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ORCIDFAccT 2023: Chicago, IL, USA
- Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, FAccT 2023, Chicago, IL, USA, June 12-15, 2023. ACM 2023
- Chacha Chen
, Shi Feng, Amit Sharma, Chenhao Tan:
Machine Explanations and Human Understanding. 1 - Ajay Divakaran, Aparna Sridhar, Ramya Srinivasan:
Broadening AI Ethics Narratives: An Indic Art View. 2-11 - Joyce Zhou, Thorsten Joachims:
How to Explain and Justify Almost Any Decision: Potential Pitfalls for Accountability in AI Decision-Making. 12-21 - Konrad Kollnig, Siddhartha Datta, Thomas Serban Von Davier, Max Van Kleek, Reuben Binns, Ulrik Lyngs, Nigel Shadbolt:
'We are adults and deserve control of our phones': Examining the risks and opportunities of a right to repair for mobile apps. 22-34 - Bilel Benbouzid:
Fairness in machine learning from the perspective of sociology of statistics: How machine learning is becoming scientific by turning its back on metrological realism. 35-43 - Jakob Mainz, Lauritz Aastrup Munch, Jens Christian Bjerring:
Two Reasons for Subjecting Medical AI Systems to Lower Standards than Humans. 44-49 - Benjamin Laufer, Thomas Krendl Gilbert, Helen Nissenbaum:
Optimization's Neglected Normative Commitments. 50-63 - Devesh Narayanan:
Welfarist Moral Grounding for Transparent AI. 64-76 - Sunnie S. Y. Kim, Elizabeth Anne Watkins, Olga Russakovsky, Ruth Fong, Andrés Monroy-Hernández:
Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application. 77-88 - Arjun Roy, Jan Horstmann, Eirini Ntoutsi:
Multi-dimensional Discrimination in Law and Machine Learning - A Comparative Overview. 89-100 - Aaron Roth, Alexander Tolbert, Scott Weinstein:
Reconciling Individual Probability Forecasts✱. 101-110 - Irene Solaiman:
The Gradient of Generative AI Release: Methods and Considerations. 111-122 - Yuxin Xiao, Shulammite Lim, Tom Joseph Pollard, Marzyeh Ghassemi:
In the Name of Fairness: Assessing the Bias in Clinical Record De-identification. 123-137 - Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel:
"How Biased are Your Features?": Computing Fairness Influence Functions with Global Sensitivity Analysis. 138-148 - Zichong Wang, Nripsuta Saxena, Tongjia Yu, Sneha Karki, Tyler Zetty, Israat Haque, Shan Zhou, Dukka Kc, Ian Stockwell, Xuyu Wang, Albert Bifet, Wenbin Zhang:
Preventing Discriminatory Decision-making in Evolving Data Streams. 149-159 - Ali Akbar Septiandri, Marios Constantinides, Mohammad Tahaei, Daniele Quercia:
WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT? 160-171 - Bran Knowles, Jasmine Fledderjohann, John T. Richards, Kush R. Varshney:
Trustworthy AI and the Logics of Intersectional Resistance. 172-182 - Nandana Sengupta, Ashwini Vaidya, James A. Evans:
In her Shoes: Gendered Labelling in Crowdsourced Safety Perceptions Data from India. 183-192 - Anna P. Meyer, Aws Albarghouthi, Loris D'Antoni:
The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions. 193-204 - Vinitha Gadiraju, Shaun K. Kane, Sunipa Dev, Alex S. Taylor, Ding Wang, Emily Denton, Robin Brewer:
"I wouldn't say offensive but...": Disability-Centered Perspectives on Large Language Models. 205-216 - Sanna J. Ali, Angèle Christin, Andrew Smart, Riitta Katila:
Walking the Walk of AI Ethics: Organizational Challenges and the Individualization of Risk among Ethics Entrepreneurs. 217-226 - José Pablo Lapostol Piderit, Romina Garrido Iglesias, María Paz Hermosilla Cornejo:
Algorithmic Transparency from the South: Examining the state of algorithmic transparency in Chile's public administration algorithms. 227-235 - Gabriel Lima, Nina Grgic-Hlaca, Jin Keun Jeong, Meeyoung Cha:
Who Should Pay When Machines Cause Harm? Laypeople's Expectations of Legal Damages for Machine-Caused Harm. 236-246 - Alon Jacovi, Jasmijn Bastings, Sebastian Gehrmann, Yoav Goldberg, Katja Filippova:
Diagnosing AI Explanation Methods with Folk Concepts of Behavior. 247 - Nicolas Scharowski, Michaela Benk, Swen J. Kühne, Léane Wettstein, Florian Brühlmann:
Certification Labels for Trustworthy AI: Insights From an Empirical Mixed-Method Study. 248-260 - Will Hawkins, Brent D. Mittelstadt:
The ethical ambiguity of AI data enrichment: Measuring gaps in research ethics norms and practices. 261-270 - Borhane Blili-Hamelin, Leif Hancox-Li:
Making Intelligence: Ethical Values in IQ and ML Benchmarks. 271-284 - Angie W. Boggust, Harini Suresh, Hendrik Strobelt, John V. Guttag, Arvind Satyanarayan:
Saliency Cards: A Framework to Characterize and Compare Saliency Methods. 285-296 - Jamelle Watson-Daniels, Solon Barocas, Jake M. Hofman, Alexandra Chouldechova:
Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints. 297-311 - Dasha Pruss:
Ghosting the Machine: Judicial Resistance to a Recidivism Risk Assessment Instrument. 312-323 - Jenny L. Davis:
'Affordances' for Machine Learning. 324-332 - Tim Miller:
Explainable AI is Dead, Long Live Explainable AI!: Hypothesis-driven Decision Support using Evaluative AI. 333-342 - Giada Pistilli, Carlos Muñoz Ferrandis, Yacine Jernite, Margaret Mitchell:
Stronger Together: on the Articulation of Ethical Charters, Legal Tools, and Technical Documentation in ML. 343-354 - Samuel James Bell, Levent Sagun:
Simplicity Bias Leads to Amplified Performance Disparities. 355-369 - Laura Cabello, Anna Katrine Jørgensen, Anders Søgaard:
On the Independence of Association Bias and Empirical Fairness in Language Models. 370-378 - Robin N. Brewer, Christina N. Harrington, Courtney Heldreth:
Envisioning Equitable Speech Technologies for Black Older Adults. 379-388 - Andrew Estornell, Sanmay Das, Yang Liu, Yevgeniy Vorobeychik:
Group-Fair Classification with Strategic Agents. 389-399 - Andrew Bell, Lucius Bynum, Nazarii Drushchak, Tetiana Zakharchenko, Lucas Rosenblatt, Julia Stoyanovich:
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice. 400-422 - José M. Álvarez, Kristen M. Scott, Bettina Berendt, Salvatore Ruggieri:
Domain Adaptive Decision Trees: Implications for Accuracy and Fairness. 423-433 - Amélie Marian:
Algorithmic Transparency and Accountability through Crowdsourcing: A Study of the NYC School Admission Lottery. 434-443 - Florian Eyert, Paola Lopez:
Rethinking Transparency as a Communicative Constellation. 444-454 - Edward B. Kang:
On the Praxes and Politics of AI Speech Emotion Recognition. 455-466 - David Gray Widder, Derrick Zhen, Laura Dabbish, James D. Herbsleb:
It's about power: What ethical concerns do software engineers have, and what do they (feel they can) do about them? 467-479 - Terrence Neumann, Nicholas Wolczynski:
Does AI-Assisted Fact-Checking Disproportionately Benefit Majority Groups Online? 480-490 - Bogdana Rakova, Roel Dobbe:
Algorithms as Social-Ecological-Technological Systems: an Environmental Justice Lens on Algorithmic Audits. 491 - Jennifer King, Daniel E. Ho, Arushi Gupta, Victor Wu, Helen Webley-Brown:
The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in U.S. Government. 492-505 - Rida Qadri, Renee Shelby, Cynthia L. Bennett, Emily Denton:
AI's Regimes of Representation: A Community-centered Study of Text-to-Image Models in South Asia. 506-517 - Aram Grigoryan, Markus Möller:
A Theory of Auditability for Allocation and Social Choice Mechanisms. 518 - A. Stevie Bergman, Lisa Anne Hendricks, Maribeth Rauh, Boxi Wu, William Agnew, Markus Kunesch, Isabella Duan, Iason Gabriel, William Isaac:
Representation in AI Evaluations. 519-533 - Matt Franchi, J. D. Zamfirescu-Pereira, Wendy Ju, Emma Pierson:
Detecting disparities in police deployments using dashcam data. 534-544 - Han Zhang, Shangen Lu, Yixin Wang, Mihaela Curmei:
Delayed and Indirect Impacts of Link Recommendations. 545-557 - Anna-Lena Theus:
Striving for Affirmative Algorithmic Futures: How the Social Sciences can Promote more Equitable and Just Algorithmic System Design. 558-568 - Shreya Chowdhary, Anna Kawakami, Mary L. Gray, Jina Suh, Alexandra Olteanu, Koustuv Saha:
Can Workers Meaningfully Consent to Workplace Wellbeing Technologies? 569-582 - Lameck Mbangula Amugongo, Nicola J. Bidwell, Caitlin C. Corrigan:
Invigorating Ubuntu Ethics in AI for healthcare: Enabling equitable care. 583-592 - Stephen Tze-Inn Wu, Daniel Demetriou, Rudwan Ali Husain:
Honor Ethics: The Challenge of Globalizing Value Alignment in AI. 593-602 - Paola Lopez:
Power and Resistance in the Twitter Bias Discourse. 603 - Thomas A. Henzinger, Mahyar Karimi, Konstantin Kueffner, Kaushik Mallik:
Runtime Monitoring of Dynamic Fairness Properties. 604-614 - Maciej Krzysztof Zuziak, Onntje Hinrichs, Aizhan Abdrassulova, Salvatore Rinzivillo:
Data Collaboratives with the Use of Decentralised Learning. 615-625 - Angelina Wang, Sayash Kapoor, Solon Barocas, Arvind Narayanan:
Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy. 626 - John Rudnik, Robin Brewer:
Care and Coordination in Algorithmic Systems: An Economies of Worth Approach. 627-638 - Anna Ma, Elizabeth Patitsas, Jonathan Sterne:
You Sound Depressed: A Case Study on Sonde Health's Diagnostic Use of Voice Analysis AI. 639-650 - Alan Chan, Rebecca Salganik, Alva Markelius, Chris Pang, Nitarshan Rajkumar, Dmitrii Krasheninnikov, Lauro Langosco, Zhonghao He, Yawen Duan, Micah Carroll, Michelle Lin, Alex Mayhew, Katherine M. Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj:
Harms from Increasingly Agentic Algorithmic Systems. 651-666 - Lingwei Cheng, Isabel O. Gallegos, Derek Ouyang, Jacob Goldin, Daniel E. Ho:
How Redundant are Redundant Encodings? Blindness in the Wild and Racial Disparity when Race is Unobserved. 667-686 - Seth Lazar, Jake Stone:
On the Site of Predictive Justice. 687 - Luke Guerdan, Amanda Coston, Zhiwei Steven Wu, Kenneth Holstein:
Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making. 688-704 - Wesley Hanwen Deng, Nur Yildirim, Monica Chang, Motahhare Eslami, Kenneth Holstein, Michael Madaio:
Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practice. 705-716 - Aditya Karan, Naina Balepur, Hari Sundaram:
Your Browsing History May Cost You: A Framework for Discovering Differential Pricing in Non-Transparent Markets. 717-735 - Brianna Richardson, Prasanna Sattigeri, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Amit Dhurandhar, Juan E. Gilbert:
Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential Fairness. 736-752 - Daman Deep Singh, Syamantak Das, Abhijnan Chakraborty:
FairAssign: Stochastically Fair Driver Assignment in Gig Delivery Platforms. 753-763 - Henrietta Lyons, Tim Miller, Eduardo Velloso:
Algorithmic Decisions, Desire for Control, and the Preference for Human Review over Algorithmic Review. 764-774 - Xudong Shen, Tianhui Tan, Tuan Quang Phan, Jussi Keppo:
Gender Animus Can Still Exist Under Favorable Disparate Impact: a Cautionary Tale from Online P2P Lending. 775-791 - Marissa Radensky, Julie Anne Séguin, Jang Soo Lim, Kristen Olson, Robert Geiger:
"I Think You Might Like This": Exploring Effects of Confidence Signal Patterns on Trust in and Reliance on Conversational Recommender Systems. 792-804 - Hilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy:
Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree. 805-816 - Eike Petersen, Melanie Ganz, Sune Hannibal Holm, Aasa Feragen:
On (assessing) the fairness of risk score models. 817-829 - Tim De Jonge, Djoerd Hiemstra:
UNFair: Search Engine Manipulation, Undetectable by Amortized Inequity. 830-839 - Ana Valdivia, Martina Tazzioli:
Datafication Genealogies beyond Algorithmic Fairness: Making Up Racialised Subjects. 840-850 - MaryBeth Defrance, Tijl De Bie:
Maximal fairness. 851-880 - Orestis Papakyriakopoulos, Anna Seo Gyeong Choi, William Thong, Dora Zhao, Jerone Theodore Alexander Andrews, Rebecca Bourke, Alice Xiang, Allison Koenecke:
Augmented Datasheets for Speech Datasets and Ethical Decision-Making. 881-904 - Delaram Golpayegani, Harshvardhan J. Pandit, Dave Lewis:
To Be High-Risk, or Not To Be - Semantic Specifications and Implications of the AI Act's High-Risk AI Applications and Harmonised Standards. 905-915 - Alexander Peysakhovich, Christian Kroer, Nicolas Usunier:
Implementing Fairness Constraints in Markets Using Taxes and Subsidies. 916-930 - Drew Hemment, Morgan Currie, Sarah Joy Bennett, Jake Elwes, Anna Ridler, Caroline Sinders, Matjaz Vidmar, Robin Hill, Holly Warner:
AI in the Public Eye: Investigating Public AI Literacy Through AI Art. 931-942 - Astrid Bertrand, James R. Eagan, Winston Maxwell:
Questioning the ability of feature-based explanations to empower non-experts in robo-advised financial decision-making. 943-958 - Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek:
On the Impact of Explanations on Understanding of Algorithmic Decision-Making. 959-970 - Andrés Domínguez Hernández, Richard Owen, Dan Saattrup Nielsen, Ryan McConville:
Addressing contingency in algorithmic (mis)information classification: Toward a responsible machine learning agenda. 971 - Sonja Mei Wang, Kristen M. Scott, Margarita Artemenko, Milagros Miceli, Bettina Berendt:
"We try to empower them" - Exploring Future Technologies to Support Migrant Jobseekers. 972-983 - Ahmad-Reza Ehyaei, Amir-Hossein Karimi, Bernhard Schölkopf, Setareh Maghsudi:
Robustness Implies Fairness in Causal Algorithmic Recourse. 984-1001 - Joachim Baumann, Alessandro Castelnovo, Riccardo Crupi, Nicole Inverardi, Daniele Regoli:
Bias on Demand: A Modelling Framework That Generates Synthetic Data With Bias. 1002-1013 - Andrea 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:
ACROCPoLis: A Descriptive Framework for Making Sense of Fairness. 1014-1025 - Felicia S. Jing, Sara E. Berger, Juana Catalina Becerra Sandoval:
Towards Labor Transparency in Situated Computational Systems Impact Research. 1026-1037 - Mohsen Abbasi, Calvin Barrett, Kristian Lum, Sorelle A. Friedler, Suresh Venkatasubramanian:
Measuring and mitigating voting access disparities: a study of race and polling locations in Florida and North Carolina. 1038-1048 - Alina Leidinger, Richard Rogers:
Which Stereotypes Are Moderated and Under-Moderated in Search Engine Autocompletion? 1049-1061 - Ulla Petti, Rune Nyrup, Jeffrey M. Skopek, Anna Korhonen:
Ethical considerations in the early detection of Alzheimer's disease using speech and AI. 1062-1075 - Michal Luria:
Co-Design Perspectives on Algorithm Transparency Reporting: Guidelines and Prototypes. 1076-1087 - Juniper L. Lovato, Philip Mueller, Parisa Suchdev, Peter Sheridan Dodds:
More Data Types More Problems: A Temporal Analysis of Complexity, Stability, and Sensitivity in Privacy Policies. 1088-1100 - Morgan Currie, Lena Podoletz:
Emotions and Dynamic Assemblages: A Study of Automated Social Security Using Qualitative Longitudinal Research. 1101-1111 - Philipp Hacker, Andreas Engel, Marco Mauer:
Regulating ChatGPT and other Large Generative AI Models. 1112-1123 - Benedikt Höltgen, Robert C. Williamson:
On the Richness of Calibration. 1124-1138 - Cecilia Panigutti, Ronan Hamon, Isabelle Hupont, David Fernández Llorca, Delia Fano Yela, Henrik Junklewitz, Salvatore Scalzo, Gabriele Mazzini, Ignacio Sánchez, Josep Soler Garrido, Emilia Gómez:
The role of explainable AI in the context of the AI Act. 1139-1150 - Hanlin Li, Nicholas Vincent, Stevie Chancellor, Brent J. Hecht:
The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data Producers. 1151-1161 - Lara Groves, Aidan Peppin, Andrew Strait, Jenny Brennan:
Going public: the role of public participation approaches in commercial AI labs. 1162-1173 - Robert Wolfe, Yiwei Yang, Bill Howe, Aylin Caliskan:
Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Bias. 1174-1185 - Jennifer Cobbe, Michael Veale, Jatinder Singh:
Understanding accountability in algorithmic supply chains. 1186-1197 - Luca Nannini, Agathe Balayn, Adam Leon Smith:
Explainability in AI Policies: A Critical Review of Communications, Reports, Regulations, and Standards in the EU, US, and UK. 1198-1212 - Joaquin Quiñonero Candela, Yuwen Wu, Brian Hsu, Sakshi Jain, Jennifer Ramos, Jon Adams, Robert Hallman, Kinjal Basu:
Disentangling and Operationalizing AI Fairness at LinkedIn. 1213-1228 - Alessandra Calvi, Dimitris Kotzinos:
Enhancing AI fairness through impact assessment in the European Union: a legal and computer science perspective. 1229-1245 - Anaelia Ovalle, Palash Goyal, Jwala Dhamala, Zachary Jaggers, Kai-Wei Chang, Aram Galstyan, Richard S. Zemel, Rahul Gupta:
"I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation. 1246-1266 - Laura Lucaj, Patrick van der Smagt, Djalel Benbouzid:
AI Regulation Is (not) All You Need. 1267-1279 - Jacob Thebault-Spieker, Sukrit Venkatagiri, Naomi Mine, Kurt Luther:
Diverse Perspectives Can Mitigate Political Bias in Crowdsourced Content Moderation. 1280-1291 - Marissa Gerchick, Tobi Jegede, Tarak Shah, Ana Gutierrez, Sophie Beiers, Noam Shemtov, Kath Xu, Anjana Samant, Aaron Horowitz:
The Devil is in the Details: Interrogating Values Embedded in the Allegheny Family Screening Tool. 1292-1310 - Leah Hope Ajmani, Stevie Chancellor, Bijal Mehta, Casey Fiesler, Michael Zimmer, Munmun De Choudhury:
A Systematic Review of Ethics Disclosures in Predictive Mental Health Research. 1311-1323 - Amina A. Abdu, Irene V. Pasquetto, Abigail Z. Jacobs:
An Empirical Analysis of Racial Categories in the Algorithmic Fairness Literature. 1324-1333 - Evani Radiya-Dixit, Gina Neff:
A Sociotechnical Audit: Assessing Police Use of Facial Recognition. 1334-1346 - Kathleen Cachel, Elke A. Rundensteiner:
Fairer Together: Mitigating Disparate Exposure in Kemeny Rank Aggregation. 1347-1357 - Faisal Hamman, Jiahao Chen, Sanghamitra Dutta:
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity. 1358-1368 - Vivian Lai, Chacha Chen, Alison Smith-Renner, Q. Vera Liao, Chenhao Tan:
Towards a Science of Human-AI Decision Making: An Overview of Design Space in Empirical Human-Subject Studies. 1369-1385 - Nathalie DiBerardino, Luke Stark:
(Anti)-Intentional Harms: The Conceptual Pitfalls of Emotion AI in Education. 1386-1395 - Jee 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 E. Vidal, Suresh Balu, Mark P. Sendak:
Organizational Governance of Emerging Technologies: AI Adoption in Healthcare. 1396-1417 - Chris Norval, Richard Cloete, Jatinder Singh:
Navigating the Audit Landscape: A Framework for Developing Transparent and Auditable XR. 1418-1431 - David Liu, Virginie Do, Nicolas Usunier, Maximilian Nickel:
Group fairness without demographics using social networks. 1432-1449 - Jacob Metcalf, Ranjit Singh, Emanuel Moss, Emnet Tafesse, Elizabeth Anne Watkins:
Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability. 1450-1462 - Hellina Hailu Nigatu, Lisa Pickoff-White, John F. Canny, Sarah E. Chasins:
Co-Designing for Transparency: Lessons from Building a Document Organization Tool in the Criminal Justice Domain. 1463-1478 - Anjalie Field, Amanda Coston, Nupoor Gandhi, Alexandra Chouldechova, Emily Putnam-Hornstein, David Steier, Yulia Tsvetkov:
Examining risks of racial biases in NLP tools for child protective services. 1479-1492 - Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan:
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. 1493-1504 - Melissa 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:
What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB. 1505-1519 - Xin Chen, Zexing Xu, Zishuo Zhao, Yuan Zhou:
Personalized Pricing with Group Fairness Constraint. 1520-1530 - Rock Yuren Pang, Jack Cenatempo, Franklyn Graham, Bridgette Kuehn, Maddy Whisenant, Portia K. Botchway, Katie Stone Perez, Allison Koenecke:
Auditing Cross-Cultural Consistency of Human-Annotated Labels for Recommendation Systems. 1531-1552 - Miri Zilka, Riccardo Fogliato, Jiri Hron, Bradley Butcher, Carolyn Ashurst, Adrian Weller:
The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments. 1553-1569 - Kweku Kwegyir-Aggrey, Marissa Gerchick, Malika Mohan, Aaron Horowitz, Suresh Venkatasubramanian:
The Misuse of AUC: What High Impact Risk Assessment Gets Wrong. 1570-1583 - Luke Guerdan, Amanda Coston, Kenneth Holstein, Zhiwei Steven Wu:
Counterfactual Prediction Under Outcome Measurement Error. 1584-1598 - Raphael Poulain, Mirza Farhan Bin Tarek, Rahmatollah Beheshti:
Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods. 1599-1608 - Bogdan Kulynych, Hsiang Hsu, Carmela Troncoso, Flávio P. Calmon:
Arbitrary Decisions are a Hidden Cost of Differentially Private Training. 1609-1623 - Eric Corbett, Emily Denton:
Interrogating the T in FAccT. 1624-1634 - Ashkan Bashardoust, Sorelle A. Friedler, Carlos Scheidegger, Blair D. Sullivan, Suresh Venkatasubramanian:
Reducing Access Disparities in Networks using Edge Augmentation✱. 1635-1651 - Jessie J. Smith, Anas Buhayh, Anushka Kathait, Pradeep Ragothaman, Nicholas Mattei, Robin Burke, Amy Voida:
The Many Faces of Fairness: Exploring the Institutional Logics of Multistakeholder Microlending Recommendation. 1652-1663 - Joshua Gardner, Renzhe Yu, Quan Nguyen, Christopher Brooks, René F. Kizilcec:
Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity. 1664-1684 - Hilson Shrestha, Kathleen Cachel, Mallak Alkhathlan, Elke A. Rundensteiner, Lane Harrison:
Help or Hinder? Evaluating the Impact of Fairness Metrics and Algorithms in Visualizations for Consensus Ranking. 1685-1698 - Katelyn Mei, Sonia Fereidooni, Aylin Caliskan:
Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks. 1699-1710 - Princess Sampson, Ro Encarnacion, Danaë Metaxa:
Representation, Self-Determination, and Refusal: Queer People's Experiences with Targeted Advertising. 1711-1722 - Markelle Kelly, Aakriti Kumar, Padhraic Smyth, Mark Steyvers:
Capturing Humans' Mental Models of AI: An Item Response Theory Approach. 1723-1734 - Pedro Silva, Bhawna Juneja, Shloka Desai, Ashudeep Singh, Nadia Fawaz:
Representation Online Matters: Practical End-to-End Diversification in Search and Recommender Systems. 1735-1746 - David Bruns-Smith, Avi Feller, Emi Nakamura:
Using Supervised Learning to Estimate Inequality in the Size and Persistence of Income Shocks. 1747-1756 - Teanna Barrett, Quanze Chen, Amy X. Zhang:
Skin Deep: Investigating Subjectivity in Skin Tone Annotations for Computer Vision Benchmark Datasets. 1757-1771 - Varun Nagaraj Rao, Aleksandra Korolova:
Discrimination through Image Selection by Job Advertisers on Facebook. 1772-1788 - Prakhar Ganesh, Hongyan Chang, Martin Strobel, Reza Shokri:
On The Impact of Machine Learning Randomness on Group Fairness. 1789-1800 - Cyrus DiCiccio, Brian Hsu, YinYin Yu, Preetam Nandy, Kinjal Basu:
Detection and Mitigation of Algorithmic Bias via Predictive Parity. 1801-1816 - Jingyi Yang, Joel Miller, Mesrob Ohannessian:
Fairness Auditing in Urban Decisions using LP-based Data Combination. 1817-1825 - Yuxi Wu, Sydney Bice, W. Keith Edwards, Sauvik Das:
The Slow Violence of Surveillance Capitalism: How Online Behavioral Advertising Harms People. 1826-1837 - Gabriel Grill, Fabian Fischer, Florian Cech:
Bias as Boundary Object: Unpacking The Politics Of An Austerity Algorithm Using Bias Frameworks. 1838-1849 - Reuben Binns, Jeremias Adams-Prassl, Aislinn Kelly-Lyth:
Legal Taxonomies of Machine Bias: Revisiting Direct Discrimination. 1850-1858 - Thibault Laugel, Adulam Jeyasothy, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
Achieving Diversity in Counterfactual Explanations: a Review and Discussion. 1859-1869 - Michael Saxon, William Yang Wang:
Disparities in Text-to-Image Model Concept Possession Across Languages. 1870 - Katja Andric, Atoosa Kasirzadeh:
Reconciling Governmental Use of Online Targeting With Democracy. 1871-1881 - Organizers Of QueerInAI, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, Pranav A, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark:
Queer In AI: A Case Study in Community-Led Participatory AI. 1882-1895
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