Skygest -- our personalized feed of academic content on Bluesky -- we'd appreciate you reposting this! We’ve found that the most effective way for us to reach new users and communities is through users sharing it with their network

1 41 38

Reposted by Emma Harvey

Adam Visokay @avisokay.bsky.social · Jul 27

This is such a great paper and really helps to emphasize how data under specification in ML systems bias our understanding and decision making. Especially in inequitable resource scarce settings. Thanks for sharing @emmharv.bsky.social !

Emma Harvey @emmharv.bsky.social · Jul 14

👯 Allocation Multiplicity: Evaluating the Promises of the Rashomon Set by Jain et al. (incl. @kathleencreel.bsky.social) argues that allocation (vs. model) multiplicity should be seen as a pathway for reducing discrimination, homogenization, and arbitrariness in decision-making problems.

Screenshot of paper title and author list:

Allocation Multiplicity: Evaluating the Promises of the Rashomon Set
Shomik Jain, Margaret Wang, Kathleen Creel, Ashia Wilson

1 4

Reposted by Emma Harvey

Deb Raji @rajiinio.bsky.social · Jul 26

Emma has such good research taste :)

Given the sheer scale of these events, its really helpful to see what caught people's eye at these conferences...

Emma Harvey @emmharv.bsky.social · Jul 14

After having such a great time at #CHI2025 and #FAccT2025, I wanted to share some of my favorite recent papers here!

I'll aim to post new ones throughout the summer and will tag all the authors I can find on Bsky. Please feel welcome to chime in with thoughts / paper recs / etc.!!

🧵⬇️:

2 9

Emma Harvey @emmharv.bsky.social · Jul 24

What's super cool to me about this paper is that it does a longitudinal analysis - so many audit studies stick to a single point in time, and this paper is a great demonstration that the data available to you at that time will inevitably impact your measurements.

🔗: dl.acm.org/doi/10.1145/...

Bias Delayed is Bias Denied? Assessing the Effect of Reporting Delays on Disparity Assessments | Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency

You will be notified whenever a record that you have chosen has been cited.

dl.acm.org

2

Emma Harvey @emmharv.bsky.social · Jul 24

The authors find that delays in reporting patient demographics are the norm (for >50% of patients, race is reported >60 days after other details like DOB). These delays obfuscate measurement of health outcomes and health disparities, and techniques like imputing race do not improve measurement.

1 2

Emma Harvey @emmharv.bsky.social · Jul 24

⏳ Bias Delayed is Bias Denied? Assessing the Effect of Reporting Delays on Disparity Assessments by @jennahgosciak.bsky.social and @aparnabee.bsky.social et al. (incl. @allisonkoe.bsky.social @marzyehghassemi.bsky.social) analyzes how missing demographic data impacts estimates of health disparities.

Screenshot of paper title and author list:

Bias Delayed is Bias Denied? Assessing the Effect of Reporting Delays on Disparity Assessments
Jennah Gosciak, Aparna Balagopalan, Derek Ouyang, Allison Koenecke, Marzyeh Ghassemi, Daniel E. Ho

1 3

Emma Harvey @emmharv.bsky.social · Jul 24

I love how this paper emphasizes that evaluation != accountability and recommends steps towards accountability: ensuring that tools are open, valid, and reliable; focusing on tools to support participatory methods; and ensuring auditors are protected from retaliation.

🔗: dl.acm.org/doi/full/10....

Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling | Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

You will be notified whenever a record that you have chosen has been cited.

dl.acm.org

2 2

Emma Harvey @emmharv.bsky.social · Jul 24

The authors analyze 435(!) tools, finding that most focus on evaluation – but tools for other aspects of AI audits, like harms discovery, communicating audit results, and advocating for change, are less common. Further, while many tools are freely available, auditors often struggle to use them.

1 2

Emma Harvey @emmharv.bsky.social · Jul 24

Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling by @victorojewale.bsky.social @rbsteed.com @briana-v.bsky.social @abeba.bsky.social @rajiinio.bsky.social compares the landscape of AI audit tools (tools.auditing-ai.com) to the actual needs of AI auditors.

Screenshot of paper title and author list:

Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling
Victor Ojewale, Ryan Steed, Briana Vecchione, Abeba Birhane, Inioluwa Deborah Raji

1 4 23

Emma Harvey @emmharv.bsky.social · Jul 24

This work won a 🏆Best Paper Award🏆 at FAccT! I think it's a fantastic example of an external audit that not only identifies a problem but also provides concrete steps towards a solution.

🔗: dl.acm.org/doi/10.1145/...

External Evaluation of Discrimination Mitigation Efforts in Meta's Ad Delivery | Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency

dl.acm.org

1 2

Emma Harvey @emmharv.bsky.social · Jul 24

The authors show that the external review established by the settlement is insufficient to guarantee that Meta is actually reducing discrimination in ad delivery (as opposed to adversarially complying by showing the same ad repeatedly to one person or applying VRS only to small ad campaigns).

1 2

Emma Harvey @emmharv.bsky.social · Jul 24

📱 External Evaluation of Discrimination Mitigation Efforts in Meta's Ad Delivery by Imana et al. audits VRS (Meta’s process for reducing bias in ad delivery as part of a settlement with DOJ), and finds VRS reduces demographic differences in ad audience – but also reduces reach and increases cost.

Screenshot of paper title and author list:

External Evaluation of Discrimination Mitigation Efforts in Meta’s Ad Delivery
Basileal Imana, Zeyu Shen, John Heidemann, Aleksandra Korolova

1 2

Emma Harvey @emmharv.bsky.social · Jul 24

I thought this paper was really interesting, and I particularly appreciated the authors' point that models can make decisions that are "consistent" but still "arbitrary" if model selection is not done in a principled way!

🔗: dl.acm.org/doi/10.1145/...

dl.acm.org

1 2

Emma Harvey @emmharv.bsky.social · Jul 24

The authors propose that opportunity pluralism is most important in domains that involve normative or high-uncertainty decisions, or where decision-subject can choose among multiple decision-makers. Even in those domains, the authors argue that individual models should still be consistent.

1 2

Emma Harvey @emmharv.bsky.social · Jul 24

🎲 Consistently Arbitrary or Arbitrarily Consistent: Navigating the Tensions Between Homogenization and Multiplicity in Algorithmic Decision-Making by Gur-Arieh and Lee explores the competing desires for consistency in decision-making models and opportunity pluralism in decision-making ecosystems.

Screenshot of paper title and author list:

Consistently Arbitrary or Arbitrarily Consistent: Navigating the Tensions Between Homogenization and Multiplicity in Algorithmic Decision-Making
Shira Gur-Arieh, Christina Lee

1 2

Reposted by Emma Harvey

Allison Koenecke @allisonkoe.bsky.social · Jul 23

Check out our work at @ic2s2.bsky.social this afternoon during the Communication & Cooperation II session!

Emma Harvey @emmharv.bsky.social · Jun 23

I am so excited to be in 🇬🇷Athens🇬🇷 to present "A Framework for Auditing Chatbots for Dialect-Based Quality-of-Service Harms" by me, @kizilcec.bsky.social, and @allisonkoe.bsky.social, at #FAccT2025!!

🔗: arxiv.org/pdf/2506.04419

A screenshot of our paper's:

Title: A Framework for Auditing Chatbots for Dialect-Based Quality-of-Service Harms
Authors: Emma Harvey, Rene Kizilcec, Allison Koenecke
Abstract: 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 when they produce harmful responses when prompted with text written in minoritized dialects. However, whether and how this bias propagates to systems built on top of LLMs, such as chatbots, is still unclear. We conduct a review of existing approaches for auditing LLMs for dialect bias and show that they cannot be straightforwardly adapted to audit LLM-based chatbots due to issues of substantive and ecological validity. To address this, we present a framework for auditing LLM-based chatbots for dialect bias by measuring the extent to which they produce quality-of-service harms, which occur when systems do not work equally well for different people. Our framework has three key characteristics that make it useful in practice. First, by leveraging dynamically generated instead of pre-existing text, our framework enables testing over any dialect, facilitates multi-turn conversations, and represents how users are likely to interact with chatbots in the real world. Second, by measuring quality-of-service harms, our framework aligns audit results with the real-world outcomes of chatbot use. Third, our framework requires only query access to an LLM-based chatbot, meaning that it can be leveraged equally effectively by internal auditors, external auditors, and even individual users in order to promote accountability. To demonstrate the efficacy of our framework, we conduct a case study audit of Amazon Rufus, a widely-used LLM-based chatbot in the customer service domain. Our results reveal that Rufus produces lower-quality responses to prompts written in minoritized English dialects.

1 8

Reposted by Emma Harvey

ACL @aclmeeting.bsky.social · Jul 22

🥳 🎉 ❤️ The ACL 2025 Proceedings are live on the ACL Anthology 🥰 !
We’re thrilled to pre-celebrate the incredible research 📚 ✨ that will be presented starting Monday next week in Vienna 🇦🇹 !
Start exploring 👉 aclanthology.org/events/acl-2...
#NLProc #ACL2025NLP #ACLAnthology

Annual Meeting of the Association for Computational Linguistics (2025) - ACL Anthology

pdf bibProceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)Wanxiang Che | Joyce Nabende | Ekaterina Shutova | Mohammad Taher Pilehvar

aclanthology.org

19 57

Emma Harvey @emmharv.bsky.social · Jul 21

I broke the thread 😅

Emma Harvey @emmharv.bsky.social · Jul 21

🚗 Not Even Nice Work If You Can Get It; A Longitudinal Study of Uber's Algorithmic Pay and Pricing by @rdbinns.bsky.social @jmlstein.bsky.social et al. (incl. @emax.bsky.social) audits Uber's pay practices, focusing on the shift to paying drivers a "dynamic" (opaque, unpredictable) share of fare.

Screenshot of paper title and author list:

Not Even Nice Work If You Can Get It; A Longitudinal Study of Uber's Algorithmic Pay and Pricing
Reuben Binns, Jake Stein, Siddhartha Datta, Max Van Kleek, Nigel Shadbolt

1 2

Emma Harvey @emmharv.bsky.social · Jul 21

My favorite part of this paper was the point that "synthetic data creates distance between individuals and the data...derived from [them]." Synthetic data is often considered privacy-preserving, but it can actually reduce opportunities for participation and redress!

🔗: dl.acm.org/doi/10.1145/...

Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline | Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency

dl.acm.org

1