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ORCIDFAccT 2021: Virtual Event / Toronto, Canada
- Madeleine Clare Elish, William Isaac, Richard S. Zemel:
FAccT '21: 2021 ACM Conference on Fairness, Accountability, and Transparency, Virtual Event / Toronto, Canada, March 3-10, 2021. ACM 2021, ISBN 978-1-4503-8309-7 - Lelia Marie Hampton:
Black Feminist Musings on Algorithmic Oppression. 1 - Maxime C. Cohen, Adam N. Elmachtoub, Xiao Lei:
Price Discrimination with Fairness Constraints. 2 - Harvineet Singh, Rina Singh, Vishwali Mhasawade
, Rumi Chunara:
Fairness Violations and Mitigation under Covariate Shift. 3-13 - Atoosa Kasirzadeh:
Reasons, Values, Stakeholders: A Philosophical Framework for Explainable Artificial Intelligence. 14 - Hoda Heidari, Jon M. Kleinberg:
Allocating Opportunities in a Dynamic Model of Intergenerational Mobility. 15-25 - Tom Ron, Omer Ben-Porat, Uri Shalit:
Corporate Social Responsibility via Multi-Armed Bandits. 26-40 - Ramya Srinivasan, Kanji Uchino:
Biases in Generative Art: A Causal Look from the Lens of Art History. 41-51 - Joon Sung Park, Danielle Bragg, Ece Kamar, Meredith Ringel Morris:
Designing an Online Infrastructure for Collecting AI Data From People With Disabilities. 52-63 - Lauren Thornton, Bran Knowles, Gordon S. Blair:
Fifty Shades of Grey: In Praise of a Nuanced Approach Towards Trustworthy Design. 64-76 - Kyla Chasalow, Karen Levy:
Representativeness in Statistics, Politics, and Machine Learning. 77-89 - Elinor Benami, Reid Whitaker, Vincent La, Hongjin Lin, Brandon R. Anderson, Daniel E. Ho:
The Distributive Effects of Risk Prediction in Environmental Compliance: Algorithmic Design, Environmental Justice, and Public Policy. 90-105 - Marc Cheong, Kobi Leins, Simon Coghlan:
Computer Science Communities: Who is Speaking, and Who is Listening to the Women? Using an Ethics of Care to Promote Diverse Voices. 106-115 - Ari Ball-Burack, Michelle Seng Ah Lee, Jennifer Cobbe, Jatinder Singh:
Differential Tweetment: Mitigating Racial Dialect Bias in Harmful Tweet Detection. 116-128 - Tim Räz:
Group Fairness: Independence Revisited. 129-137 - Hongjing Zhang, Ian Davidson:
Towards Fair Deep Anomaly Detection. 138-148 - Victoria Cheng, Vinith M. Suriyakumar, Natalie Dullerud, Shalmali Joshi, Marzyeh Ghassemi:
Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness. 149-160 - Milagros Miceli, Tianling Yang, Laurens Naudts, Martin Schuessler, Diana Serbanescu, Alex Hanna:
Documenting Computer Vision Datasets: An Invitation to Reflexive Data Practices. 161-172 - Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alexandra Chouldechova, Daniel E. Ho:
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy. 173-184 - Kate Donahue, Solon Barocas:
Better Together?: How Externalities of Size Complicate Notions of Solidarity and Actuarial Fairness. 185-195 - Fereshte Khani, Percy Liang:
Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately. 196-205 - Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang:
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information. 206-214 - Nicholas Vincent, Hanlin Li, Nicole Tilly, Stevie Chancellor, Brent J. Hecht:
Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies. 215-227 - Atoosa Kasirzadeh, Andrew Smart:
The Use and Misuse of Counterfactuals in Ethical Machine Learning. 228-236 - Anay Mehrotra, L. Elisa Celis:
Mitigating Bias in Set Selection with Noisy Protected Attributes. 237-248 - McKane Andrus, Elena Spitzer, Jeffrey Brown, Alice Xiang:
What We Can't Measure, We Can't Understand: Challenges to Demographic Data Procurement in the Pursuit of Fairness. 249-260 - Nikhil Garg, Hannah Li, Faidra Monachou:
Standardized Tests and Affirmative Action: The Role of Bias and Variance. 261 - Bran Knowles, John T. Richards:
The Sanction of Authority: Promoting Public Trust in AI. 262-271 - Angela E. Kilby:
Algorithmic Fairness in Predicting Opioid Use Disorder using Machine Learning. 272 - Samuel Yeom, Michael Carl Tschantz:
Avoiding Disparity Amplification under Different Worldviews. 273-283 - Joshua L. Martin:
Spoken Corpora Data, Automatic Speech Recognition, and Bias Against African American Language: The case of Habitual 'Be'. 284 - Emily Black, Matt Fredrikson:
Leave-one-out Unfairness. 285-295 - Nathan Kallus, Angela Zhou:
Fairness, Welfare, and Equity in Personalized Pricing. 296-314 - Nithya Sambasivan, Erin Arnesen, Ben Hutchinson, Tulsee Doshi, Vinodkumar Prabhakaran:
Re-imagining Algorithmic Fairness in India and Beyond. 315-328 - Rediet Abebe, Kehinde D. Aruleba, Abeba Birhane, Sara Kingsley, George Obaido, Sekou L. Remy, Swathi Sadagopan:
Narratives and Counternarratives on Data Sharing in Africa. 329-341 - Kendra Albert, Maggie K. Delano:
This Whole Thing Smacks of Gender: Algorithmic Exclusion in Bioimpedance-based Body Composition Analysis. 342-352 - Amir-Hossein Karimi, Bernhard Schölkopf, Isabel Valera:
Algorithmic Recourse: from Counterfactual Explanations to Interventions. 353-362 - Simone Diniz Junqueira Barbosa, Gabriel Diniz Junqueira Barbosa, Clarisse Sieckenius de Souza, Carla Faria Leitão:
A Semiotics-based epistemic tool to reason about ethical issues in digital technology design and development. 363-374 - Abigail Z. Jacobs:
Measurement and Fairness. 375-385 - Alan Mishler, Edward H. Kennedy, Alexandra Chouldechova:
Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds. 386-400 - Neel Patel, Martin Strobel, Yair Zick:
High Dimensional Model Explanations: An Axiomatic Approach. 401-411 - Stefania Ionescu, Anikó Hannák, Kenneth Joseph:
An Agent-based Model to Evaluate Interventions on Online Dating Platforms to Decrease Racial Homogamy. 412-423 - Severin Kacianka, Alexander Pretschner:
Designing Accountable Systems. 424-437 - Mehrdad Ghadiri, Samira Samadi, Santosh S. Vempala:
Socially Fair k-Means Clustering. 438-448 - Won-Ik Cho, Ji Won Kim, Jaeyeong Yang, Nam Soo Kim:
Towards Cross-Lingual Generalization of Translation Gender Bias. 449-457 - William Boag, Hassan Kané, Saumya Rawat, Jesse Wei, Alexander Goehler:
A Pilot Study in Surveying Clinical Judgments to Evaluate Radiology Report Generation. 458-465 - Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson:
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. 466-477 - Mats Mulder, Oana Inel, Jasper Oosterman, Nava Tintarev:
Operationalizing Framing to Support Multiperspective Recommendations of Opinion Pieces. 478-488 - Jessie Finocchiaro, Roland Maio, Faidra Monachou, Gourab K. Patro, Manish Raghavan, Ana-Andreea Stoica, Stratis Tsirtsis:
Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness. 489-503 - Mohsen Abbasi, Aditya Bhaskara, Suresh Venkatasubramanian:
Fair Clustering via Equitable Group Representations. 504-514 - Inioluwa Deborah Raji, Morgan Klaus Scheuerman, Razvan Amironesei:
You Can't Sit With Us: Exclusionary Pedagogy in AI Ethics Education. 515-525 - Jialu Wang, Yang Liu, Caleb C. Levy:
Fair Classification with Group-Dependent Label Noise. 526-536 - Eddie Yang, Margaret E. Roberts:
Censorship of Online Encyclopedias: Implications for NLP Models. 537-548 - Ronan Hamon, Henrik Junklewitz, Gianclaudio Malgieri, Paul de Hert, Laurent Beslay, Ignacio Sánchez:
Impossible Explanations?: Beyond explainable AI in the GDPR from a COVID-19 use case scenario. 549-559 - Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, Margaret Mitchell:
Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure. 560-575 - Maximilian Kasy, Rediet Abebe:
Fairness, Equality, and Power in Algorithmic Decision-Making. 576-586 - Zaid Khan, Yun Fu:
One Label, One Billion Faces: Usage and Consistency of Racial Categories in Computer Vision. 587-597 - Jennifer Cobbe, Michelle Seng Ah Lee, Jatinder Singh:
Reviewable Automated Decision-Making: A Framework for Accountable Algorithmic Systems. 598-609 - Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, Shmargaret Shmitchell:
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 610-623 - Alon Jacovi, Ana Marasovic, Tim Miller, Yoav Goldberg:
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI. 624-635 - Elias Grünewald, Frank Pallas:
TILT: A GDPR-Aligned Transparency Information Language and Toolkit for Practical Privacy Engineering. 636-646 - Kira Lussier:
From Papers to Programs: Courts, Corporations, Clinics and the Battle over Computerized Psychological Testing. 647 - Bahar Taskesen, Jose H. Blanchet, Daniel Kuhn, Viet Anh Nguyen:
A Statistical Test for Probabilistic Fairness. 648-665 - Christo Wilson, Avijit Ghosh, Shan Jiang, Alan Mislove, Lewis J. Baker, Janelle Szary, Kelly Trindel, Frida Polli:
Building and Auditing Fair Algorithms: A Case Study in Candidate Screening. 666-677 - L. Elisa Celis, Chris Hays, Anay Mehrotra, Nisheeth K. Vishnoi:
The Effect of the Rooney Rule on Implicit Bias in the Long Term. 678-689 - Maria Kasinidou, Styliani Kleanthous, Pinar Barlas, Jahna Otterbacher:
I agree with the decision, but they didn't deserve this: Future Developers' Perception of Fairness in Algorithmic Decisions. 690-700 - Ryan Steed, Aylin Caliskan:
Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases. 701-713 - Smitha Milli, Luca Belli, Moritz Hardt:
From Optimizing Engagement to Measuring Value. 714-722 - Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi:
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. 723-734 - Jacob Metcalf, Emanuel Moss, Elizabeth Anne Watkins, Ranjit Singh, Madeleine Clare Elish:
Algorithmic Impact Assessments and Accountability: The Co-construction of Impacts. 735-746 - Corinna Hertweck, Christoph Heitz, Michele Loi:
On the Moral Justification of Statistical Parity. 747-757 - Joshua A. Kroll:
Outlining Traceability: A Principle for Operationalizing Accountability in Computing Systems. 758-771 - P. M. Krafft, Meg Young, Michael A. Katell, Jennifer E. Lee, Shankar Narayan, Micah Epstein, Dharma Dailey, Bernease Herman, Aaron Tam, Vivian Guetler, Corinne Bintz, Daniella Raz, Pa Ousman Jobe, Franziska Putz, Brian Robick, Bissan Barghouti:
An Action-Oriented AI Policy Toolkit for Technology Audits by Community Advocates and Activists. 772-781 - Luke Stark, Jesse Hoey:
The Ethics of Emotion in Artificial Intelligence Systems. 782-793 - Elena Beretta, Antonio Vetrò, Bruno Lepri, Juan Carlos De Martin:
Detecting discriminatory risk through data annotation based on Bayesian inferences. 794-804 - Sérgio M. Jesus, Catarina G. Belém, Vladimir Balayan, João Bento, Pedro Saleiro, Pedro Bizarro, João Gama:
How can I choose an explainer?: An Application-grounded Evaluation of Post-hoc Explanations. 805-815 - Kathleen Creel, Deborah Hellman:
The Algorithmic Leviathan: Arbitrariness, Fairness, and Opportunity in Algorithmic Decision Making Systems. 816 - Leif Hancox-Li, I. Elizabeth Kumar:
Epistemic values in feature importance methods: Lessons from feminist epistemology. 817-826 - Joshua Williams, J. Zico Kolter:
A Bayesian Model of Cash Bail Decisions. 827-837 - Nil-Jana Akpinar, Maria De-Arteaga, Alexandra Chouldechova:
The effect of differential victim crime reporting on predictive policing systems. 838-849 - Hong Shen, Wesley H. Deng, Aditi Chattopadhyay, Zhiwei Steven Wu, Xu Wang, Haiyi Zhu:
Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberation. 850-861 - Jwala Dhamala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta:
BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation. 862-872 - Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh, Animesh Mukherjee, Krishna P. Gummadi:
When the Umpire is also a Player: Bias in Private Label Product Recommendations on E-commerce Marketplaces. 873-884
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