Demographic Dialectal Variation in Social Media: A Case Study of African-American English. - Su Lin Blodgett; Lisa Green; Brendan T. O'Connor 001 (EMNLP, 2016)

Visualizing textual models with in-text and word-as-pixel highlighting. - Abram Handler; Su Lin Blodgett; Brendan O'Connor 001 (CoRR, 2016)

A Dataset and Classifier for Recognizing Social Media English. - Su Lin Blodgett; Johnny Wei; Brendan O'Connor 001 (NUT@EMNLP, 2017)

Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English. - Su Lin Blodgett; Brendan O'Connor 001 (CoRR, 2017)

Twitter Universal Dependency Parsing for African-American and Mainstream American English. - Su Lin Blodgett; Johnny Wei; Brendan T. O'Connor 001 (ACL (1), 2018)

Monte Carlo Syntax Marginals for Exploring and Using Dependency Parses. - Katherine A. Keith; Su Lin Blodgett; Brendan T. O'Connor 001 (NAACL-HLT, 2018)

Language (Technology) is Power: A Critical Survey of "Bias" in NLP. - Su Lin Blodgett; Solon Barocas; Hal Daumé III; Hanna M. Wallach (ACL, 2020)

The meaning and measurement of bias: lessons from natural language processing. - Abigail Z. Jacobs; Su Lin Blodgett; Solon Barocas; Hal Daumé III; Hanna M. Wallach (FAT*, 2020)

Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets. - Su Lin Blodgett; Gilsinia Lopez; Alexandra Olteanu; Robert Sim; Hanna M. Wallach (ACL/IJCNLP (1), 2021)

A Survey of Race, Racism, and Anti-Racism in NLP. - Anjalie Field; Su Lin Blodgett; Zeerak Waseem; Yulia Tsvetkov (ACL/IJCNLP (1), 2021)

How to Write a Bias Statement: Recommendations for Submissions to the Workshop on Gender Bias in NLP. - Christian Hardmeier; Marta R. Costa-jussà; Kellie Webster; Will Radford; Su Lin Blodgett (CoRR, 2021)

Confronting Structural Inequities in AI for Education. - Michael Madaio; Su Lin Blodgett; Elijah Mayfield; Ezekiel Dixon-Román (CoRR, 2021)

Risks of AI Foundation Models in Education. - Su Lin Blodgett; Michael Madaio (CoRR, 2021)

Examining Responsibility and Deliberation in AI Impact Statements and Ethics Reviews. - David Liu 006; Priyanka Nanayakkara; Sarah Ariyan Sakha; Grace Abuhamad; Su Lin Blodgett; Nicholas Diakopoulos; Jessica R. Hullman; Tina Eliassi-Rad (AIES, 2022)

Responsible Language Technologies: Foreseeing and Mitigating Harms. - Su Lin Blodgett; Q. Vera Liao; Alexandra Olteanu; Rada Mihalcea; Michael J. Muller; Morgan Klaus Scheuerman; Chenhao Tan; Qian Yang 004 (CHI Extended Abstracts, 2022)

Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications. - Kaitlyn Zhou; Su Lin Blodgett; Adam Trischler; Hal Daumé III; Kaheer Suleman; Alexandra Olteanu (NAACL-HLT, 2022)

Examining Political Rhetoric with Epistemic Stance Detection. - Ankita Gupta; Su Lin Blodgett; Justin H. Gross; Brendan T. O'Connor 001 (CoRR, 2022)

Taxonomizing and Measuring Representational Harms: A Look at Image Tagging. - Jared Katzman; Angelina Wang; Morgan Klaus Scheuerman; Su Lin Blodgett; Kristen Laird; Hanna M. Wallach; Solon Barocas (AAAI, 2023)

FairPrism: Evaluating Fairness-Related Harms in Text Generation. - Eve Fleisig; Aubrie Amstutz; Chad Atalla; Su Lin Blodgett; Hal Daumé III; Alexandra Olteanu; Emily Sheng; Dan Vann; Hanna M. Wallach (ACL (1), 2023)

This prompt is measuring extlessmask textgreater: evaluating bias evaluation in language models. - Seraphina Goldfarb-Tarrant; Eddie Ungless; Esma Balkir; Su Lin Blodgett (ACL (Findings), 2023)

It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance. - Arjun Subramonian; Xingdi Yuan; Hal Daumé III; Su Lin Blodgett (ACL (Findings), 2023)

Responsible AI Considerations in Text Summarization Research: A Review of Current Practices. - Yu Lu Liu; Meng Cao 003; Su Lin Blodgett; Jackie Chi Kit Cheung; Alexandra Olteanu; Adam Trischler (EMNLP (Findings), 2023)

Fairness and Sequential Decision Making: Limits, Lessons, and Opportunities. - Samer B. Nashed; Justin Svegliato; Su Lin Blodgett (CoRR, 2023)

This Prompt is Measuring : Evaluating Bias Evaluation in Language Models. - Seraphina Goldfarb-Tarrant; Eddie Ungless; Esma Balkir; Su Lin Blodgett (CoRR, 2023)

Evaluating the Social Impact of Generative AI Systems in Systems and Society. - Irene Solaiman; Zeerak Talat; William Agnew; Lama Ahmad; Dylan K. Baker; Su Lin Blodgett; Hal Daumé III; Jesse Dodge; Ellie Evans; Sara Hooker; Yacine Jernite; Alexandra Sasha Luccioni; et al. (CoRR, 2023)

"One-size-fits-all"? Observations and Expectations of NLG Systems Across Identity-Related Language Features. - Li Lucy; Su Lin Blodgett; Milad Shokouhi; Hanna M. Wallach; Alexandra Olteanu (CoRR, 2023)

Understanding the Impacts of Language Technologies' Performance Disparities on African American Language Speakers. - Jay Cunningham; Su Lin Blodgett; Michael Madaio; Hal Daumé III; Christina Harrington; Hanna M. Wallach (ACL (Findings), 2024)

ECBD: Evidence-Centered Benchmark Design for NLP. - Yu Lu Liu; Su Lin Blodgett; Jackie C. K. Cheung; Vera Liao; Alexandra Olteanu; Ziang Xiao (ACL (1), 2024)

Metrics for What, Metrics for Whom: Assessing Actionability of Bias Evaluation Metrics in NLP. - Pieter Delobelle; Giuseppe Attanasio; Debora Nozza; Su Lin Blodgett; Zeerak Talat (EMNLP, 2024)

The Perspectivist Paradigm Shift: Assumptions and Challenges of Capturing Human Labels. - Eve Fleisig; Su Lin Blodgett; Dan Klein 001; Zeerak Talat (NAACL-HLT, 2024)

"One-Size-Fits-All"? Examining Expectations around What Constitute "Fair" or "Good" NLG System Behaviors. - Li Lucy; Su Lin Blodgett; Milad Shokouhi; Hanna M. Wallach; Alexandra Olteanu (NAACL-HLT, 2024)

Measuring machine learning harms from stereotypes: requires understanding who is being harmed by which errors in what ways. - Angelina Wang; Xuechunzi Bai; Solon Barocas; Su Lin Blodgett (CoRR, 2024)

"I Am the One and Only, Your Cyber BFF": Understanding the Impact of GenAI Requires Understanding the Impact of Anthropomorphic AI. - Myra Cheng; Alicia DeVrio; Lisa Egede; Su Lin Blodgett; Alexandra Olteanu (CoRR, 2024)

Evaluating Generative AI Systems is a Social Science Measurement Challenge. - Hanna M. Wallach; Meera A. Desai; Nicholas Pangakis; A. Feder Cooper; Angelina Wang; Solon Barocas; Alexandra Chouldechova; Chad Atalla; Su Lin Blodgett; Emily Corvi; P. Alex Dow; Jean Garcia-Gathright; et al. (CoRR, 2024)

Gaps Between Research and Practice When Measuring Representational Harms Caused by LLM-Based Systems. - Emma Harvey; Emily Sheng; Su Lin Blodgett; Alexandra Chouldechova; Jean Garcia-Gathright; Alexandra Olteanu; Hanna M. Wallach (CoRR, 2024)

Dehumanizing Machines: Mitigating Anthropomorphic Behaviors in Text Generation Systems. - Myra Cheng; Su Lin Blodgett; Alicia DeVrio; Lisa Egede; Alexandra Olteanu (ACL (1), 2025)

Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems. - Emma Harvey; Emily Sheng; Su Lin Blodgett; Alexandra Chouldechova; Jean Garcia-Gathright; Alexandra Olteanu; Hanna M. Wallach (ACL (Findings), 2025)

A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies. - Alicia DeVrio; Myra Cheng; Lisa Egede; Alexandra Olteanu; Su Lin Blodgett (CHI, 2025)

Measuring Machine Learning Harms from Stereotypes Requires Understanding Who Is Harmed by Which Errors in What Ways. - Angelina Wang; Xuechunzi Bai; Solon Barocas; Su Lin Blodgett (FAccT, 2025)

'It was 80% me, 20% AI': Seeking Authenticity in Co-Writing with Large Language Models. - Angel Hsing-Chi Hwang; Q. Vera Liao; Su Lin Blodgett; Alexandra Olteanu; Adam Trischler (Proc. ACM Hum. Comput. Interact., 2025)

Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge. - Hanna M. Wallach; Meera A. Desai; A. Feder Cooper; Angelina Wang; Chad Atalla; Solon Barocas; Su Lin Blodgett; Alexandra Chouldechova; Emily Corvi; P. Alex Dow; Jean Garcia-Gathright; Alexandra Olteanu; et al. (CoRR, 2025)

AI Automatons: AI Systems Intended to Imitate Humans. - Alexandra Olteanu; Solon Barocas; Su Lin Blodgett; Lisa Egede; Alicia DeVrio; Myra Cheng (CoRR, 2025)

Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor. - Alexandra Olteanu; Su Lin Blodgett; Agathe Balayn; Angelina Wang; Fernando Diaz 001; Flávio du Pin Calmon; Margaret Mitchell; Michael D. Ekstrand; Reuben Binns; Solon Barocas (CoRR, 2025)