Table of Contents

• Interdisciplinarity, Gender Diversity, and Network Structure Predict the Centrality of AI OrganizationsMadalina Vlasceanu, Miroslav Dudík, Ida Momennejad. 1-10 [doi]
• Dynamic Privacy Budget Allocation Improves Data Efficiency of Differentially Private Gradient DescentJunyuan Hong, Zhangyang Wang, Jiayu Zhou. 11-35 [doi]
• A Data-driven analysis of the interplay between Criminological theory and predictive policing algorithmsAdriane Chapman, Philip Grylls, Pamela Ugwudike, David Gammack, Jacqui Ayling. 36-45 [doi]
• #FuckTheAlgorithm: algorithmic imaginaries and political resistanceGarfield Benjamin. 46-57 [doi]
• Learning to Break Deep Perceptual Hashing: The Use Case NeuralHashLukas Struppek, Dominik Hintersdorf, Daniel Neider, Kristian Kersting. 58-69 [doi]
• Fairness Indicators for Systematic Assessments of Visual Feature ExtractorsPriya Goyal, Adriana Romero-Soriano, Caner Hazirbas, Levent Sagun, Nicolas Usunier. 70-88 [doi]
• FAccT-Check on AI regulation: Systematic Evaluation of AI Regulation on the Example of the Legislation on the Use of AI in the Public Sector in the German Federal State of Schleswig-HolsteinKatharina Simbeck. 89-96 [doi]
• News from Generative Artificial Intelligence Is Believed LessChiara Longoni, Andrey Fradkin, Luca Cian, Gordon Pennycook. 97-106 [doi]
• When learning becomes impossibleNicholas Asher, Julie Hunter. 107-116 [doi]
• Providing Item-side Individual Fairness for Deep Recommender SystemsXiuling Wang, Wendy Hui Wang. 117-127 [doi]
• What People Think AI Should Infer From FacesSeverin Engelmann, Chiara Ullstein, Orestis Papakyriakopoulos, Jens Grossklags. 128-141 [doi]
• Minimax Demographic Group Fairness in Federated LearningAfroditi Papadaki, Natalia Martínez, Martín Bertrán, Guillermo Sapiro, Miguel R. D. Rodrigues. 142-159 [doi]
• Automating Care: Online Food Delivery Work During the CoVID-19 Crisis in IndiaAnubha Singh, Tina Park. 160-172 [doi]
• The Values Encoded in Machine Learning ResearchAbeba Birhane, Pratyusha Kalluri, Dallas Card, William Agnew, Ravit Dotan, Michelle Bao. 173-184 [doi]
• AI Opacity and Explainability in Tort LitigationHenry Fraser, Rhyle Simcock, Aaron J. Snoswell. 185-196 [doi]
• Pareto-Improving Data-Sharing✱Ronen Gradwohl, Moshe Tennenholtz. 197-198 [doi]
• A Framework for Deprecating Datasets: Standardizing Documentation, Identification, and CommunicationAlexandra Sasha Luccioni, Frances Corry, Hamsini Sridharan, Mike Ananny, Jason Schultz, Kate Crawford 0002. 199-212 [doi]
• Treatment Effect Risk: Bounds and InferenceNathan Kallus. 213 [doi]
• Taxonomy of Risks posed by Language ModelsLaura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, Po-Sen Huang, John Mellor, Amelia Glaese, Myra Cheng, Borja Balle, Atoosa Kasirzadeh, Courtney Biles, Sasha Brown, Zac Kenton, Will Hawkins, Tom Stepleton, Abeba Birhane, Lisa Anne Hendricks, Laura Rimell, William S. Isaac, Julia Haas, Sean Legassick, Geoffrey Irving, Iason Gabriel. 214-229 [doi]
• Bias in Automated Speaker RecognitionWiebke Toussaint Hutiri, Aaron Yi Ding. 230-247 [doi]
• It's Just Not That Simple: An Empirical Study of the Accuracy-Explainability Trade-off in Machine Learning for Public PolicyAndrew Bell, Ian Solano-Kamaiko, Oded Nov, Julia Stoyanovich. 248-266 [doi]
• South Korean Public Value Coproduction Towards'AI for Humanity': A Synergy of Sociocultural Norms and Multistakeholder Deliberation in Bridging the Design and Implementation of National AI Ethics GuidelinesYou Jeen Ha. 267-277 [doi]
• Equitable Public Bus Network Optimization for Social Good: A Case Study of SingaporeDavid Alexander Tedjopurnomo, Zhifeng Bao, Farhana Murtaza Choudhury, Hui Luo, A. Kai Qin. 278-288 [doi]
• GetFair: Generalized Fairness Tuning of Classification ModelsSandipan Sikdar, Florian Lemmerich, Markus Strohmaier. 289-299 [doi]
• Social Inclusion in Curated Contexts: Insights from Museum PracticesHan-Yin Huang, Cynthia C. S. Liem. 300-309 [doi]
• How Different Groups Prioritize Ethical Values for Responsible AIMaurice Jakesch, Zana Buçinca, Saleema Amershi, Alexandra Olteanu. 310-323 [doi]
• Measuring Representational Harms in Image CaptioningAngelina Wang, Solon Barocas, Kristen Laird, Hanna M. Wallach. 324-335 [doi]
• Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing EvaluationAngelina Wang, Vikram V. Ramaswamy, Olga Russakovsky. 336-349 [doi]
• An Outcome Test of Discrimination for Ranked ListsJonathan Roth, Guillaume Saint-Jacques, YinYin Yu. 350-356 [doi]
• Causal Inference Struggles with Agency on Online PlatformsSmitha Milli, Luca Belli, Moritz Hardt. 357-365 [doi]
• Flipping the Script on Criminal Justice Risk Assessment: An actuarial model for assessing the risk the federal sentencing system poses to defendantsMikaela Meyer, Aaron Horowitz, Erica Marshall, Kristian Lum. 366-378 [doi]
• De-biasing "bias" measurementKristian Lum, Yunfeng Zhang, Amanda Bower. 379-389 [doi]
• Mind the Gap: Autonomous Systems, the Responsibility Gap, and Moral EntanglementTrystan S. Goetze. 390-400 [doi]
• Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future ProspectsBenjamin Laufer, Sameer Jain, A. Feder Cooper, Jon M. Kleinberg, Hoda Heidari. 401-426 [doi]
• Interactive Model Cards: A Human-Centered Approach to Model DocumentationAnamaria Crisan, Margaret Drouhard, Jesse Vig, Nazneen Rajani. 427-439 [doi]
• The Model Card Authoring Toolkit: Toward Community-centered, Deliberation-driven AI DesignHong Shen, Leijie Wang, Wesley H. Deng, Ciell Brusse, Ronald Velgersdijk, Haiyi Zhu. 440-451 [doi]
• Tech Worker Organizing for Power and AccountabilityWilliam Boag, Harini Suresh, Bianca Lepe, Catherine D'Ignazio. 452-463 [doi]
• Equi-explanation Maps: Concise and Informative Global Summary ExplanationsTanya Chowdhury, Razieh Rahimi, James Allan. 464-472 [doi]
• Exploring How Machine Learning Practitioners (Try To) Use Fairness ToolkitsWesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee, Jatinder Singh, Zhiwei Steven Wu, Kenneth Holstein, Haiyi Zhu. 473-484 [doi]
• Are "Intersectionally Fair" AI Algorithms Really Fair to Women of Color? A Philosophical AnalysisYoujin Kong. 485-494 [doi]
• Affirmative Algorithms: Relational Equality as Algorithmic FairnessMarilyn Zhang. 495-507 [doi]
• Goodbye Tracking? Impact of iOS App Tracking Transparency and Privacy LabelsKonrad Kollnig, Anastasia Shuba, Max Van Kleek, Reuben Binns, Nigel Shadbolt. 508-520 [doi]
• Language variation and algorithmic bias: understanding algorithmic bias in British English automatic speech recognitionNina Markl. 521-534 [doi]
• Towards a multi-stakeholder value-based assessment framework for algorithmic systemsMireia Yurrita, Dave Murray-Rust, Agathe Balayn, Alessandro Bozzon. 535-563 [doi]
• Ethical Concerns and Perceptions of Consumer Neurotechnology from Lived Experiences of Mental Workload TrackingSerena Midha, Max L. Wilson 0001, Sarah Sharples. 564-573 [doi]
• Best vs. All: Equity and Accuracy of Standardized Test Score ReportingMingzi Niu, Sampath Kannan, Aaron Roth 0001, Rakesh Vohra. 574-586 [doi]
• REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning ResearchJessie J. Smith, Saleema Amershi, Solon Barocas, Hanna Wallach, Jennifer Wortman Vaughan. 587-597 [doi]
• Normative Logics of Algorithmic AccountabilityJoseph Donia. 598 [doi]
• Selection in the Presence of Implicit Bias: The Advantage of Intersectional ConstraintsAnay Mehrotra, Bary S. R. Pradelski, Nisheeth K. Vishnoi. 599-609 [doi]
• Fairness for AUC via Feature AugmentationHortense Fong, Vineet Kumar 0006, Anay Mehrotra, Nisheeth K. Vishnoi. 610 [doi]
• Human Interpretation of Saliency-based Explanation Over TextHendrik Schuff, Alon Jacovi, Heike Adel, Yoav Goldberg, Ngoc Thang Vu. 611-636 [doi]
• Subverting Fair Image Search with Generative Adversarial PerturbationsAvijit Ghosh, Matthew Jagielski, Christo Wilson. 637-650 [doi]
• Don't let Ricci v. DeStefano Hold You Back: A Bias-Aware Legal Solution to the Hiring ParadoxJad Salem, Deven Desai, Swati Gupta. 651-666 [doi]
• Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata CollectionHarini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, Catherine D'Ignazio. 667-678 [doi]
• Disclosure by Design: Designing information disclosures to support meaningful transparency and accountabilityChris Norval, Kristin Cornelius, Jennifer Cobbe, Jatinder Singh. 679-690 [doi]
• The Death of the Legal Subject: How Predictive Algorithms Are (Re)constructing Legal SubjectivityKatrina Geddes. 691-701 [doi]
• Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking TheoryHarmanpreet Kaur, Eytan Adar, Eric Gilbert, Cliff Lampe. 702-714 [doi]
• Achieving Fairness via Post-Processing in Web-Scale Recommender Systems✱Preetam Nandy, Cyrus DiCiccio, Divya Venugopalan, Heloise Logan, Kinjal Basu 0001, Noureddine El Karoui. 715-725 [doi]
• Making the Unaccountable Internet: The Changing Meaning of Accounting in the Early ARPANETA. Feder Cooper, Gili Vidan. 726-742 [doi]
• Robots Enact Malignant StereotypesAndrew Hundt, William Agnew, Vicky Zeng, Severin Kacianka, Matthew Gombolay. 743-756 [doi]
• Attribute Privacy: Framework and MechanismsWanrong Zhang 0001, Olga Ohrimenko, Rachel Cummings. 757-766 [doi]
• Imperfect Inferences: A Practical AssessmentAaron Rieke, Vincent Southerland, Dan Svirsky, Mingwei Hsu. 767-777 [doi]
• Behavioral Use Licensing for Responsible AIDanish Contractor, Daniel McDuff, Julia Katherine Haines, Jenny Lee, Christopher Hines, Brent Hecht, Nicholas Vincent, Hanlin Li. 778-788 [doi]
• Exploring the Role of Grammar and Word Choice in Bias Toward African American English (AAE) in Hate Speech ClassificationCamille Harris, Matan Halevy, Ayanna Howard, Amy Bruckman, Diyi Yang. 789-798 [doi]
• Trucks Don't Mean Trump: Diagnosing Human Error in Image AnalysisJ. D. Zamfirescu-Pereira, Jerry Chen, Emily Wen, Allison Koenecke, Nikhil Garg, Emma Pierson. 799-813 [doi]
• Fair Representation Clustering with Several Protected ClassesZhen Dai, Yury Makarychev, Ali Vakilian. 814-823 [doi]
• How are ML-Based Online Content Moderation Systems Actually Used? Studying Community Size, Local Activity, and Disparate TreatmentLeijie Wang, Haiyi Zhu. 824-838 [doi]
• Learning to Limit Data Collection via Scaling Laws: A Computational Interpretation for the Legal Principle of Data MinimizationDivya Shanmugam, Fernando Diaz 0001, Samira Shabanian, Michele Finck, Asia Biega. 839-849 [doi]
• Model Multiplicity: Opportunities, Concerns, and SolutionsEmily Black, Manish Raghavan, Solon Barocas. 850-863 [doi]
• Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine LearningA. Feder Cooper, Emanuel Moss, Benjamin Laufer, Helen Nissenbaum. 864-876 [doi]
• Promoting Ethical Awareness in Communication Analysis: Investigating Potentials and Limits of Visual Analytics for Intelligence ApplicationsMaximilian T. Fischer, Simon David Hirsbrunner, Wolfgang Jentner, Matthias Miller, Daniel A. Keim, Paula Helm. 877-889 [doi]
• On the Fairness of Machine-Assisted Human DecisionsBryce McLaughlin, Jann Spiess, Talia Gillis. 890 [doi]
• Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial ContextsSebastian Bordt, Michèle Finck, Eric Raidl, Ulrike von Luxburg. 891-905 [doi]
• Multi-disciplinary fairness considerations in machine learning for clinical trialsIsabel Chien, Nina Deliu, Richard Turner, Adrian Weller, Sofia Villar, Niki Kilbertus. 906-924 [doi]
• Prediction as Extraction of DiscretionSun-ha Hong. 925-934 [doi]
• German AI Start-Ups and "AI Ethics": Using A Social Practice Lens for Assessing and Implementing Socio-Technical InnovationMona Sloane, Janina Zakrzewski. 935-947 [doi]
• The Forgotten Margins of AI EthicsAbeba Birhane, Elayne Ruane, Thomas Laurent 0003, Matthew S. Brown, Johnathan Flowers, Anthony Ventresque, Christopher L. Dancy. 948-958 [doi]
• The Fallacy of AI FunctionalityInioluwa Deborah Raji, I. Elizabeth Kumar, Aaron Horowitz, Andrew D. Selbst. 959-972 [doi]
• Female, white, 27? Bias Evaluation on Data and Algorithms for Affect Recognition in FacesJaspar Pahl, Ines Rieger, Anna Möller, Thomas Wittenberg, Ute Schmid. 973-987 [doi]
• Beyond Fairness: Reparative Algorithms to Address Historical Injustices of Housing Discrimination in the USWonyoung So, Pranay Lohia, Rakesh Pimplikar, A. E. Hosoi, Catherine D'Ignazio. 988-1004 [doi]
• Subverting machines, fluctuating identities: Re-learning human categorizationChristina Lu, Jackie Kay, Kevin McKee. 1005-1015 [doi]
• Models for Classifying AI Systems: the Switch, the Ladder, and the MatrixJakob Mökander, Margi Sheth, David Watson, Luciano Floridi. 1016 [doi]
• Regulating Facial Processing Technologies: Tensions Between Legal and Technical Considerations in the Application of Illinois BIPARui-Jie Yew, Alice Xiang. 1017-1027 [doi]
• A Data-Driven Simulation of the New York State Foster Care SystemYuhao Du, Stefania Ionescu, Melanie Sage, Kenneth Joseph. 1028-1038 [doi]
• Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcareStephen Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins, Nigam Shah. 1039-1052 [doi]
• FADE: FAir Double Ensemble Learning for Observable and Counterfactual OutcomesAlan Mishler, Edward H. Kennedy. 1053 [doi]
• Counterfactual Shapley Additive ExplanationsEmanuele Albini, Jason Long, Danial Dervovic, Daniele Magazzeni. 1054-1070 [doi]
• Tackling Algorithmic Disability Discrimination in the Hiring Process: An Ethical, Legal and Technical AnalysisMaarten Buyl, Christina Cociancig, Cristina Frattone, Nele Roekens. 1071-1082 [doi]
• Rational Shapley ValuesDavid Watson. 1083-1094 [doi]
• Trade-offs between Group Fairness Metrics in Societal Resource AllocationTasfia Mashiat, Xavier Gitiaux, Huzefa Rangwala, Patrick Fowler, Sanmay Das. 1095-1105 [doi]
• An Algorithmic Framework for Bias BountiesIra Globus-Harris, Michael Kearns, Aaron Roth 0001. 1106-1124 [doi]
• Auditing for Gerrymandering by Identifying Disenfranchised IndividualsJerry Lin, Carolyn Chen, Marc Chmielewski, Samia Zaman, Brandon Fain. 1125-1135 [doi]
• Smallset Timelines: A Visual Representation of Data Preprocessing DecisionsLydia R. Lucchesi, Petra M. Kuhnert, Jenny L. Davis, Lexing Xie. 1136-1153 [doi]
• Brain Computer Interfaces and Human Rights: Brave new rights for a brave new worldMarietjie Wilhelmina Maria Botes. 1154-1161 [doi]
• Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholdersLogan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alexandra Chouldechova, Ken Holstein, Zhiwei Steven Wu, Haiyi Zhu. 1162-1177 [doi]
• Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing PipelineAvrim Blum, Kevin Stangl, Ali Vakilian. 1178-1193 [doi]
• The Road to Explainability is Paved with Bias: Measuring the Fairness of ExplanationsAparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh Ghassemi. 1194-1206 [doi]
• Multiaccurate Proxies for Downstream FairnessEmily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth 0001, Saeed Sharifi-Malvajerdi. 1207-1239 [doi]
• Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services DeliveryAida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud, Eric Rice. 1240-1256 [doi]
• Designing for Responsible Trust in AI Systems: A Communication PerspectiveQ. Vera Liao, S. Shyam Sundar. 1257-1268 [doi]
• Markedness in Visual Semantic AIRobert Wolfe, Aylin Caliskan. 1269-1279 [doi]
• Gender and Racial Bias in Visual Question Answering DatasetsYusuke Hirota, Yuta Nakashima, Noa Garcia. 1280-1292 [doi]
• Evidence for Hypodescent in Visual Semantic AIRobert Wolfe, Mahzarin R. Banaji, Aylin Caliskan. 1293-1304 [doi]
• The Algorithmic ImprintUpol Ehsan, Ranjit Singh, Jacob Metcalf, Mark Riedl. 1305-1317 [doi]
• DualCF: Efficient Model Extraction Attack from Counterfactual ExplanationsYongJie Wang, Hangwei Qian, Chunyan Miao. 1318-1329 [doi]
• Why Am I Not Seeing It? Understanding Users' Needs for Counterfactual Explanations in Everyday RecommendationsRuoxi Shang, K. J. Kevin Feng, Chirag Shah. 1330-1340 [doi]
• The Case for a Legal Compliance API for the Enforcement of the EU's Digital Services Act on Social Media PlatformsCatalina Goanta, Thales Bertaglia, Adriana Iamnitchi. 1341-1349 [doi]
• Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?Patrick Schramowski, Christopher Tauchmann, Kristian Kersting. 1350-1361 [doi]
• Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical ImagingRiccardo Fogliato, Shreya Chappidi, Matthew Lungren, Paul Fisher, Diane Wilson, Michael Fitzke, Mark Parkinson, Eric Horvitz, Kori Inkpen, Besmira Nushi. 1362-1374 [doi]
• Confronting Power and Corporate Capture at the FAccT ConferenceMeg Young, Michael Katell, P. M. Krafft. 1375-1386 [doi]
• The Alchemy of Trust: The Creative Act of Designing Trustworthy Socio-Technical SystemsLauren Thornton, Bran Knowles, Gordon Blair. 1387-1398 [doi]
• Towards Fair Unsupervised LearningFrancois Buet-Golfouse, Islam Utyagulov. 1399-1409 [doi]
• Decision Time: Normative Dimensions of Algorithmic SpeedDaniel Susser. 1410-1420 [doi]
• Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision MakingMiriam Rateike, Ayan Majumdar, Olga Mineeva, Krishna P. Gummadi, Isabel Valera. 1421-1433 [doi]
• At the Tensions of South and North: Critical Roles of Global South Stakeholders in AI GovernanceMarie-Therese Png. 1434-1445 [doi]
• Accountable Data: The Politics and Pragmatics of Disclosure DatasetsLindsay Poirier. 1446-1456 [doi]
• How Explainability Contributes to Trust in AIAndrea Ferrario, Michele Loi. 1457-1466 [doi]
• Adaptive Sampling Strategies to Construct Equitable Training DatasetsWilliam Cai, Ro Encarnacion, Bobbie Chern, Sam Corbett-Davies, Miranda Bogen, Stevie Bergman, Sharad Goel. 1467-1478 [doi]
• Algorithmic Fairness and Vertical Equity: Income Fairness with IRS Tax Audit ModelsEmily Black, Hadi Elzayn, Alexandra Chouldechova, Jacob Goldin, Daniel Ho. 1479-1503 [doi]
• Justice in Misinformation Detection Systems: An Analysis of Algorithms, Stakeholders, and Potential HarmsTerrence Neumann, Maria De-Arteaga, Sina Fazelpour. 1504-1515 [doi]
• Should attention be all we need? The epistemic and ethical implications of unification in machine learningNic Fishman, Leif Hancox-Li. 1516-1527 [doi]
• Critical Tools for Machine Learning: Working with Intersectional Critical Concepts in Machine Learning Systems DesignGoda Klumbyte, Claude Draude, Alex S. Taylor. 1528-1541 [doi]
• On the Power of Randomization in Fair Classification and RepresentationSushant Agarwal, Amit Deshpande. 1542-1551 [doi]
• ABCinML: Anticipatory Bias Correction in Machine Learning ApplicationsAbdulaziz A. Almuzaini, Chidansh A. Bhatt, David M. Pennock, Vivek K. Singh. 1552-1560 [doi]
• Algorithms Off-limits?: If digital trade law restricts access to source code of software then accountability will sufferKristina Irion. 1561-1570 [doi]
• Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystemSasha Costanza-Chock, Inioluwa Deborah Raji, Joy Buolamwini. 1571-1583 [doi]
• System Safety and Artificial IntelligenceRoel Dobbe. 1584 [doi]
• Assessing Annotator Identity Sensitivity via Item Response Theory: A Case Study in a Hate Speech CorpusPratik S. Sachdeva, Renata Barreto, Claudia von Vacano, Chris J. Kennedy. 1585-1603 [doi]
• Surfacing Racial Stereotypes through Identity PortrayalGauri Kambhatla, Ian Stewart, Rada Mihalcea. 1604-1615 [doi]
• "There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-MakingJakob Schoeffer, Niklas Kuehl, Yvette Machowski. 1616-1628 [doi]
• Characterizing Properties and Trade-offs of Centralized Delegation Mechanisms in Liquid DemocracyBrian Brubach, Audrey Ballarin, Heeba Nazeer. 1629-1638 [doi]
• Human-Algorithm Collaboration: Achieving Complementarity and Avoiding UnfairnessKate Donahue, Alexandra Chouldechova, Krishnaram Kenthapadi. 1639-1656 [doi]
• Stop the Spread: A Contextual Integrity Perspective on the Appropriateness of COVID-19 Vaccination CertificatesShikun Zhang, Yan Shvartzshnaider, Yuanyuan Feng, Helen Nissenbaum, Norman Sadeh. 1657-1670 [doi]
• What is the Bureaucratic Counterfactual? Categorical versus Algorithmic Prioritization in U.S. Social PolicyRebecca Ann Johnson, Simone Zhang. 1671-1682 [doi]
• NeuroView-RNN: It's About TimeCj Barberan, Sina Alemmohammad, Naiming Liu, Randall Balestriero, Richard Baraniuk. 1683-1697 [doi]
• Fairness-aware Model-agnostic Positive and Unlabeled LearningZiwei Wu, Jingrui He. 1698-1708 [doi]
• Demographic-Reliant Algorithmic Fairness: Characterizing the Risks of Demographic Data Collection in the Pursuit of FairnessMcKane Andrus, Sarah Villeneuve. 1709-1721 [doi]
• Testing Concerns about Technology's Behavioral Impacts with N-of-one TrialsNathan Matias, Eric Pennington, Zenobia Chan. 1722-1732 [doi]
• Adversarial Scrutiny of Evidentiary Statistical SoftwareRediet Abebe, Moritz Hardt, Angela Jin, John Miller 0001, Ludwig Schmidt, Rebecca Wexler. 1733-1746 [doi]
• Predictability and Surprise in Large Generative ModelsDeep Ganguli, Danny Hernandez, Liane Lovitt, Amanda Askell, Yuntao Bai, Anna Chen, Tom Conerly, Nova DasSarma, Dawn Drain, Nelson Elhage, Sheer El Showk, Stanislav Fort, Zac Hatfield-Dodds, Tom Henighan, Scott Johnston, Andy Jones, Nicholas Joseph, Jackson Kernian, Shauna Kravec, Ben Mann, Neel Nanda, Kamal Ndousse, Catherine Olsson, Daniela Amodei, Tom Brown, Jared Kaplan, Sam McCandlish, Christopher Olah, Dario Amodei, Jack Clark. 1747-1764 [doi]
• Models for understanding and quantifying feedback in societal systemsLydia Reader, Pegah Nokhiz, Cathleen Power, Neal Patwari, Suresh Venkatasubramanian, Sorelle Friedler. 1765-1775 [doi]
• Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AIMahima Pushkarna, Andrew Zaldivar, Oddur Kjartansson. 1776-1826 [doi]
• On the Existence of Simpler Machine Learning ModelsLesia Semenova, Cynthia Rudin, Ronald Parr. 1827-1858 [doi]
• Evaluation Gaps in Machine Learning PracticeBen Hutchinson, Negar Rostamzadeh, Christina Greer, Katherine Heller, Vinodkumar Prabhakaran. 1859-1876 [doi]
• Measuring the Carbon Intensity of AI in Cloud InstancesJesse Dodge, Taylor Prewitt, Remi Tachet des Combes, Erika Odmark, Roy Schwartz 0001, Emma Strubell, Alexandra Sasha Luccioni, Noah A. Smith, Nicole DeCario, Will Buchanan. 1877-1894 [doi]
• Model Explanations with Differential PrivacyNeel Patel, Reza Shokri, Yair Zick. 1895-1904 [doi]
• Marrying Fairness and Explainability in Supervised LearningPrzemyslaw A. Grabowicz, Nicholas Perello, Aarshee Mishra. 1905-1916 [doi]
• 'We can't find fault with a friend': The Mediation of Accountability on Instant Loan Platforms in IndiaDivya Ramesh, Vaishnav Kameswaran, Ding Wang, Nithya Sambasivan. 1917-1928 [doi]
• Fair ranking: a critical review, challenges, and future directionsGourab K. Patro, Lorenzo Porcaro, Laura Mitchell, Qiuyue Zhang, Meike Zehlike, Nikhil Garg. 1929-1942 [doi]
• Healthsheet: Development of a Transparency Artifact for Health DatasetsNegar Rostamzadeh, Diana Mincu, Subhrajit Roy, Andrew Smart, Lauren Wilcox, Mahima Pushkarna, Jessica Schrouff, Razvan Amironesei, Nyalleng Moorosi, Katherine Heller. 1943-1961 [doi]
• The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning ModelsGreg d'Eon, Jason d'Eon, James R. Wright, Kevin Leyton-Brown. 1962-1981 [doi]
• CounterFAccTual: How FAccT Undermines Its Organizing PrinciplesBen Gansky, Sean McDonald. 1982-1992 [doi]
• What is Proxy Discrimination?Michael Carl Tschantz. 1993-2003 [doi]
• Uncertainty and the Social Planner's Problem: Why Sample Complexity MattersCyrus Cousins. 2004-2015 [doi]
• Reliable and Safe Use of Machine Translation in Medical SettingsNikita Mehandru, Samantha Robertson, Niloufar Salehi. 2016-2025 [doi]
• Is calibration a fairness requirement?: An argument from the point of view of moral philosophy and decision theoryMichele Loi, Christoph Heitz. 2026-2034 [doi]
• Limits and Possibilities for "Ethical AI" in Open Source: A Study of DeepfakesDavid Gray Widder, Dawn Nafus, Laura Dabbish, James Herbsleb. 2035-2046 [doi]
• AI Ethics Statements: Analysis and Lessons Learnt from NeurIPS Broader Impact StatementsCarolyn Ashurst, Emmie Hine, Paul Sedille, Alexis Carlier. 2047-2056 [doi]
• Disentangling the Components of Ethical Research in Machine LearningCarolyn Ashurst, Solon Barocas, Rosie Campbell, Deborah Raji. 2057-2068 [doi]
• Designing Up with Value-Sensitive Design: Building a Field Guide for Ethical ML DevelopmentKaren Boyd. 2069-2082 [doi]
• Theories of "Gender" in NLP Bias ResearchHannah Devinney, Jenny Björklund, Henrik Björklund. 2083-2102 [doi]
• The Conflict Between Explainable and Accountable Decision-Making AlgorithmsGabriel Lima, Nina Grgic-Hlaca, Jin Keun Jeong, Meeyoung Cha. 2103-2113 [doi]
• The Effects of Crowd Worker Biases in Fact-Checking TasksTim Draws, David La Barbera, Michael Soprano, Kevin Roitero, Davide Ceolin, Alessandro Checco, Stefano Mizzaro. 2114-2124 [doi]
• Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract SettingUlrike Kuhl, André Artelt, Barbara Hammer. 2125-2137 [doi]
• Algorithmic Tools in Public Employment Services: Towards a Jobseeker-Centric PerspectiveKristen M. Scott, Sonja Mei Wang, Milagros Miceli, Pieter Delobelle, Karolina Sztandar-Sztanderska, Bettina Berendt. 2138-2148 [doi]
• Promoting Fairness in Learned Models by Learning to Active Learn under Parity ConstraintsAmr Sharaf, Hal Daume III, Renkun Ni. 2149-2156 [doi]
• Fast online ranking with fairness of exposureNicolas Usunier, Virginie Do, Elvis Dohmatob. 2157-2167 [doi]
• From Demo to Design in Teaching Machine LearningKarl-Emi Kjær Bilstrup, Magnus Høholt Kaspersen, Ira Assent, Simon Enni, Marianne Graves Petersen. 2168-2178 [doi]
• The Long Arc of Fairness: Formalisations and Ethical DiscoursePola Schwöbel, Peter Remmers. 2179-2188 [doi]
• Seeing without Looking: Analysis Pipeline for Child Sexual Abuse DatasetsCamila Laranjeira da Silva, Joao Macedo, Sandra Avila, Jefersson dos Santos. 2189-2205 [doi]
• Data Governance in the Age of Large-Scale Data-Driven Language TechnologyYacine Jernite, Huu Nguyen, Stella Biderman, Anna Rogers, Maraim Masoud, Valentin Danchev, Samson Tan, Alexandra Sasha Luccioni, Nishant Subramani, Isaac Johnson, Gerard Dupont, Jesse Dodge, Kyle Lo, Zeerak Talat, Dragomir Radev, Aaron Gokaslan, Somaieh Nikpoor, Peter Henderson 0002, Rishi Bommasani, Margaret Mitchell. 2206-2222 [doi]
• Understanding and Being Understood: User Strategies for Identifying and Recovering From Mistranslations in Machine Translation-Mediated ChatSamantha Robertson, Mark Díaz. 2223-2238 [doi]
• A Review of Taxonomies of Explainable Artificial Intelligence (XAI) MethodsTimo Speith. 2239-2250 [doi]
• Limits of Individual Consent and Models of Distributed Consent in Online Social NetworksJuniper L. Lovato, Antoine Allard, Randall Harp, Jeremiah Onaolapo, Laurent Hébert-Dufresne. 2251-2262 [doi]
• Measuring Fairness of Rankings under Noisy Sensitive InformationAzin Ghazimatin, Matthaus Kleindessner, Chris Russell 0001, Ziawasch Abedjan, Jacek Golebiowski. 2263-2279 [doi]
• What Does it Mean for a Language Model to Preserve Privacy?Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, Florian Tramèr. 2280-2292 [doi]
• People are not coins: Morally distinct types of predictions necessitate different fairness constraintsEleonora Viganò, Corinna Hertweck, Christoph Heitz, Michele Loi. 2293-2301 [doi]
• Data augmentation for fairness-aware machine learning: Preventing algorithmic bias in law enforcement systemsIoannis Pastaltzidis, Nikolaos Dimitriou, Katherine Quezada-Tavarez, Stergios Aidinlis, Thomas Marquenie, Agata Gurzawska, Dimitrios Tzovaras. 2302-2314 [doi]
• Enforcing Group Fairness in Algorithmic Decision Making: Utility Maximization Under SufficiencyJoachim Baumann 0002, Anikó Hannák, Christoph Heitz. 2315-2326 [doi]
• Locality of Technical Objects and the Role of Structural Interventions for Systemic ChangeEfrén Cruz Cortés, Sarah Rajtmajer, Debashis Ghosh. 2327-2341 [doi]
• CrowdWorkSheets: Accounting for Individual and Collective Identities Underlying Crowdsourced Dataset AnnotationMark Díaz, Ian D. Kivlichan, Rachel Rosen, Dylan K. Baker, Razvan Amironesei, Vinodkumar Prabhakaran, Emily Denton. 2342-2351 [doi]