ACM FAccT 2024 Accepted Papers

The research program of ACM FAccT solicits academic work from a wide variety of disciplines, including computer science, statistics, law, social sciences, the humanities, and policy, and multidisciplinary scholarship on fairness, accountability, and transparency in computational systems (broadly construed). We welcome contributions that consider a wide range of technical, policy, societal, and normative issues. These include, but are not limited to, issues of structural and individual (in)equity, justice in systems and policy; the material, environmental, and economic effects of computational systems.

List of accepted papers

Classification Metrics for Image Explanations: Towards Building Reliable XAI-Evaluations

Benjamin Fresz, University of Stuttgart, Lena Lena Lörcher,University of Stuttgart, Marco Huber, University of Stuttgart

Designing Long-term Group Fair Policies in Dynamical Systems

Miriam Rateike, Saarland University, Isabel Valera, Saarland University, Patrick Forrel; Saarland University

Learning Fairness from Demonstrations via Inverse Reinforcement Learning

Jack Blandin, University of Illinois at Chicago, Ian A. Kash, University of Illinois at Chicago

Using Property Elicitation to Understand the Impacts of Fai rness Regularizers

Jessie Finocchiaro, Harvard University

Beyond Individual Accountability: (Re-)Asserting Democratic Control of AI

Daniel James Bogiatzis-Gibbons, Birkbeck College

Power Hungry Processing: Watts Driving the Cost of AI Deployment?

Sasha Luccioni, Hugging Face, Yacine Jernite, Hugging Face, Emma Strubell, Carnegie Mellon, Allen AI Institute

Data Feminism for AI

Lauren Klein, Emory University, Catherine D'Ignazio, MIT

Reliability Gaps Between Groups in COMPAS Dataset

Tim Räz, University of Bern

Mapping AI ethics: a meso-scale analysis of its charters and manifestos

Mélanie Gornet, Télécom Paris, Simon Delarue, Télécom Paris, Maria Boritchev, Télécom Paris, Tiphaine Viard, Télécom Paris

''I Searched for a Religious Song in Amharic and Got Sexual Content Instead:'' Investigating Online Harm in Low-Resourced Languages on YouTube.

Hellina Hailu Nigatu, UC Berkeley, Inioluwa Deborah Raji, UC Berkeley

Why is "Problems" Predictive of Positive Sentiment? A Case Study of Explaining Unintuitive Features in Sentiment Classification

Jiaming Qu, UNC Chapel Hill, Jaime Arguello, UNC Chapel Hill, Yue Wang, UNC Chapel Hill

Regulating AI-Based Remote Biometric Identification. Investigating the Public Demand for Bans, Audits, and Public Database Registrations

Kimon Kieslich, University of Amsterdam<, Marco Lünich, Heinrich Heine University

AI Art is Theft: Labour, Extraction, and Exploitation: Or, On the Dangers of Stochastic Pollocks ��

Trystan S. Goetze, Cornell University

Algorithmic Pluralism: A Structural Approach To Equal Opportunity

Shomik Jain, MIT; Vinith Suriyakumar, MIT; Kathleen Creel, Northeastern University; Ashia Wilson, MIT

A Framework for Exploring the Consequences of AI-Mediated Enterprise Knowledge Access and Identifying Risks to Workers

Anna Gausen, Imperial College London; Bhaskar Mitra, Microsoft Research; Siân Lindley, Microsoft Research

A Decision Theoretic Framework for Measuring AI Reliance

Ziyang Guo, Northwestern University; Yifan Wu, Northwestern University; Jason D. Hartline, Northwestern University; Jessica Hullman, Northwestern University

Ethnic Classifications in Algorithmic Fairness: Concepts, Measures and Implications in Practice

Sofia Jaime, University of California; Christoph Kern, LMU Munich

Algorithmic Reproductive Justice

Jasmine Fledderjohann, Lancaster University; Bran Knowles, Lancaster University; Esmorie Miller, Lancaster University

"Like rearranging deck chairs on the Titanic"? Feasibility, Fairness, and Ethical Concerns of a Citizen Carbon Budget for Reducing CO2 Emissions

Gisela Reyes-Cruz, University of Nottingham; Peter Craigon, University of Nottingham; Anna-Maria Piskopani, University of Nottingham; Liz Dowthwaite, University of Nottingham; Yang Lu, York St John University; Justyna Lisinska, King's College London; Elnaz Shafipour, University of Southampton; Sebastian Stein, University of Southampton; Joel Fischer, University of Nottingham

A preprocessing Shapley value-based approach to detect relevant and disparity prone features in machine learning

Guilherme Dean Pelegrina, University of Campinas; Miguel Couceiro, Université de Lorraine; Leonardo Tomazeli Duarte, University of Campinas

Failing Our Youngest: On the Biases, Pitfalls, and Risks in a Decision Support Algorithm Used for Child Protection

Therese Moreau, IT University of Copenhagen; Roberta Sinatra, University of Copenhagen; Vedran Sekara, IT University of Copenhagen

Misgendered During Moderation: How Transgender Bodies Make Visible Cisnormative Content Moderation Policies and Enforcement in a Meta Oversight Board Case

Samuel Mayworm, University of Michigan; Kendra Albert, Harvard University; Oliver L. Haimson, University of Michigan

A structured regression approach for evaluating model performance across intersectional subgroups

Christine Herlihy, University of Maryland; Kimberly Truong, Oregon State University; Alexandra Chouldechova, Microsoft Research; Miroslav Dudík, Microsoft Research

Trans-centered moderation: Trans technology creators and centering transness in platform and community governance

Hibby Thach, University of Michigan; Samuel Mayworm, University of Michigan; Michaelanne Thomas, University of Michigan; Oliver L. Haimson, University of Michigan

The Fall of an Algorithm: Characterizing the Dynamics Toward Abandonment

Nari Johnson, Carnegie Mellon University; Sanika Moharana, Carnegie Mellon University; Christina Harrington, Carnegie Mellon University; Nazanin Andalibi, University of Michigan; Hoda Heidari, Carnegie Mellon University; Motahhare Eslami, Carnegie Mellon University

Not My Voice! A Taxonomy of Ethical and Safety Harms of Speech Generators

Wiebke Hutiri, Sony AI; Orestis Papakyriakopoulos, Sony AI; Alice Xiang, Sony AI

Operationalizing the Search for Less Discriminatory Alternatives in Fair Lending

Talia B. Gillis, Columbia University; Vitaly Meursault, Federal Reserve Bank of Philadelphia Research Department; Berk Ustun, Halicioglu Data Science Institute, UCSD

Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image Generation

Jessica Quaye, Harvard University; Alicia Parrish, Google; Oana Inel, University of Zürich; Charvi Rastogi, Google; Hannah Rose Kirk, University of Oxford; Minsuk Kahng, Google; Erin Van Liemt, Google; Max Bartolo, University College London; Jess Tsang, Google; Justin White, Google; Nathan Clement, Google; Rafael Mosquera, ML Commons; Juan Ciro, ML Commons; Vijay Janapa Reddi, Harvard University; Lora Aroyo, Google

Insights From Insurance for Fair Machine Learning

Christian Fröhlich, University of Tübingen; Robert C. Williamson, University of Tübingen

No Simple Fix: How AI Harms Reflect Power and Jurisdiction in the Workplace

Nataliya Nedzhvetskaya, University of California, Berkeley; JS Tan, Massachusetts Institute of Technology

Algorithmic Misjudgement in Google Search Results: Evidence from Auditing the US Online Electoral Information Environment

Brooke Perreault, Wellesley College; Johanna Hoonsun Lee, Wellesley College; Ropafadzo Shava, Wellesley College; Eni Mustafaraj, Wellesley College

To See or Not to See: Understanding the Tensions of Algorithmic Curation for Visual Arts

Ramya Srinivasan, Fujitsu Research of America

In the Walled Garden: Challenges and Opportunities for Research on the Practices of the AI Tech Industry

Morgan Klaus Scheuerman, University of Colorado Boulder

Value is in the Eye of the Beholder: A Framework for an Equitable Graph Data Evaluation

Francesco Paolo Nerini, Sapienza University of Rome; Paolo Bajardi, CENTAI Institute; André Panisson, CENTAI Institute

Overriding (in)justice: pretrial risk assessment administration on the frontlines

Sarah Riley, Stanford University

Benchmarking the Fairness of Image Upsampling Methods

Mike Laszkiewicz, Ruhr University Bochum; Imant Daunhawer, ETH Zurich; Julia E. Vogt, ETH Zurich; Asja Fischer, Ruhr University Bochum; Johannes Lederer, University of Hamburg

Analyzing the Relationship Between Difference and Ratio-Based Fairness Metrics

Min-Hsuan Yeh, University of Massachusetts; Blossom Metevier, University of Massachusetts; Austin Hoag, Berkeley Existential Risk Initiative; Philip Thomas, University of Massachusetts

Diversified Ensembling: An Experiment in Crowdsourced Machine Learning

Ira Globus-Harris, University of Pennsylvania; Declan Harrison, University of Pennsylvania; Michael Kearns, University of Pennsylvania; Pietro Perona, California Institute of Technology; Aaron Roth, University of Pennsylvania

Trust Development and Repair in AI-Assisted Decision-Making during Complementary Expertise

Saumya Pareek, The University of Melbourne; Eduardo Velloso, The University of Melbourne; Jorge Goncalves, The University of Melbourne

Tackling Language Modelling Bias in Support of Linguistic Diversity

Gábor Bella, IMT Atlantique; Paula Helm, University of Amsterdam; Gertraud Koch, University of Hamburg; Fausto Giunchiglia, University of Trento

Legitimate Power, Illegitimate Automation: The problem of ignoring legitimacy in automated decision systems

Jake Stone, Australian National University; Brent Mittelstadt, Oxford University

Diversity of What? On the Different Conceptualizations of Diversity in Recommender Systems

Sanne Vrijenhoek, University of Amsterdam; Savvina Daniil, Centrum Wiskunde & Informatica; Jorden Sandel, University of Amsterdam; Laura Hollink, Centrum Wiskunde & Informatica

Towards Geographic Inclusion in the Evaluation of Text-to-Image Models

Melissa Hall, Meta (FAIR); Samuel J. Bell, Meta (FAIR); Candace Ross, Meta (FAIR); Adina Williams, Meta (FAIR); Michal Drozdzal, Meta (FAIR); Adriana Romero Soriano, McGill University

D-hacking

Emily Black, Barnard College; Talia Gillis, Columbia University; Zara Yasmine Hall, Columbia University

Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairness

Seamus Somerstep, University of Michigan; Ya'acov Ritov, University of Michigan; Yuekai Sun, University of Michigan

Data Agency Theory: A Precise Theory of Justice for AI Applications

Leah Ajmani, University of Minnesota; Logan Stapleton, University of Minnesota; Mo Houtti, University of Minnesota; Stevie Chancellor, University of Minnesota

Lazy Data Practices Harm Fairness Research

Jan Simson, LMU Munich; Alessandro Fabris, LMU Munich; Christoph Kern, LMU Munich

Auditing GPT's Content Moderation Guardrails: Can ChatGPT Write Your Favorite TV Show?

Yaaseen Mahomed, University of Pennsylvania; Charlie M. Crawford, Haverford College; Sanjana Gautam, Pennsylvania State University; Sorelle A. Friedler, Haverford College

Identifying and Improving Disability Bias in GPT-Based Resume Screening

Kate Glazko, Yusuf Mohammed, Ben Kosa, Venkatesh Potluri, Jennifer Mankoff; University of Washington /i>

The Digital Faces of Oppression and Domination: A Relational and Egalitarian Perspective on the Data-driven Society and its Regulation

Laurens Naudts, Univeristy of Amsterdam

AI Failure Cards: Understanding and Supporting Grassroots Efforts to Mitigate AI Failures in Homeless Services

Ningjing Tang, Carnegie Mellon University; Jiayin Zhi, Carnegie Mellon University; Tzu-Sheng Kuo, Carnegie Mellon University; Calla Kainaroi; Jeremy J. Northup, Point Park University; Kenneth Holstein, Carnegie Mellon University; Haiyi Zhu, Carnegie Mellon University; Hoda Heidari, Carnegie Mellon University; Hong Shen, Carnegie Mellon University

Silencing the Risk, Not the Whistle: A Semi-automated Text Sanitization Tool for Mitigating the Risk of Whistleblower Re-Identification

Dimitri Staufer, TU Berlin; Frank Pallas, University of Salzburg; Bettina Berendt, TU Berlin, Weizenbaum Institute, and KU Leuven

Gender Bias Detection in Court Decisions: A Brazilian Case Study

Raysa Benatti, University of Tübengen; Fabiana Severi, Univeristy of São Paulo; Sandra Avila, University of Campinas; Esther Luna Colombini, Univerity of Campinas

The four-fifths rule is not disparate impact: A woeful tale of epistemic trespassing in algorithmic fairness

Elizabeth Watkins, Intel Labs; Jiahao Chen, Responsible AI LLC

Mapping the Individual, Social and Biospheric Impacts of Foundation Models

Andrés Domínguez Hernández, Public Policy Programme, The Alan Turing Institute; Shyam Krishna, Public Policy Programme, The Alan Turing Institute and The Digital Environment Research Institute, Queen Mary University London; Antonella Maia Perini, Public Policy Programme, The Alan Turing Institute; Michael Katell, Public Policy Programme, The Alan Turing Institute; SJ Bennett, Department of Geography, Durham University; Ann Borda, Public Policy Programme, The Alan Turing Institute; Youmna Hashem, Public Policy Programme, The Alan Turing Institute; Semeli Hadjiloizou, Public Policy Programme, The Alan Turing Institute; Sabeehah Mahomed, Public Policy Programme, The Alan Turing Institute; Smera Jayadeva, Public Policy Programme, The Alan Turing Institute; Mhairi Aitken, Public Policy Programme, The Alan Turing Institute; David Leslie, The Digital Environment Research Institute, Queen Mary University London and Public Policy Programme, The Alan Turing Institute

Generalized People Diversity: Learning a Human Perception-Aligned Diversity Representation for People Images

Hansa Srinivasan, Google; Candice Schumann, Google; Aradhana Sinha, Google; David Madras, Google; Gbolahan Oluwafemi Olanubi, Google; Alex Beutel, OpenAI; Susanna Ricco, Google; Jilin Chen, Google

"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust

Sunnie S. Y. Kim, Princeton University; Q. Vera Liao, Microsoft; Mihaela Vorvoreanu, Microsoft; Stephanie Ballard, Microsoft; Jennifer Wortman Vaughan, Microsoft

The Legal Duty to Search for Less Discriminatory Algorithms

Emily Black, Barnard College; Logan Koepke, Upturn; Pauline Kim, Washington University in St. Louis; Solon Barocas, Microsoft Research; Mingwei Hsu, Upturn

Escalation Risks from Language Models in Military and Diplomatic Decision-Making

Juan-Pablo Rivera, Georgia Institute of Technology; Gabriel Mukobi, Stanford University; Anka Reuel, Stanford University; Max Lamparth, Stanford University; Chandler Smith, Northeastern University; Jacquelyn Schneider, Hoover Wargaming and Crisis Simulation Initiative

The Harmful Fetishization of Reductive Personal Tracking Metrics in Digital Systems

Aisha Sobey, Leverhulme Centre for the Future of Intelligence, University of Cambridge; Laura Carter, Independent

More Than the Sum of its Parts: Susceptibility to Algorithmic Disadvantage as a Conceptual Framework

Paola Lopez, University of Vienna and University of Bremen

A Systematic Review of Biometric Monitoring in the Workplace: Analyzing Socio-Technical Harms in Development, Deployment, and Use

Ezra Awumey, Carnegie Mellon University; Sauvik Das, Carnegie Mellon University; Jodi Forlizzi, Human Computer Interaction Institute, Carnegie Mellon University

Beyond Behaviorist Representational Harms: A Plan for Measurement and Mitigation

Jennifer Chien, University of California San Diego (UCSD); David Danks, University of California San Diego (UCSD)

Gender Representation Across Online Retail Products

Danapess Pessach, Amazon; Barbara Poblete, Department of Computer Science, University of Chile and Amazon

Visibility into AI Agents

Alan Chan, Centre for the Governance of AI and Mila (Quebec AI Institute); Carson Ezell, Harvard University; Max Kaufmann, Independent; Kevin Wei, Harvard Law School; Lewis Hammond, University of Oxford and Cooperative AI Foundation; Herbie Bradley, University of Cambridge; Emma Bluemke, Centre for the Governance of AI; Nitarshan Rajkumar, University of Cambridge; David Krueger, University of Cambridge; Noam Kolt, University of Toronto; Lennart Heim, Centre for the Governance of AI; Markus Anderljung, Centre for the Governance of AI

How sharing human rights data can have negative consequences: analysing modern slavery data sharing in the UK

Jamie Hancock, The Alan Turing Institute; Sarada Mahesh, The Alan Turing Institute; Jennifer Cobbe, University of Cambridge; Jatinder Singh, University of Cambridge; Anjali Mazumder, The Alan Turing Institute

Trouble at Sea: Data and Digital Technology Challenges for Maritime Human Rights Concerns

Jamie Hancock, The Alan Turing Institute; Ruoyun Hui, The Alan Turing Institute; Jatinder Singh, Compliant & Accountable Systems Group, University of Cambridge, and The Alan Turing Institute; Anjali Mazumder, The Alan Turing Institute

From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap

Tianqi Kou, College of Information Sciences and Technology, Pennsylvania State University

Structural Interventions and the Dynamics of Inequality

Aurora Zhang, Institute for Data, Systems, and Society, Massachusetts Institute of Technology; Anette Hosoi, Massachusetts Institute of Technology

Explainable Artificial Intelligence for Academic Performance Prediction: An Experimental Study on the Impact of Accuracy and Simplicity of Decision Trees on Causability and Fairness Perceptions

Marco Lünich, Faculty of Arts and Humanities, Heinrich Heine University; Birte Keller, Faculty of Arts and Humanities, Heinrich Heine University

Mitigating Group Bias in Federated Learning for Heterogeneous Devices

Khotso Selialia, University of Massachusetts Amherst; Yasra Chandio, University of Massachusetts Amherst; Fatima M. Anwar, University of Massachusetts Amherst

Machine Learning Data Practices Through a Data Curation Lens: An Evaluation Framework

Eshta Bhardwaj, University of Toronto; Harshit Gujral, University of Toronto; Siyi Wu, University of Toronto; Ciara Zogheib, University of Toronto; Tegan Maharaj, University of Toronto; Christoph Becker, University of Toronto

When Human-AI Interactions Become Parasocial: Agency and Anthropomorphism in Affective Design

Takuya Maeda, Faculty of Information and Media Studies, Western University; Anabel Quan-Haase, Faculty of Information and Media Studies, Western University, and Department of Sociology, Western University

A Framework for Assurance Audits of Algorithmic Systems

Khoa Lam, BABL AI Inc.; Benjamin Lange, BABL AI Inc. and Ludwig Maximilians University (LMU); Borhane Blili-Hamelin, BABL AI Inc. and AI Risk and Vulnerability Alliance (ARVA); Jovana Davidovic, BABL AI Inc. and University of Iowa; Shea Brown, BABL AI Inc. and University of Iowa; Ali Hasan, BABL AI Inc. and University of Iowa

Building, Shifting, & Employing Power: A Taxonomy of Responses From Below to Algorithmic Harm

Alicia DeVrio, Carnegie Mellon University; Motahhare Eslami, Carnegie Mellon University; Kenneth Holstein, Carnegie Mellon University

Auditing Work: Exploring the New York City Algorithmic Bias Audit Regime

Lara Groves, Ada Lovelace Institute; Jacob Metcalf, Data & Society Research Institute; Alayna Kennedy, Independent Researcher; Briana Vecchione, Data & Society Research Institute; Andrew Strait, Ada Lovelace Institute

Automated Transparency: A Legal and Empirical Analysis of the Digital Services Act Transparency Database

Rishabh Kaushal, Maastricht University; Jacob van de Kerkhof, Utrecht University; Catalina Goanta, Utrecht University; Gerasimos Spanakis, Maastricht University; Anda Iamnitchi, Maastricht University

PreFAIR: Combining Partial Preferences for Fair Consensus Decision-making

Kathleen Cachel, Worcester Polytechnic Institute; Elke Rundensteiner, Worcester Polytechnic Institute

Algorithmic Transparency and Participation through the Handoff Lens: Lessons Learned from the U.S. Census Bureau’s Adoption of Differential Privacy

Amina A. Abdu, University of Michigan; Lauren M. Chambers, University of California, Berkeley; Deirdre K. Mulligan, University of California, Berkeley; Abigail Z. Jacobs, University of Michigan

Auditing Image-based NSFW Classifiers for Content Filtering

Warren Leu, University of California, Irvine; Yuta Nakashima, Osaka University; Noa Garcia, Osaka University

Should Users Trust Advanced AI Assistants? Justified Trust As a Function of Competence and Alignment

Arianna Manzini, Google DeepMind; Geoff Keeling, Google Research; Nahema Marchal, Google DeepMind; Kevin R. McKee, Google DeepMind; Verena Rieser, Google DeepMind; Iason Gabriel, Google DeepMind

Impact Charts: A Tool for Identifying Systematic Bias in Social Systems and Data encoded in three different data sets

Darren Vengroff

Laboratory-Scale AI: Open-Weight Models are Competitive Even in Low-Resource Settings

Robert Wolfe, University of Washington; Isaac Slaughter, University of Washington; Bin Han, University of Washington; Bingbing Wen, University of Washington; Yiwei Yang, University of Washington; Lucas Rosenblatt, New York University; Bernease Herman, University of Washington; Eva Brown, University of Washington; Zening Qu, University of Washington; Nic Weber, University of Washington; Bill Howe, University of Washington

Human, all too human: accounting for automation bias in generative Large Language Models

Irina Carnat, Sant'Anna School of Advanced Studies

WorldBench: Quantifying Geographic Disparities in LLM Factual Recall

Mazda Moayeri, University of Maryland; Elham Tabassi, National Institutes of Standards and Technology; Soheil Feizi, University of Maryland

Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages

My H Dinh, University of Virginia; James Kotary, University of Virginia; Ferdinando Fioretto, University of Virginia

The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models

Abeba Birhane, Mozilla Foundation and Trinity College Dublin; Sepehr Dehdashtian, Michigan State University; Vinay Prabhu, Independent Researcher; Vishnu Boddeti, Michigan State University

Speaking of accent: A content analysis of accent misconceptions in ASR research

Kerri Prinos, Washington University in St. Louis; Neal Patwari, Washington University in St. Louis; Cathleen A. Power, Relational Communities

Law and the Emerging Political Economy of Algorithmic Audits

Petros Terzis, University of Amsterdam & University College London; Michael Veale, University College London; Noëlle Gaumann, University College London

Meaningful Transparency for Clinicians: Operationalising HCXAI Research with Gynaecologists

Bianca Schor, University of Cambridge; Emma Kallina, University of Cambridge; Jatinder Singh, University of Cambridge; Alan Blackwell, University of Cambridge

A Causal Perspective on Label Bias

Vishwali Mhasawade, New York University; Alexander D'Amour, Google; Stephen R. Pfohl, Google

Epistemic Power in AI Ethics Labor: Legitimizing Located Complaints

David Gray Widder, Digital Life Initiative, Cornell Tech

One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions

Jan Simson, Institute of Statistics, LMU Munich and Munich Center for Machine Learning (MCML); Florian Pfisterer, Institute of Statistics, LMU Munich; Christoph Kern, Institute of Statistics, LMU Munich and Munich Center for Machine Learning (MCML), University of Maryland

Large Language Models Portray Socially Subordinate Groups as More Homogeneous, Consistent with a Bias Observed in Humans

Messi H.J. Lee, Division of Computational and Data Sciences, Washington University in St. Louis; Jacob M. Montgomery, Department of Political Science, Washington University in St. Louis; Calvin K. Lai, Department of Psychological & Brain Sciences, Washington University in St. Louis

Perceptive Visual Urban Analytics is Not (Yet) Suitable for Municipalities

Tim Alpherts, University of Amsterdam; Sennay Ghebreab, University of Amsterdam; Yen-Chia Hsu, University of Amsterdam; Nanne Van Noord, University of Amsterdam

The Impact of Differential Feature Under-reporting on Algorithmic Fairness

Nil-Jana Akpinar, Carnegie Mellon University and Amazon Web Services; Zachary Lipton, Carnegie Mellon University; Alexandra Chouldechova, Carnegie Mellon University

Beyond Eviction Prediction: Leveraging Local Spatiotemporal Public Records to Inform Action

Tasfia Mashiat, George Mason University; Alex DiChristofano, Washington University in St. Louis; Patrick J. Fowler, Washington University in St. Louis; Sanmay Das, George Mason University

Collective Constitutional AI: Aligning a Language Model with Public Input

Saffron Huang, Collective Intelligence Project; Divya Siddarth, Collective Intelligence Project; Liane Lovitt, Anthropic; Thomas I. Liao, Unaffiliated; Esin Durmus, Anthropic; Alex Tamkin, Anthropic; Deep Ganguli, Anthropic

Fairness in Online Ad Delivery

Joachim Baumann, University of Zurich and Zurich University of Applied Sciences; Piotr Sapiezynski, Northeastern University; Christoph Heitz, Zurich University of Applied Sciences; Aniko Hannak, University of Zurich

Knowledge-Enhanced Language Models Are Not Bias-Proof: Situated Knowledge and Epistemic Injustice in AI

Angelie Kraft, Universität Hamburg and Leuphana Universität Lüneburg; Eloïse Soulier, Universität Hamburg

NLP for Maternal Healthcare: Perspectives and Guiding Principles in the Age of LLMs

Maria Antoniak, Allen Institute for AI; Aakanksha Naik, Allen Institute for AI; Carla S. Alvarado, Association of American Medical Colleges, Center for Health Justice; Lucy Lu Wang, University of Washington, Allen Institute for AI; Irene Y. Chen, University of California, Berkeley and University of California, San Francisco

Achieving Reproducibility in EEG-Based Machine Learning

Sean Kinahan, School of Computing and Augmented Intelligence, Arizona State University and College of Health Solutions, Arizona State University; Pouria Saidi, School of Electrical, Computer, and Energy Engineering, Arizona State University; Ayoub Daliri, College of Health Solutions, Arizona State University; Julie Liss, College of Health Solutions, Arizona State University; Visar Berisha, College of Health Solutions, Arizona State University and School of Electrical, Computer, and Energy Engineering, Arizona State University

Investigating and Designing for Trust in AI-powered Code Generation Tools

Ruotong Wang, Paul G. Allen School of Computer Science, University of Washington; Ruijia Cheng, Human Centered Design and Engineering, University of Washington; Denae Ford, Microsoft Research; Thomas Zimmermann, Microsoft Research

Transparency in the Wild: Navigating Transparency in a Deployed AI System to Broaden Need-Finding Approaches

Violet Turri, Carnegie Mellon University Software Engineering Institute; Katelyn Morrison, Carnegie Mellon University; Katherine-Marie Robinson, Carnegie Mellon University Software Engineering Institute; Collin Abidi, Carnegie Mellon University Software Engineering Institute; Adam Perer, Carnegie Mellon University; Jodi Forlizzi, Carnegie Mellon University; Rachel Dzombak, Carnegie Mellon University Software Engineering Institute

How the Types of Consequences in Social Scoring Systems Shape People's Perceptions and Behavioral Reactions

Carmen Loefflad, School of Computation, Information and Technology, Technical University of Munich; Jens Grossklags, School of Computation, Information and Technology, Technical University of Munich

The Impact and Opportunities of Generative AI in Fact-Checking

Robert Wolfe, University of Washington; Tanushree Mitra, University of Washington

Learning about Responsible AI On-The-Job: Learning Pathways, Orientations, and Aspirations

Michael Madaio, Google Research; Shivani Kapania, Carnegie Mellon University; Rida Qadri, Google Research; Ding Wang, Google Research; Andrew Zaldivar, Google Research; Remi Denton, Google Research; Lauren Wilcox, eBay

Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness

Edward Small, RMIT University; Kacper Sokol, ETH Zürich; Daniel Manning, RMIT University; Flora D. Salim, University of New South Wales; Jeffrey Chan, RMIT University

A Critical Survey on Fairness Benefits of Explainable AI

Luca Deck, University of Bayreuth; Jakob Schoeffer, University of Texas at Austin; Maria De-Arteaga, University of Texas at Austin; Niklas Kühl, University of Bayreuth

Evidence of What, for Whom? The Socially Contested Role of Algorithmic Bias in a Predictive Policing Tool

Marta Ziosi, University of Oxford; Dasha Pruss, Harvard University

Participation in the Age of Foundation Models

Harini Suresh, Cornell Tech and Brown University; Emily Tseng, Cornell University; Meg Young, Data & Society Research Institute; Mary Gray, Microsoft Research; Emma Pierson, Cornell Tech; Karen Levy, Cornell University

A Robot Walks into a Bar: Can Language Models Serve as Creativity SupportTools for Comedy? An Evaluation of LLMs’ Humour Alignment with Comedians

Piotr Mirowski, Google DeepMind; Juliette Love, Google DeepMind; Kory Mathewson, Google DeepMind; Shakir Mohamed, Google DeepMind

Participatory Objective Design via Preference Elicitation

Ali Shirali, UC Berkeley; Jessie Finocchiaro, CRCS, Harvard University; Rediet Abebe, Harvard Society of Fellows

Animation and Artificial Intelligence

Luke Stark, Faculty of Information and Media Studies, Western University and Azrieli Global Scholars Program, Canadian Institute for Advanced Research (CIFAR)

Careless Whisper: Speech-to-Text Hallucination Harms

Allison Koenecke, Cornell University; Anna Seo Gyeong Choi, Cornell University; Katelyn X. Mei, University of Washington; Hilke Schellmann, New York University; Mona Sloane, University of Virginia

Actionable Recourse for Automated Decisions: Examining the Effects of Counterfactual Explanation Type and Presentation on Lay User Understanding

Peter M. VanNostrand, Worcester Polytechnic Institute; Dennis M. Hofmann, Worcester Polytechnic Institute; Lei Ma, Worcester Polytechnic Institute; Elke A. Rundensteiner, Worcester Polytechnic Institute

Null Compliance: NYC Local Law 144 and the Challenges of Algorithm Accountability

Lucas Wright, Citizens and Technology Lab, Cornell University; Roxana Mika Muenster, Department of Communication, Cornell University; Briana Vecchione, Data & Society Research Institute; Tianyao Qu, Department of Sociology, Cornell University; Pika (Senhuang) Cai, Department of Information Science, Cornell University; Alan Smith, Consumer Reports; Comm 2450 Student Investigators, Cornell University; Jacob Metcalf, Data & Society Research Institute; J. Nathan Matias, Citizens and Technology Lab, Cornell University

SIDEs: Separating Idealization from Deceptive 'Explanations' in xAI

Emily Sullivan, Utrecht University

Algorithmic Harms and Algorithmic Wrongs

Nathalie Diberardino, Department of Philosophy, Western University; Clair Baleshta, Department of Philosophy, Western University; Luke Stark, Faculty of Information and Media Studies, Western University and Azrieli Global Scholars Program, Canadian Institute for Advanced Research (CIFAR)

Real Risks of Fake Data: Synthetic Data, Diversity-Washing, and Consent Circumvention

Cedric Deslandes Whitney, UC Berkeley; Justin Norman, UC Berkeley

CARMA: A Practical Framework to Generate Recommendations for Causal Algorithmic Recourse at Scale

Ayan Majumdar, MPI-SWS and Saarland University; Isabel Valera, Saarland University and MPI-SWS

System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes

Arpit Agarwal, FAIR, Meta; Nicolas Usunier, FAIR, Meta; Alessandro Lazaric, FAIR, Meta; Maximilian Nickel, FAIR, Meta

Group Fairness via Group Consensus

Eunice Chan, University of Illinois, Urbana-Champaign; Zhining Liu, University of Illinois, Urbana-Champaign; Ruizhong Qiu, University of Illinois, Urbana-Champaign; Yuheng Zhang, University of Illinois, Urbana-Champaign; Ross Maciejewski, Arizona State University; Hanghang Tong, University of Illinois, Urbana-Champaign

Beyond Use-Cases: A Participatory Approach to Envisioning Data Science in Law Enforcement

Caitlin Kearney, Technical University Munich; Jiri Hron, Google DeepMind; Helen Kosc, University of Oxford; Miri Zilka, University of Cambridge

Intervening to Increase Community Trust for Fair Network Outcomes

Naina Balepur, University of Illinois Urbana-Champaign; Hari Sundaram, University of Illinois Urbana-Champaign

Constructing Capabilities: The Politics of Testing Infrastructures for Generative AI

Gabriel Grill, School of Information, University of Michigan

Unlawful Proxy Discrimination: A Framework for Challenging Inherently Discriminatory Algorithms

Hilde Weerts, Eindhoven University of Technology; Aislinn Kelly-Lyth, Blackstone Chambers; Reuben Binns, University of Oxford; Jeremias Adams-Prassl, University of Oxford

MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification Models

Grace Guo, Georgia Institute of Technology; Lifu Deng, Cleveland Clinic; Animesh Tandon, Cleveland Clinic; Alex Endert, Georgia Institute of Technology; Bum Chul Kwon, IBM Research

AI as a Sport: On the Competitive Epistemologies of Benchmarking

Will Orr, University of Southern California; Edward B. Kang, New York University

Talking past each other? Navigating discourse on ethical AI: Comparing the discourse on ethical AI policy by Big Tech companies and the European Commission

Cornelia Evers, Independent Researcher

Fairness without Sensitive Attributes via Knowledge Sharing

Hongliang Ni, University of Queensland; Lei Han, University of Queensland; Tong Chen, University of Queensland; Shazia Sadiq, University of Queensland; Gianluca Demartini, University of Queensland

The Conflict Between Algorithmic Fairness and Non-Discrimination: An Analysis of Fair Automated Hiring

Robert Lee Poe, Laboratorio Interdisciplinare Diritti e Regole (LIDER-Lab), Sant'Anna School of Advanced Studies; Soumia Zohra El Mestari, Interdisciplinary Research Group in Socio-technical Cybersecurity (IRISC), Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg

BaBE: Enhancing Fairness via Estimation of Explaining Variables

Ruta Binkyte, CISPA – Helmholtz Center for Information Security; Daniele Gorla, Università di Roma; Catuscia Palamidessi, Inria and École Polytechnique (IPP)

Akal Badi ya Bias: An Exploratory Study of Gender Bias in Hindi Language Technology

Rishav Hada, Microsoft Research; Safiya Husain, Karya; Varun Gumma, Microsoft Research; Harshita Diddee, Carnegie Mellon University; Aditya Yadavalli, Karya; Agrima Seth, University of Michigan; Nidhi Kulkarni, Karya; Ujwal Gadiraju, Delft University of Technology; Aditya Vashistha, Cornell University; Vivek Seshadri, Microsoft Research; Kalika Bali, Microsoft Research

Balancing Act: Evaluating People's Perceptions of Fair Ranking Metrics

Mallak Alkhathlan, Worcester Polytechnic Institute; Kathleen Cachel, Worcester Polytechnic Institute; Hilson Shrestha, Worcester Polytechnic Institute; Lane Harrison, Worcester Polytechnic Institute; Elke Rundensteiner, Worcester Polytechnic Institute

The Emerging Artifacts of Centralized Open-Code

Madiha Zahrah Choksi, Cornell Tech; Ilan Mandel, Cornell Tech; David Widder, Cornell Tech; Yan Shvartzshnaider, York University

From the Fair Distribution of Predictions to the Fair Distribution of Social Goods: Evaluating the Impact of Fair Machine Learning on Long-Term Unemployment

Sebastian Zezulka, University of Tübingen; Konstantin Genin, University of Tübingen

Perceptions of Policing Surveillance Technologies in Detroit: Moving Beyond "Better than Nothing"

Alex Jiahong Lu, Rutgers University; Cameron Moy, University of Pennsylvania; Mark S. Ackerman, University of Michigan; Jeffrey Morenoff, University of Michigan; Tawanna R. Dillahunt, University of Michigan

Responsible Adoption of Generative AI in Higher Education: Developing a “Points to Consider” Approach Based on Faculty Perspectives

Ravit Dotan, TechBetter; Lisa S. Parker, University of Pittsburgh; John Radzilowicz, University of Pittsburgh

The Unfair Side of Privacy Enhancing Technologies: Addressing the Trade-Offs Between PETs and Fairness

Alessandra Calvi, Vrije Universiteit Brussel; Gianclaudio Malgieri, Leiden University; Dimitris Kotzinos, CY Cergy Paris University

The Neutrality Fallacy: When Algorithmic Fairness Interventions are (Not) Positive Action

Hilde Weerts, Eindhoven University of Technology; Raphaële Xenidis, Sciences Po Law School; Fabien Tarissan, ENS Paris-Saclay; Henrik Palmer Olsen, University of Copenhagen; Mykola Pechenizkiy, Eindhoven University of Technology

My Future with My Chatbot: A Scenario-Driven, User-Centric Approach to Anticipating AI Impacts

Kimon Kieslich, University of Amsterdam; Natali Helberger, University of Amsterdam; Nicholas Diakopoulos, Northwestern University

The Impact of iBuying is About More Than Just Racial Disparities: Evidence from Mecklenburg County, NC

Isaac Slaughter, University of Washington; Eva Maxfield Brown, University of Washington; Nic Weber, University of Washington

Regulating Explainability in Machine Learning Applications -- Observations from a Policy Design Experiment

Nadia Nahar, Carnegie Mellon University; Jenny Rowlett, Oberlin College; Matthew Bray, Yale University; Zahra Abba Omar, Yale University; Xenophon Papademetris, Yale University; Alka Menon, Yale University; Christian Kästner, Carnegie Mellon University

Fairness Feedback Loops: Training on Synthetic Data Amplifies Bias

Sierra Wyllie, University of Toronto and Vector Institute; Ilia Shumailov, University of Oxford; Nicolas Papernot, University of Toronto and Vector Institute

Data, Annotation, and Meaning-Making: The Politics of Categorization in Annotating a Dataset of Faith-based Communal Violence

Mohammad Rashidujjaman Rifat, University of Toronto; Abdullah Hasan Safir, University of Cambridge; Sourav Saha, Shahjalal University Of Science And Technology; Jahedul Alam Junaed, Shahjalal University of Science and Technology; Maryam Saleki, Fordham University; Mohammad Ruhul Amin, Fordham University; Syed Ishtiaque Ahmed, University of Toronto

The Role of Explainability in Collaborative Human-AI Disinformation Detection

Vera Schmitt, TU Berlin and DFKI; Luis-Felipe Villa-Arenas, Telekom and TU Berlin; Nils Feldhus, DFKI; Joachim Meyer, Tel Aviv University; Robert P. Spang, TU Berlin; Sebastian Möller, TU Berlin and DFKI

An Information Bottleneck Characterization of the Understanding-Workload Tradeoff in Human-Centered Explainable AI

Lindsay Sanneman, Massachusetts Institute of Technology; Mycal Tucker, Massachusetts Institute of Technology; Julie A. Shah, Massachusetts Institute of Technology

A Critical Analysis of the Largest Source for Generative AI Training Data: Common Crawl

Stefan Baack, Mozilla Foundation

Seeing through opacity: The limitations of digital ad transparency in Brazil

Rose Marie Santini, Federal University of Rio de Janeiro; Débora Salles, Federal University of Rio de Janeiro; Bruno Maurício Martins, Federal University of Rio de Janeiro; Alékis Moreira, Fluminense Federal University; João Gabriel Haddad, Federal University of Rio de Janeiro

Trust Issues: Discrepancies in Trustworthy AI Keywords Use in Policy and Research

Autumn Toney, Georgetown University; Kathleen Curlee, Georgetown University; Emelia Probasco, Georgetown University

Algorithmic Arbitrariness in Content Moderation

Juan Felipe Gomez, Harvard University; Caio Machado, Oxford University; Lucas Monteiro Paes, Harvard University; Flavio Calmon, Harvard University

Black-Box Access is Insufficient for Rigorous AI Audits

Stephen Casper, Massachusetts Institute of Technology; Carson Ezell, Harvard University; Charlotte Siegmann, Massachusetts Institute of Technology; Noam Kolt, University of Toronto; Taylor Lynn Curtis, Massachusetts Institute of Technology; Benjamin Bucknall, Centre for the Governance of AI; Andreas Haupt, Massachusetts Institute of Technology; Kevin Wei, Harvard University; Jérémy Scheurer, Apollo Research; Marius Hobbhahn, Apollo Research; Lee Sharkey, Apollo Research; Satyapriya Krishna, Harvard University; Marvin Von Hagen, Massachusetts Institute of Technology; Silas Alberti, Stanford University; Alan Chan, Mila (Quebec AI Institute); Qinyi Sun, Massachusetts Institute of Technology; Michael Gerovitch, Massachusetts Institute of Technology; David Bau, Northeastern University; Max Tegmark, Massachusetts Institute of Technology; David Krueger, University of Cambridge; Dylan Hadfield-Menell, Massachusetts Institute of Technology

Attitudes Toward Facial Analysis AI: A Cross-National Study Comparing Argentina, Kenya, Japan, and the USA

Chiara Ullstein, Technical University of Munich; Severin Engelmann, Cornell Tech; Orestis Papakyriakopoulos, Technical University of Munich; Yuko Ikkatai, Kanazawa University; Naira Paola Arnez-Jordan, Technical University of Munich; Rose Caleno, Unaffiliated; Brian Mboya, Dedan Kimathi University of Technology; Shuichiro Higuma, The University of Tokyo; Tilman Hartwig, AI Lab, Umweltbundesamt; Hiromi Yokoyama, The University of Tokyo; Jens Grossklags, Technical University of Munich

Embracing Diversity: Interpretable Zero-shot Classification Beyond One Vector Per Class

Mazda Moayeri, University of Maryland; Michael Rabbat, Meta AI; Mark Ibrahim, Meta AI; Diane Bouchacourt, Meta AI

From "AI" to Probabilistic Automation: How Does Anthropomorphization of Technical Systems Descriptions Influence Trust?

Nanna Inie, IT University of Copenhagen / University of Washington; Stefania Druga, University of Chicago; Peter Zukerman, University of Washington; Emily M. Bender, University of Washington

Auditing for Racial Discrimination in the Delivery of Education Ads

Basileal Imana, Princeton University; Aleksandra Korolova, Princeton University; John Heidemann, University of Southern California

Analyzing And Editing Inner Mechanisms of Backdoored Language Models

Max Lamparth, Stanford University; Anka Reuel, Stanford University

Understanding Disparities in Post Hoc Machine Learning Explanation

Vishwali Mhasawade, New York University; Salman Rahman, New York University; Zoé Haskell-Craig, New York University; Rumi Chunara, New York University

Recommend Me? Designing Fairness Metrics with Providers

Jessie J. Smith, University of Colorado Boulder; Aishwarya Satwani, University of Colorado Boulder; Robin Burke, University of Colorado Boulder; Casey Fiesler, University of Colorado Boulder

Visions of a Discipline: Analyzing Introductory AI Courses on YouTube

Severin Engelmann, Cornell Tech; Madiha Zahrah Choksi, Cornell Tech; Angelina Wang, Princeton; Casey Fiesler, University of Colorado Boulder

Drivers and persuasive strategies to influence user intention to learn about manipulative design

Pooria Babaei, University of Saskatchewan; Julita Vassileva, University of Saskatchewan

Model ChangeLists: Characterizing Updates to ML Models

Sabri Eyuboglu, Stanford University; Karan Goel, Stanford University; Arjun Desai, Stanford University; Lingjiao Chen, Stanford University; Mathew Monfort, Amazon Web Services; Chris Ré, Stanford University; James Zou, Stanford University

(A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice

Inyoung Cheong, University of Washington; King Xia, Independent Attorney; K. J. Kevin Feng, University of Washington; Quan Ze Chen, University of Washington; Amy X. Zhang, University of Washington

Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronouns

Goya van Boven, Utrecht University; Yupei Du, Utrecht University; Dong Nguyen, Utrecht University

Racial/Ethnic Categories in AI and Algorithmic Fairness: Why They Matter and What They Represent

Jennifer Mickel, The University of Texas at Austin

On the Quest for Effectiveness in Human Oversight: Interdisciplinary Perspectives

Sarah Sterz, Saarland University; Kevin Baum, DFKI; Sebastian Biewer, Saarland University; Holger Hermanns, Saarland University; Anne Lauber-Rönsberg, TU Dresden; Philip Meinel, TU Dresden; Markus Langer, Universität Freiburg

Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages

My H Dinh, University of Virginia; James Kotary, University of Virginia; Ferdinando Fioretto, University of Virginia

One vs. Many: Comprehending Accurate Information from Multiple Erroneous and Inconsistent AI Generations

Yoonjoo Lee, KAIST; Kihoon Son, KAIST; Tae Soo Kim, KAIST; Jisu Kim, Georgia Institute of Technology; John Joon Young Chung, Midjourney; Eytan Adar, University of Michigan; Juho Kim, KAIST

Rethinking open source generative AI: open washing and the EU AI Act

Andreas Liesenfeld and Mark Dingemanse, Radboud University