Table of Contents

• Machine Explanations and Human UnderstandingChacha Chen, Shi Feng, Amit Sharma 0007, Chenhao Tan. 1 [doi]
• Broadening AI Ethics Narratives: An Indic Art ViewAjay Divakaran, Aparna Sridhar, Ramya Srinivasan 0002. 2-11 [doi]
• How to Explain and Justify Almost Any Decision: Potential Pitfalls for Accountability in AI Decision-MakingJoyce Zhou, Thorsten Joachims. 12-21 [doi]
• 'We are adults and deserve control of our phones': Examining the risks and opportunities of a right to repair for mobile appsKonrad Kollnig, Siddhartha Datta, Thomas Serban Von Davier, Max Van Kleek, Reuben Binns, Ulrik Lyngs, Nigel Shadbolt. 22-34 [doi]
• Fairness in machine learning from the perspective of sociology of statistics: How machine learning is becoming scientific by turning its back on metrological realismBilel Benbouzid. 35-43 [doi]
• Two Reasons for Subjecting Medical AI Systems to Lower Standards than HumansJakob Mainz, Lauritz Munch, Jens Christian Bjerring. 44-49 [doi]
• Optimization's Neglected Normative CommitmentsBenjamin Laufer, Thomas Krendl Gilbert, Helen Nissenbaum. 50-63 [doi]
• Welfarist Moral Grounding for Transparent AIDevesh Narayanan. 64-76 [doi]
• Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision ApplicationSunnie S. Y. Kim, Elizabeth Anne Watkins, Olga Russakovsky, Ruth Fong, Andrés Monroy-Hernández. 77-88 [doi]
• Multi-dimensional Discrimination in Law and Machine Learning - A Comparative OverviewArjun Roy 0001, Jan Horstmann, Eirini Ntoutsi. 89-100 [doi]
• Reconciling Individual Probability Forecasts✱Aaron Roth 0001, Alexander Tolbert, Scott Weinstein. 101-110 [doi]
• The Gradient of Generative AI Release: Methods and ConsiderationsIrene Solaiman. 111-122 [doi]
• In the Name of Fairness: Assessing the Bias in Clinical Record De-identificationYuxin Xiao, Shulammite Lim, Tom Joseph Pollard, Marzyeh Ghassemi. 123-137 [doi]
• "How Biased are Your Features?": Computing Fairness Influence Functions with Global Sensitivity AnalysisBishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel. 138-148 [doi]
• Preventing Discriminatory Decision-making in Evolving Data StreamsZichong Wang, Nripsuta Saxena, Tongjia Yu, Sneha Karki, Tyler Zetty, Israat Haque 0001, Shan Zhou, Dukka Kc, Ian Stockwell, Xuyu Wang, Albert Bifet, Wenbin Zhang 0002. 149-159 [doi]
• WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT?Ali Akbar Septiandri, Marios Constantinides, Mohammad Tahaei, Daniele Quercia. 160-171 [doi]
• Trustworthy AI and the Logics of Intersectional ResistanceBran Knowles, Jasmine Fledderjohann, John T. Richards, Kush R. Varshney. 172-182 [doi]
• In her Shoes: Gendered Labelling in Crowdsourced Safety Perceptions Data from IndiaNandana Sengupta, Ashwini Vaidya, James A. Evans. 183-192 [doi]
• The Dataset Multiplicity Problem: How Unreliable Data Impacts PredictionsAnna P. Meyer, Aws Albarghouthi, Loris D'Antoni. 193-204 [doi]
• "I wouldn't say offensive but...": Disability-Centered Perspectives on Large Language ModelsVinitha Gadiraju, Shaun K. Kane, Sunipa Dev, Alex S. Taylor, Ding Wang, Emily Denton, Robin Brewer. 205-216 [doi]
• Walking the Walk of AI Ethics: Organizational Challenges and the Individualization of Risk among Ethics EntrepreneursSanna J. Ali, Angèle Christin, Andrew Smart, Riitta Katila. 217-226 [doi]
• Algorithmic Transparency from the South: Examining the state of algorithmic transparency in Chile's public administration algorithmsJosé Pablo Lapostol Piderit, Romina Garrido Iglesias, María Paz Hermosilla Cornejo. 227-235 [doi]
• Who Should Pay When Machines Cause Harm? Laypeople's Expectations of Legal Damages for Machine-Caused HarmGabriel Lima, Nina Grgic-Hlaca, Jin Keun Jeong, Meeyoung Cha. 236-246 [doi]
• Diagnosing AI Explanation Methods with Folk Concepts of BehaviorAlon Jacovi, Jasmijn Bastings, Sebastian Gehrmann, Yoav Goldberg, Katja Filippova. 247 [doi]
• Certification Labels for Trustworthy AI: Insights From an Empirical Mixed-Method StudyNicolas Scharowski, Michaela Benk, Swen J. Kühne, Léane Wettstein, Florian Brühlmann. 248-260 [doi]
• The ethical ambiguity of AI data enrichment: Measuring gaps in research ethics norms and practicesWill Hawkins, Brent D. Mittelstadt 0002. 261-270 [doi]
• Making Intelligence: Ethical Values in IQ and ML BenchmarksBorhane Blili-Hamelin, Leif Hancox-Li. 271-284 [doi]
• Saliency Cards: A Framework to Characterize and Compare Saliency MethodsAngie Boggust, Harini Suresh, Hendrik Strobelt, John V. Guttag, Arvind Satyanarayan. 285-296 [doi]
• Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource ConstraintsJamelle Watson-Daniels, Solon Barocas, Jake M. Hofman, Alexandra Chouldechova. 297-311 [doi]
• Ghosting the Machine: Judicial Resistance to a Recidivism Risk Assessment InstrumentDasha Pruss. 312-323 [doi]
• 'Affordances' for Machine LearningJenny L. Davis. 324-332 [doi]
• Explainable AI is Dead, Long Live Explainable AI!: Hypothesis-driven Decision Support using Evaluative AITim Miller 0001. 333-342 [doi]
• Stronger Together: on the Articulation of Ethical Charters, Legal Tools, and Technical Documentation in MLGiada Pistilli, Carlos Muñoz Ferrandis, Yacine Jernite, Margaret Mitchell. 343-354 [doi]
• Simplicity Bias Leads to Amplified Performance DisparitiesSamuel James Bell, Levent Sagun. 355-369 [doi]
• On the Independence of Association Bias and Empirical Fairness in Language ModelsLaura Cabello, Anna Katrine Jørgensen, Anders Søgaard. 370-378 [doi]
• Envisioning Equitable Speech Technologies for Black Older AdultsRobin N. Brewer, Christina N. Harrington, Courtney Heldreth. 379-388 [doi]
• Group-Fair Classification with Strategic AgentsAndrew Estornell, Sanmay Das, Yang Liu 0018, Yevgeniy Vorobeychik. 389-399 [doi]
• The Possibility of Fairness: Revisiting the Impossibility Theorem in PracticeAndrew Bell, Lucius Bynum, Nazarii Drushchak, Tetiana Zakharchenko, Lucas Rosenblatt, Julia Stoyanovich. 400-422 [doi]
• Domain Adaptive Decision Trees: Implications for Accuracy and FairnessJosé M. Álvarez 0002, Kristen M. Scott, Bettina Berendt, Salvatore Ruggieri. 423-433 [doi]
• Algorithmic Transparency and Accountability through Crowdsourcing: A Study of the NYC School Admission LotteryAmélie Marian. 434-443 [doi]
• Rethinking Transparency as a Communicative ConstellationFlorian Eyert, Paola Lopez. 444-454 [doi]
• On the Praxes and Politics of AI Speech Emotion RecognitionEdward B. Kang. 455-466 [doi]
• It's about power: What ethical concerns do software engineers have, and what do they (feel they can) do about them?David Gray Widder, Derrick Zhen, Laura Dabbish, James D. Herbsleb. 467-479 [doi]
• Does AI-Assisted Fact-Checking Disproportionately Benefit Majority Groups Online?Terrence Neumann, Nicholas Wolczynski. 480-490 [doi]
• Algorithms as Social-Ecological-Technological Systems: an Environmental Justice Lens on Algorithmic AuditsBogdana Rakova, Roel Dobbe. 491 [doi]
• The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in U.S. GovernmentJennifer King, Daniel Ho, Arushi Gupta, Victor Wu, Helen Webley-Brown. 492-505 [doi]
• AI's Regimes of Representation: A Community-centered Study of Text-to-Image Models in South AsiaRida Qadri, Renee Shelby, Cynthia L. Bennett, Emily Denton. 506-517 [doi]
• A Theory of Auditability for Allocation and Social Choice MechanismsAram Grigoryan, Markus Möller. 518 [doi]
• Representation in AI EvaluationsA. Stevie Bergman, Lisa Anne Hendricks, Maribeth Rauh, Boxi Wu, William Agnew, Markus Kunesch, Isabella Duan, Iason Gabriel, William Isaac 0001. 519-533 [doi]
• Detecting disparities in police deployments using dashcam dataMatt Franchi, J. D. Zamfirescu-Pereira, Wendy Ju, Emma Pierson. 534-544 [doi]
• Delayed and Indirect Impacts of Link RecommendationsHan Zhang, Shangen Lu, Yixin Wang, Mihaela Curmei. 545-557 [doi]
• Striving for Affirmative Algorithmic Futures: How the Social Sciences can Promote more Equitable and Just Algorithmic System DesignAnna-Lena Theus. 558-568 [doi]
• Can Workers Meaningfully Consent to Workplace Wellbeing Technologies?Shreya Chowdhary, Anna Kawakami, Mary L. Gray, Jina Suh, Alexandra Olteanu, Koustuv Saha. 569-582 [doi]
• Invigorating Ubuntu Ethics in AI for healthcare: Enabling equitable careLameck Mbangula Amugongo, Nicola J. Bidwell, Caitlin C. Corrigan. 583-592 [doi]
• Honor Ethics: The Challenge of Globalizing Value Alignment in AIStephen Tze-Inn Wu, Daniel Demetriou, Rudwan Ali Husain. 593-602 [doi]
• Power and Resistance in the Twitter Bias DiscoursePaola Lopez. 603 [doi]
• Runtime Monitoring of Dynamic Fairness PropertiesThomas A. Henzinger, Mahyar Karimi, Konstantin Kueffner, Kaushik Mallik. 604-614 [doi]
• Data Collaboratives with the Use of Decentralised LearningMaciej Krzysztof Zuziak, Onntje Hinrichs, Aizhan Abdrassulova, Salvatore Rinzivillo. 615-625 [doi]
• Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive AccuracyAngelina Wang, Sayash Kapoor, Solon Barocas, Arvind Narayanan. 626 [doi]
• Care and Coordination in Algorithmic Systems: An Economies of Worth ApproachJohn Rudnik, Robin Brewer. 627-638 [doi]
• You Sound Depressed: A Case Study on Sonde Health's Diagnostic Use of Voice Analysis AIAnna Ma, Elizabeth Patitsas, Jonathan Sterne. 639-650 [doi]
• Harms from Increasingly Agentic Algorithmic SystemsAlan Chan, Rebecca Salganik, Alva Markelius, Chris Pang, Nitarshan Rajkumar, Dmitrii Krasheninnikov, Lauro Langosco, Zhonghao He, Yawen Duan, Micah Carroll, Michelle Lin, Alex Mayhew, Katherine Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj. 651-666 [doi]
• How Redundant are Redundant Encodings? Blindness in the Wild and Racial Disparity when Race is UnobservedLingwei Cheng, Isabel O. Gallegos, Derek Ouyang, Jacob Goldin, Daniel E. Ho. 667-686 [doi]
• On the Site of Predictive JusticeSeth Lazar, Jake Stone. 687 [doi]
• Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-MakingLuke Guerdan, Amanda Coston, Zhiwei Steven Wu, Kenneth Holstein. 688-704 [doi]
• Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry PracticeWesley Hanwen Deng, Nur Yildirim, Monica Chang, Motahhare Eslami, Kenneth Holstein, Michael Madaio. 705-716 [doi]
• Your Browsing History May Cost You: A Framework for Discovering Differential Pricing in Non-Transparent MarketsAditya Karan, Naina Balepur, Hari Sundaram. 717-735 [doi]
• Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential FairnessBrianna Richardson, Prasanna Sattigeri, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Amit Dhurandhar, Juan E. Gilbert. 736-752 [doi]
• FairAssign: Stochastically Fair Driver Assignment in Gig Delivery PlatformsDaman Deep Singh, Syamantak Das, Abhijnan Chakraborty. 753-763 [doi]
• Algorithmic Decisions, Desire for Control, and the Preference for Human Review over Algorithmic ReviewHenrietta Lyons, Tim Miller 0001, Eduardo Velloso. 764-774 [doi]
• Gender Animus Can Still Exist Under Favorable Disparate Impact: a Cautionary Tale from Online P2P LendingXudong Shen, Tianhui Tan, Tuan Phan, Jussi Keppo. 775-791 [doi]
• "I Think You Might Like This": Exploring Effects of Confidence Signal Patterns on Trust in and Reliance on Conversational Recommender SystemsMarissa Radensky, Julie Anne Séguin, Jang Soo Lim, Kristen Olson, Robert Geiger. 792-804 [doi]
• Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision TreeHilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy. 805-816 [doi]
• On (assessing) the fairness of risk score modelsEike Petersen, Melanie Ganz, Sune Hannibal Holm, Aasa Feragen. 817-829 [doi]
• UNFair: Search Engine Manipulation, Undetectable by Amortized InequityTim De Jonge, Djoerd Hiemstra. 830-839 [doi]
• Datafication Genealogies beyond Algorithmic Fairness: Making Up Racialised SubjectsAna Valdivia, Martina Tazzioli. 840-850 [doi]
• Maximal fairnessMaryBeth Defrance, Tijl De Bie. 851-880 [doi]
• Augmented Datasheets for Speech Datasets and Ethical Decision-MakingOrestis Papakyriakopoulos, Anna Seo Gyeong Choi, William Thong, Dora Zhao, Jerone Theodore Alexander Andrews, Rebecca Bourke, Alice Xiang, Allison Koenecke. 881-904 [doi]
• To Be High-Risk, or Not To Be - Semantic Specifications and Implications of the AI Act's High-Risk AI Applications and Harmonised StandardsDelaram Golpayegani, Harshvardhan J. Pandit, Dave Lewis 0001. 905-915 [doi]
• Implementing Fairness Constraints in Markets Using Taxes and SubsidiesAlexander Peysakhovich, Christian Kroer, Nicolas Usunier. 916-930 [doi]
• AI in the Public Eye: Investigating Public AI Literacy Through AI ArtDrew Hemment, Morgan Currie, SJ Bennett, Jake Elwes, Anna Ridler, Caroline Sinders, Matjaz Vidmar, Robin Hill, Holly Warner. 931-942 [doi]
• Questioning the ability of feature-based explanations to empower non-experts in robo-advised financial decision-makingAstrid Bertrand, James R. Eagan, Winston Maxwell. 943-958 [doi]
• On the Impact of Explanations on Understanding of Algorithmic Decision-MakingTimothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek. 959-970 [doi]
• Addressing contingency in algorithmic (mis)information classification: Toward a responsible machine learning agendaAndrés Domínguez Hernández, Richard Owen, Dan Saattrup Nielsen, Ryan McConville. 971 [doi]
• "We try to empower them" - Exploring Future Technologies to Support Migrant JobseekersSonja Mei Wang, Kristen M. Scott, Margarita Artemenko, Milagros Miceli, Bettina Berendt. 972-983 [doi]
• Robustness Implies Fairness in Causal Algorithmic RecourseAhmad-Reza Ehyaei, Amir-Hossein Karimi, Bernhard Schölkopf, Setareh Maghsudi. 984-1001 [doi]
• Bias on Demand: A Modelling Framework That Generates Synthetic Data With BiasJoachim Baumann 0002, Alessandro Castelnovo, Riccardo Crupi, Nicole Inverardi, Daniele Regoli. 1002-1013 [doi]
• ACROCPoLis: A Descriptive Framework for Making Sense of FairnessAndrea Aler Tubella, Dimitri Coelho Mollo, Adam Dahlgren Lindström, Hannah Devinney, Virginia Dignum, Petter Ericson, Anna Jonsson, Timotheus Kampik, Tom Lenaerts, Julian Alfredo Mendez, Juan Carlos Nieves. 1014-1025 [doi]
• Towards Labor Transparency in Situated Computational Systems Impact ResearchFelicia S. Jing, Sara E. Berger, Juana Catalina Becerra Sandoval. 1026-1037 [doi]
• Measuring and mitigating voting access disparities: a study of race and polling locations in Florida and North CarolinaMohsen Abbasi, Calvin Barrett, Kristian Lum, Sorelle A. Friedler, Suresh Venkatasubramanian. 1038-1048 [doi]
• Which Stereotypes Are Moderated and Under-Moderated in Search Engine Autocompletion?Alina Leidinger, Richard Rogers. 1049-1061 [doi]
• Ethical considerations in the early detection of Alzheimer's disease using speech and AIUlla Petti, Rune Nyrup, Jeffrey M. Skopek, Anna Korhonen. 1062-1075 [doi]
• Co-Design Perspectives on Algorithm Transparency Reporting: Guidelines and PrototypesMichal Luria. 1076-1087 [doi]
• More Data Types More Problems: A Temporal Analysis of Complexity, Stability, and Sensitivity in Privacy PoliciesJuniper Lovato, Philip Mueller, Parisa Suchdev, Peter Sheridan Dodds. 1088-1100 [doi]
• Emotions and Dynamic Assemblages: A Study of Automated Social Security Using Qualitative Longitudinal ResearchMorgan Currie, Lena Podoletz. 1101-1111 [doi]
• Regulating ChatGPT and other Large Generative AI ModelsPhilipp Hacker, Andreas Engel 0006, Marco Mauer. 1112-1123 [doi]
• On the Richness of CalibrationBenedikt Höltgen, Robert C. Williamson. 1124-1138 [doi]
• The role of explainable AI in the context of the AI ActCecilia Panigutti, Ronan Hamon, Isabelle Hupont, David Fernández Llorca, Delia Fano Yela, Henrik Junklewitz, Salvatore Scalzo, Gabriele Mazzini, Ignacio Sanchez, Josep Soler Garrido, Emilia Gómez. 1139-1150 [doi]
• The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data ProducersHanlin Li, Nicholas Vincent, Stevie Chancellor, Brent J. Hecht. 1151-1161 [doi]
• Going public: the role of public participation approaches in commercial AI labsLara Groves, Aidan Peppin, Andrew Strait, Jenny Brennan. 1162-1173 [doi]
• Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification BiasRobert Wolfe, Yiwei Yang 0009, Bill Howe, Aylin Caliskan. 1174-1185 [doi]
• Understanding accountability in algorithmic supply chainsJennifer Cobbe, Michael Veale, Jatinder Singh. 1186-1197 [doi]
• Explainability in AI Policies: A Critical Review of Communications, Reports, Regulations, and Standards in the EU, US, and UKLuca Nannini, Agathe Balayn, Adam Leon Smith. 1198-1212 [doi]
• Disentangling and Operationalizing AI Fairness at LinkedInJoaquin Quiñonero Candela, Yuwen Wu, Brian Hsu, Sakshi Jain, Jennifer Ramos, Jon Adams, Robert Hallman, Kinjal Basu 0001. 1213-1228 [doi]
• Enhancing AI fairness through impact assessment in the European Union: a legal and computer science perspectiveAlessandra Calvi, Dimitris Kotzinos. 1229-1245 [doi]
• "I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language GenerationAnaelia Ovalle, Palash Goyal, Jwala Dhamala, Zachary Jaggers, Kai-Wei Chang, Aram Galstyan, Richard S. Zemel, Rahul Gupta 0001. 1246-1266 [doi]
• AI Regulation Is (not) All You NeedLaura Lucaj, Patrick van der Smagt, Djalel Benbouzid. 1267-1279 [doi]
• Diverse Perspectives Can Mitigate Political Bias in Crowdsourced Content ModerationJacob Thebault-Spieker, Sukrit Venkatagiri, Naomi Mine, Kurt Luther. 1280-1291 [doi]
• The Devil is in the Details: Interrogating Values Embedded in the Allegheny Family Screening ToolMarissa Gerchick, Tobi Jegede, Tarak Shah, Ana Gutierrez, Sophie Beiers, Noam Shemtov, Kath Xu, Anjana Samant, Aaron Horowitz. 1292-1310 [doi]
• A Systematic Review of Ethics Disclosures in Predictive Mental Health ResearchLeah Hope Ajmani, Stevie Chancellor, Bijal Mehta, Casey Fiesler, Michael Zimmer 0004, Munmun De Choudhury. 1311-1323 [doi]
• An Empirical Analysis of Racial Categories in the Algorithmic Fairness LiteratureAmina A. Abdu, Irene V. Pasquetto, Abigail Z. Jacobs. 1324-1333 [doi]
• A Sociotechnical Audit: Assessing Police Use of Facial RecognitionEvani Radiya-Dixit, Gina Neff. 1334-1346 [doi]
• Fairer Together: Mitigating Disparate Exposure in Kemeny Rank AggregationKathleen Cachel, Elke A. Rundensteiner. 1347-1357 [doi]
• Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth SensitivityFaisal Hamman, Jiahao Chen 0001, Sanghamitra Dutta. 1358-1368 [doi]
• Towards a Science of Human-AI Decision Making: An Overview of Design Space in Empirical Human-Subject StudiesVivian Lai, Chacha Chen, Alison Smith-Renner, Q. Vera Liao, Chenhao Tan. 1369-1385 [doi]
• (Anti)-Intentional Harms: The Conceptual Pitfalls of Emotion AI in EducationNathalie DiBerardino, Luke Stark. 1386-1395 [doi]
• Organizational Governance of Emerging Technologies: AI Adoption in HealthcareJee Young Kim, William Boag, Freya Gulamali, Alifia Hasan, Henry David Jeffry Hogg, Mark Lifson, Deirdre K. Mulligan, Manesh Patel, Inioluwa Deborah Raji, Ajai Sehgal, Keo Shaw, Danny Tobey, Alexandra Valladares, David Vidal, Suresh Balu, Mark P. Sendak. 1396-1417 [doi]
• Navigating the Audit Landscape: A Framework for Developing Transparent and Auditable XRChris Norval, Richard Cloete, Jatinder Singh. 1418-1431 [doi]
• Group fairness without demographics using social networksDavid Liu, Virginie Do, Nicolas Usunier, Maximilian Nickel. 1432-1449 [doi]
• Taking Algorithms to Courts: A Relational Approach to Algorithmic AccountabilityJacob Metcalf, Ranjit Singh, Emanuel Moss, Emnet Tafesse, Elizabeth Anne Watkins. 1450-1462 [doi]
• Co-Designing for Transparency: Lessons from Building a Document Organization Tool in the Criminal Justice DomainHellina Hailu Nigatu, Lisa Pickoff-White, John F. Canny, Sarah E. Chasins. 1463-1478 [doi]
• Examining risks of racial biases in NLP tools for child protective servicesAnjalie Field, Amanda Coston, Nupoor Gandhi, Alexandra Chouldechova, Emily Putnam-Hornstein, David Steier, Yulia Tsvetkov. 1479-1492 [doi]
• Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large ScaleFederico Bianchi 0001, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou 0001, Aylin Caliskan. 1493-1504 [doi]
• What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFABMelissa D. McCradden, Oluwadara Odusi, Shalmali Joshi, Ismail Akrout, Kagiso Ndlovu, Ben Glocker, Gabriel Maicas, Xiaoxuan Liu, Mjaye Mazwi, Tee Garnett, Lauren Oakden-Rayner, Myrtede Alfred, Irvine Sihlahla, Oswa Shafei, Anna Goldenberg. 1505-1519 [doi]
• Personalized Pricing with Group Fairness ConstraintXin Chen 0026, Zexing Xu, Zishuo Zhao, Yuan Zhou. 1520-1530 [doi]
• Auditing Cross-Cultural Consistency of Human-Annotated Labels for Recommendation SystemsRock Yuren Pang, Jack Cenatempo, Franklyn Graham, Bridgette Kuehn, Maddy Whisenant, Portia K. Botchway, Katie Stone Perez, Allison Koenecke. 1531-1552 [doi]
• The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment InstrumentsMiri Zilka, Riccardo Fogliato, Jiri Hron, Bradley Butcher, Carolyn Ashurst, Adrian Weller. 1553-1569 [doi]
• The Misuse of AUC: What High Impact Risk Assessment Gets WrongKweku Kwegyir-Aggrey, Marissa Gerchick, Malika Mohan, Aaron Horowitz, Suresh Venkatasubramanian. 1570-1583 [doi]
• Counterfactual Prediction Under Outcome Measurement ErrorLuke Guerdan, Amanda Coston, Kenneth Holstein, Zhiwei Steven Wu. 1584-1598 [doi]
• Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning MethodsRaphael Poulain, Mirza Farhan Bin Tarek, Rahmatollah Beheshti. 1599-1608 [doi]
• Arbitrary Decisions are a Hidden Cost of Differentially Private TrainingBogdan Kulynych, Hsiang Hsu, Carmela Troncoso, Flávio P. Calmon. 1609-1623 [doi]
• Interrogating the T in FAccTEric Corbett, Emily Denton. 1624-1634 [doi]
• Reducing Access Disparities in Networks using Edge Augmentation✱Ashkan Bashardoust, Sorelle A. Friedler, Carlos Scheidegger, Blair D. Sullivan, Suresh Venkatasubramanian. 1635-1651 [doi]
• The Many Faces of Fairness: Exploring the Institutional Logics of Multistakeholder Microlending RecommendationJessie J. Smith, Anas Buhayh, Anushka Kathait, Pradeep Ragothaman, Nicholas Mattei, Robin Burke, Amy Voida. 1652-1663 [doi]
• Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and EquityJoshua Gardner, Renzhe Yu, Quan Nguyen 0003, Christopher Brooks 0001, René F. Kizilcec. 1664-1684 [doi]
• Help or Hinder? Evaluating the Impact of Fairness Metrics and Algorithms in Visualizations for Consensus RankingHilson Shrestha, Kathleen Cachel, Mallak Alkhathlan, Elke A. Rundensteiner, Lane Harrison. 1685-1698 [doi]
• Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification TasksKatelyn Mei, Sonia Fereidooni, Aylin Caliskan. 1699-1710 [doi]
• Representation, Self-Determination, and Refusal: Queer People's Experiences with Targeted AdvertisingPrincess Sampson, Ro Encarnacion, Danaë Metaxa. 1711-1722 [doi]
• Capturing Humans' Mental Models of AI: An Item Response Theory ApproachMarkelle Kelly, Aakriti Kumar, Padhraic Smyth, Mark Steyvers. 1723-1734 [doi]
• Representation Online Matters: Practical End-to-End Diversification in Search and Recommender SystemsPedro Silva 0010, Bhawna Juneja, Shloka Desai, Ashudeep Singh, Nadia Fawaz. 1735-1746 [doi]
• Using Supervised Learning to Estimate Inequality in the Size and Persistence of Income ShocksDavid Bruns-Smith, Avi Feller, Emi Nakamura. 1747-1756 [doi]
• Skin Deep: Investigating Subjectivity in Skin Tone Annotations for Computer Vision Benchmark DatasetsTeanna Barrett, Quanze Chen, Amy X. Zhang. 1757-1771 [doi]
• Discrimination through Image Selection by Job Advertisers on FacebookVarun Nagaraj Rao, Aleksandra Korolova. 1772-1788 [doi]
• On The Impact of Machine Learning Randomness on Group FairnessPrakhar Ganesh, Hongyan Chang, Martin Strobel 0001, Reza Shokri. 1789-1800 [doi]
• Detection and Mitigation of Algorithmic Bias via Predictive ParityCyrus DiCiccio, Brian Hsu, YinYin Yu, Preetam Nandy, Kinjal Basu 0001. 1801-1816 [doi]
• Fairness Auditing in Urban Decisions using LP-based Data CombinationJingyi Yang, Joel Miller, Mesrob Ohannessian. 1817-1825 [doi]
• The Slow Violence of Surveillance Capitalism: How Online Behavioral Advertising Harms PeopleYuxi Wu, Sydney Bice, W. Keith Edwards, Sauvik Das. 1826-1837 [doi]
• Bias as Boundary Object: Unpacking The Politics Of An Austerity Algorithm Using Bias FrameworksGabriel Grill, Fabian Fischer 0007, Florian Cech. 1838-1849 [doi]
• Legal Taxonomies of Machine Bias: Revisiting Direct DiscriminationReuben Binns, Jeremias Adams-Prassl, Aislinn Kelly-Lyth. 1850-1858 [doi]
• Achieving Diversity in Counterfactual Explanations: a Review and DiscussionThibault Laugel, Adulam Jeyasothy, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki. 1859-1869 [doi]
• Disparities in Text-to-Image Model Concept Possession Across LanguagesMichael Saxon, William Yang Wang. 1870 [doi]
• Reconciling Governmental Use of Online Targeting With DemocracyKatja Andric, Atoosa Kasirzadeh. 1871-1881 [doi]
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