‘We cannot find fault with a friend’: Perceptions of Algorithmic Accountability among Instant Loan App Users in India
Divya Ramesh, Vaishnav Kameswaran, Ding Wang and Nithya Sambasivan
"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Making
Jakob Schoeffer, Niklas Kuehl and Yvette Machowski
#FuckTheAlgorithm: algorithmic imaginaries and political resistance
Garfield Benjamin
A Data-driven analysis of the interplay between Criminiological theory and predictive policing algorithms
Adriane Chapman, Philip Grylls, Pamela Ugwudike, David Gammack and Jacqui Ayling
A Data-Driven Simulation of the New York State Foster Care System
Yuhao Du, Stefania Ionescu, Melanie Sage and Kenneth Joseph
A Review of Taxonomies of Explainable Artificial Intelligence (XAI) Methods
Timo Speith
ABCinML: Anticipatory Bias Correction in Machine Learning Applications
Abdulaziz Almuzaini, Chidansh Bhatt, David Pennock and Vivek Singh
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning
A. Feder Cooper, Benjamin Laufer, Emanuel Moss, and Helen Nissenbaum
Accountable Datasets: The Politics and Pragmatics of Disclosure Datasets
Lindsay Poirier
Achieving Fairness via Post-Processing in Web-Scale Recommender Systems
Preetam Nandy, Cyrus DiCiccio, Divya Venugopalan, Heloise Logan, Kinjal Basu and Noureddine El Karoui
Adaptive Sampling Strategies to Construct Equitable Training Datasets
William Cai, Ro Encarnacion, Bobbie Chern, Sam Corbett-Davies, Miranda Bogen, Stevie Bergman and Sharad Goel
Adversarial Scrutiny of Evidentiary Statistical Software
Rediet Abebe, Moritz Hardt, Angela Jin, John Miller, Ludwig Schmidt and Rebecca Wexler
Affirmative Algorithms: Relational Equality as Algorithmic Fairness
Marilyn Zhang
AI Ethics Statements - Analysis and Lessons Learnt from NeurIPS Broader Impact Statements
Carolyn Ashurst, Emmie Hine, Paul Sedille and Alexis Carlier
AI Opacity and Explainability in Tort Litigation
Henry Fraser, Rhyle Simcock and Aaron Snoswell
Algorithmic Fairness and Vertical Equity: Income Fairness with Tax Audit Models
Emily Black, Hadi Elzayn, Alexandra Chouldechova, Jacob Goldin and Daniel Ho
Algorithmic Tools in Public Employment Services: Towards a Jobseeker-Centric Perspective
Kristen Scott, Sonja Mei Wang, Milagros Miceli, Pieter Delobelle, Karolina Sztandar-Sztanderska and Bettina Berendt
Algorithms Off-Limits?: If digital Trade Law Restricts Access to Source Code of Software then Accountability will Suffer
Kristina Irion
An Algorithmic Framework for Bias Bounties
Ira Globus-Harris, Michael Kearns and Aaron Roth
An Outcome Test of Discrimination for Ranked Lists
Jonathan Roth, Guillaume Saint-Jacques and Yinyin Yu
Are "Intersectionally Fair" AI Algorithms Really Fair to Women of Color? A Philosophical Analysis
Youjin Kong
Assessing Annotator Identity Bias via Item Response Theory: A Case Study in a Hate Speech Corpus
Pratik Sachdeva, Renata Barreto, Claudia von Vacano and Chris Kennedy
At The Tensions of South and North: Critical Roles of Global South Stakeholders in AI Governance
Marie-Therese Png
Attribute Privacy: Framework and Mechanisms
Wanrong Zhang, Olga Ohrimenko and Rachel Cummings
Auditing for Gerrymandering by Identifying Disenfranchised Individuals
Jerry Lin, Carolyn Chen, Marc Chmielewski, Samia Zaman and Brandon Fain
Automating Care: Online Food Delivery Work During the CoVID-19 Crisis in India
Anubha Singh and Tina Park
BCIs and human rights: Brave new rights for a brave new world
Marietjie Botes
Behavioral Use Licensing for Responsible AI
Danish Contractor, Daniel McDuff, Julia Haines, Jenny Lee, Christopher Hines, Brent Hecht, Nicholas Vincent and Hanlin Li
Best vs. All: Equity and Accuracy of Standardized Test Score Reporting
Mingzi Niu, Sampath Kannan, Aaron Roth and Rakesh Vohra
Beyond Fairness: Reparative Algorithms to Address Historical Injustices of Housing Discrimination in the US
Wonyoung So, Pranay Lohia, Rakesh Pimplikar, A.E. Hosoi and Catherine D'Ignazio
Bias in Automated Speaker Recognition
Wiebke Toussaint and Aaron Yi Ding
Can Machines Help Us Answering Question 16 in Datasheets, and in turn Reflecting on Inappropriate Content?
Patrick Schramowski, Christopher Tauchmann and Kristian Kersting
Caring for Datasets: A Framework for Deprecating Datasets and Responsible Data Stewardship
Alexandra Sasha Luccioni, Frances Corry, Hamsini Sridharan, Mike Ananny, Jason Schultz and Kate Crawford
Causal Inference Struggles with Agency on Online Platforms
Smitha Milli, Luca Belli and Moritz Hardt
Characterizing Properties and Trade-offs of Centralized Delegation Mechanisms in Liquid Democracy
Brian Brubach, Audrey Ballarin and Heeba Nazeer
CounterFAccTual: How FAccT’s acontextual framing undermines its organizing principles
Ben Gansky and Sean McDonald
Counterfactual Shapley Additive Explanations
Emanuele Albini, Jason Long, Danial Dervovic and Daniele Magazzeni
Critical Evaluation Gaps in Machine Learning Practice
Ben Hutchinson, Negar Rostamzadeh, Christina Greer, Katherine Heller and Vinodkumar Prabhakaran
Critical Tools for Machine Learning: Working with Intersectional Critical Concepts in Machine Learning Systems Design
Goda Klumbyte, Claude Draude and Alex Taylor
CrowdWorkSheets: Accounting for Individual and Collective Identities Underlying Crowdsourced Dataset Annotation
Razvan Amironesei, Dylan Baker, Emily Denton, Mark Díaz, Ian Kivlichan, Vinodkumar Prabhakaran and Rachel Rosen
Data augmentation for fairness-aware machine learning: Preventing algorithmic bias in law enforcement systems
Ioannis Pastaltzidis, Nikolaos Dimitriou, Katherine Quezada-Tavárez, Stergios Aidinlis, Thomas Marquenie, Agata Gurzawska and Dimitrios Tzovaras
Data Cards: Purposeful and Transparent Documentation for Responsible AI
Mahima Pushkarna, Andrew Zaldivar and Oddur Kjartansson
Data Governance in the Age of Large-Scale Data-Driven Language Technology
Yacine Jernite, Huu Nguyen, Stella Biderman, Anna Rogers, Maraim Masoud, Valentin Danchev, Samson Tan, Alexandra Sasha Luccioni, Nishant Subramani, Isaac Johnson, Gérard Dupont, Jesse Dodge, Kyle Lo, Zeerak Talat, Dragomir Radev, Aaron Gokaslan, Somaieh Nikpoor, Peter Henderson, Rishi Bommasani and Margaret Mitchell
De-biasing "bias" measurement
Kristian Lum, Yunfeng Zhang and Amanda Bower
Decision Time: Normative Dimensions of Algorithmic Speed
Daniel Susser
Demographic-Reliant Algorithmic Fairness: Characterizing the Risks of Demographic Data Collection in the Pursuit of Fairness
Mckane Andrus and Sarah Villeneuve
Designing Up with Value-Sensitive Design: Building a Field Guide for Ethical Machine Learning Development
Karen Boyd
Disclosure by Design: Document engineering for meaningful data disclosures
Chris Norval, Kristin Cornelius, Jennifer Cobbe and Jatinder Singh
Disentangling Research Ethics in Machine Learning
Carolyn Ashurst, Solon Barocas, Rosie Campbell and Inioluwa Deborah Raji
Don't let Ricci v. DeStefano Hold You Back: A Bias-Aware Legal Solution to the Hiring Paradox
Jad Salem, Deven Desai and Swati Gupta
Don’t Throw it Away! The Utility of Unlabeled Data in Fair Decision Making
Miriam Rateike, Ayan Majumdar, Olga Mineeva, Krishna P. Gummadi and Isabel Valera
DualCF: Efficient Model Extraction Attack from Counterfactual Explanations
Yongjie Wang, Hangwei Qian and Chunyan Miao
Dynamic Privacy Budget Allocation Improves Data Efficiency of Differentially Private Gradient Descent
Junyuan Hong, Zhangyang Wang and Jiayu Zhou
Enforcing Group Fairness in Algorithmic Decision Making: Utility Maximization Under Sufficiency
Joachim Baumann, Anikó Hannák and Christoph Heitz
Equi-explanation Maps: Concise and Informative Global Summary Explanations
Tanya Chowdhury, Razieh Rahimi and James Allan
Equitable Public Bus Network Optimization for Social Good: A Case Study of Singapore
David Tedjopurnomo, Zhifeng Bao, Farhana Choudhury, Hui Luo and A. K. Qin
Ethical Concerns and Perceptions of Consumer Neurotechnology from Lived Experiences of Mental Workload Tracking
Serena Midha, Max Wilson and Sarah Sharples
Evidence for Hypodescent in Visual Semantic AI
Robert Wolfe, Mahzarin Banaji and Aylin Caliskan
Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits
Wesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee, Jatinder Singh, Zhiwei Steven Wu, Kenneth Holstein and Haiyi Zhu
Exploring the Role of Grammar and Word Choice in Bias Toward African American English (AAE) in Hate speech Classification
Camille Harris, Matan Halevy, Ayanna Howard, Amy Bruckman and Diyi Yang
FAccT-Check on AI regulation: Systematic Evaluation of AI Regulation on the Example of the Proposed Legislation on the Use of AI in the Public Sector in the German Federal State of Schleswig-Holstein
Katharina Simbeck
FADE: FAir Double Ensemble Learning for Observable and Counterfactual Outcomes
Alan Mishler and Edward H. Kennedy
Fair Data Sharing
Ronen Gradwohl and Moshe Tennenholtz
Fair ranking: a critical review, challenges, and future directions
Gourab K Patro, Lorenzo Porcaro, Laura Mitchell, Qiuyue Zhang, Meike Zehlike and Nikhil Garg
Fair Representation Clustering with Several Protected Classes
Zhen Dai, Yury Makarychev and Ali Vakilian
Fairness for AUC via Feature Augmentation
Hortense Fong, Vineet Kumar, Anay Mehrotra and Nisheeth K. Vishnoi
Fairness Indicators for Systematic Assessments of Visual Feature Extractors
Priya Goyal, Adriana Romero Soriano, Caner Hazirbas, Levent Sagun and Nicolas Usunier
Fairness-aware Model-agnostic Positive and Unlabeled Learning
Ziwei Wu and Jingrui He
Fast online ranking with fairness of exposure
Nicolas Usunier, Virginie Do and Elvis Dohmatob
Female, white, 27? Bias Evaluation on Data and Algorithms for Affect Recognition in Faces
Jaspar Pahl, Ines Rieger, Anna Möller, Thomas Wittenberg and Ute Schmid
Flipping the Script on Criminal Justice Risk Assessments
Mikaela Meyer, Aaron Horowitz, Erica Marshall and Kristian Lum
Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects
Benjamin Laufer, Sameer Jain, A. Feder Cooper, Jon Kleinberg and Hoda Heidari
From Demo to Design in Teaching Machine Learning
Karl-Emil Kjær Bilstrup, Magnus Kaspersen, Ira Assent, Simon Enni and Marianne Graves Petersen
Gender and Racial Bias in Visual Question Answering Datasets
Yusuke Hirota, Yuta Nakashima and Noa Garcia
German AI Start-Ups and “Ethical AI”: Using Social Practice as Basis for Assessing and Implementing Socio-Technical Innovation
Mona Sloane and Janina Zakrzewski
GetFair: Generalized Fairness Tuning of Classification Models
Sandipan Sikdar, Florian Lemmerich and Markus Strohmaier
Goodbye Tracking? Impact of iOS App Tracking Transparency and Privacy Labels
Konrad Kollnig, Anastasia Shuba, Max Van Kleek, Reuben Binns and Nigel Shadbolt
Healthsheet: development of a transparency artifact for health datasets
Negar Rostamzadeh, Diana Mincu, Subhrajit Roy, Andrew Smart, Lauren Wilcox, Mahima Pushkarna, Jessica Schrouff, Razvan Amironesei, Nyalleng Moorosi and Katherine Heller
How are ML-Based Online Content Moderation Systems Actually Used? Studying Community Size, Local Activity, and Disparate Treatment
Leijie Wang and Haiyi Zhu
How Different Groups Prioritize Ethical Values for Responsible AI
Maurice Jakesch, Zana Bucinca, Saleema Amershi and Alexandra Olteanu
How Explainability Contributes to Trust in AI
Andrea Ferrario and Michele Loi
Human Interpretation of Saliency-based Explanation Over Text
Hendrik Schuff, Alon Jacovi, Heike Adel, Yoav Goldberg and Ngoc Thang Vu
Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness
Kate Donahue, Alexandra Chouldechova and Krishnaram Kenthapadi
Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders
Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alexandra Chouldechova, Ken Holstein, Zhiwei Steven Wu and Haiyi Zhu
Imperfect Inferences: A Practical Assessment
Aaron Rieke, Vincent Southerland, Dan Svirsky and Mingwei Hsu
Interactive Model Cards: A Human-Centered Approach to Documentation for Large Language Models
Anamaria Crisan, Margaret Drouhard, Jesse Vig and Nazneen Rajani
Interdisciplinarity, Gender Diversity, and Network Structure Predict the Centrality of AI Organizations
Madalina Vlasceanu, Miroslav Dudik and Ida Momennejad
Is calibration a fairness requirement? An argument from the point of view of moral philosophy and decision theory.
Michele Loi and Christoph Heitz
It’s Just Not That Simple: An Empirical Study of the Accuracy-Explainability Trade-off in Machine Learning for Public Policy
Andrew Bell, Ian Solano-Kamaiko, Oded Nov and Julia Stoyanovich
Justice in Misinformation Detection Systems: An Analysis of Algorithms, Stakeholders, and Potential Harms
Terrence Neumann, Maria De-Arteaga and Sina Fazelpour
Keep your friends close and your counterfactuals closer: Improved learning from closest rather than plausible counterfactual explanations in an abstract setting
Ulrike Kuhl, André Artelt and Barbara Hammer
Language variation and algorithmic bias: understanding algorithmic bias in British English automatic speech recognition
Nina Markl
Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery
Aida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud and Eric Rice
Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash
Lukas Struppek, Dominik Hintersdorf, Daniel Neider and Kristian Kersting
Learning to Limit Data Collection via Scaling Laws: An Interpretation of GDPR's Data Minimization
Divya Shanmugam, Fernando Diaz, Samira Shabanian, Michele Finck and Asia Biega
Limits and Possibilities of "Ethical AI" in Open Source: A Case Study of Deepfakes
David Widder, Dawn Nafus, Laura Dabbish and James Herbsleb
Limits of individual consent and models of distributed consent in online social networks
Juniper Lovato, Antoine Allard, Randall Harp, Jeremiah Onaolapo and Laurent Hébert-Dufresne
Locality of Technical Objects and the Role of Structural Interventions for Systemic Change
Efrén Cruz Cortés, Sarah Rajtmajer and Debashis Ghosh
Making the Unaccountable Internet: The Changing Meaning of Accounting in the Early ARPANET
A. Feder Cooper and Gili Vidan
Markedness in Visual Semantic AI
Robert Wolfe and Aylin Caliskan
Marrying Fairness and Explainability in Supervised Learning
Przemyslaw Grabowicz, Nicholas Perello and Aarshee Mishra
Measuring Fairness of Rankings under Noisy Sensitive Information
Azin Ghazimatin, Matthäus Kleindessner, Chris Russell, Ziawasch Abedjan and Jacek Golebiowski
Measuring Machine Learning Software Carbon Intensity in Cloud Instances
Jesse Dodge, Taylor Prewitt, Remi Tachet des Combes, Erika Odmark, Roy Schwartz, Emma Strubell, Alexandra Sasha Luccioni, Noah A. Smith, Nicole DeCario and Will Buchanan
Mind the Gap: Autonomous Systems, the Responsibility Gap, and Moral Entanglement
Trystan Goetze
Minimax Demographic Group Fairness in Federated Learning
Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro and Miguel Rodrigues
Model Explanations with Differential Privacy
Neel Patel, Reza Shokri and Yair Zick
Model Multiplicity: Opportunities, Concerns, and Solutions
Emily Black, Manish Raghavan and Solon Barocas
Models for Classifying AI Systems: the Switch, the Ladder, and the Matrix
Jakob Mökander, Margi Sheth, David Watson and Luciano Floridi
Models for understanding and quantifying feedback in societal systems
Lydia Reader, Pegah Nohkiz, Cathleen Power, Neal Patwari, Suresh Venkatasubramanian and Sorelle Friedler
Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing Pipeline
Kevin Stangl, Avrim Blum and Ali Vakilian
Multi-disciplinary fairness considerations in machine learning for clinical trials
Isabel Chien, Nina Deliu, Richard Turner, Adrian Weller, Sofia Villar and Niki Kilbertus
Multiaccurate Proxies for Downstream Fairness
Emily Diana, Michael Kearns, Aaron Roth, Wesley Gill, Krishnaram Kenthapadi and Saeed Sharifi-Malvajerdi
Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare
Stephen Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins and Nigam Shah
NeuroView-RNN: It's About Time
Cj Barberan, Sina Alemmohammad, Naiming Liu, Randall Balestriero and Richard Baraniuk
News from Generative Artificial Intelligence is Believed Less
Chiara Longoni, Andrey Fradkin, Luca Cian and Gordon Pennycook
Normative Logics of Algorithmic Accountability
Joseph Donia
On the Existence of Simpler Machine Learning Models
Lesia Semenova, Cynthia Rudin and Ronald Parr
On the Fairness of Machine-Assisted Human Decisions
Bryce McLaughlin, Jann Spiess and Talia Gillis
On the Power of Randomization in Fair Classification and Representation
Sushant Agarwal and Amit Deshpande
Operationalizing Representational Harms in Image Captioning
Angelina Wang, Solon Barocas, Kristen Laird and Hanna Wallach
People are not coins: Morally distinct types of predictions necessitate different fairness constraints
Eleonora Viganó, Corinna Hertweck, Christoph Heitz and Michele Loi
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts
Sebastian Bordt, Michele Finck, Eric Raidl and Ulrike von Luxburg
Predictability and Surprise in Large Generative Models
Deep 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 and Jack Clark
Prediction as Extraction of Discretion
Sun-ha Hong
Privacy Considerations of COVID-19 Vaccination Certificates: A Contextual Integrity Perspective
Shikun Zhang, Yan Shvartzshnaider and Yuanyuan Feng
Promoting Ethical Awareness in Communication Analysis: Investigating Potentials and Limits of Visual Analytics for Intelligence Applications
Maximilian T. Fischer, Simon David Hirsbrunner, Wolfgang Jentner, Matthias Miller, Daniel A. Keim and Paula Helm
Promoting Fairness in Learned Models by Learning to Active Learn under Parity Constraints
Amr Sharaf, Hal Daumé III and Renkun Ni
Providing Item-side Individual Fairness for Deep Recommender Systems
Xiuling Wang and Wendy Hui Wang
Rational Shapley Values
David Watson
REAL ML: Recognizing, Exploring, and Articulating Limitations in Machine Learning Research
Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna Wallach and Jennifer Wortman Vaughan
Regulating Facial Processing Technologies: Tensions Between Legal and Technical Considerations in the Application of Illinois BIPA
Rui-Jie Yew and Alice Xiang
Reliable and Safe Use of Machine Translation in Medical Settings
Nikita Mehandru, Samantha Robertson and Niloufar Salehi
Robots Physically Amplify Malignant Stereotypes
Andrew Hundt, William Agnew, Severin Kacianka, Vicky Zeng and Matthew Gombolay
Seeing without Looking: Analysis Pipeline for Child Sexual Abuse Datasets
Camila Laranjeira da Silva, João Macedo, Sandra Avila and Jefersson dos Santos
Selection in the Presence of Implicit Bias: The Advantage of Intersectional Constraints
Anay Mehrotra, Bary S. R. Pradelski and Nisheeth K. Vishnoi
Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theory
Harmanpreet Kaur, Eytan Adar, Eric Gilbert and Cliff Lampe
Should attention be all we need? The ethical and epistemic implications of unification in machine learning
Nic Fishman and Leif Hancox-Li
Smallset Timelines: A Visual Representation of Data Preprocessing Decisions
Lydia R. Lucchesi, Petra Kuhnert, Jenny L. Davis and Lexing Xie
Social Inclusion in Curated Contexts: Insights from Museum Practices
Han-Yin Huang and Cynthia Liem
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 Guidelines
You Jeen Ha
Subverting Fair Image Search with Generative Adversarial Perturbations
Avijit Ghosh, Matthew Jagielski and Christo Wilson
Subverting machines, fluctuating identities: Re-learning human categorization
Jackie Kay, Christina Lu and Kevin McKee
Surfacing Racial Stereotypes through Identity Portrayal
Gauri Kambhatla, Ian Stewart and Rada Mihalcea
System Safety and Artificial Intelligence
Roel Dobbe
Tackling Algorithmic Disability Discrimination in the Hiring Process: An Ethical, Legal and Technical Analysis
Maarten Buyl, Christina Cociancig, Cristina Frattone and Nele Roekens
Taxonomy of Risks posed by Large Language Models
Laura 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 Isaac, Julia Haas, Sean Legassick, Geoffrey Irving and Iason Gabriel
Tech Worker Organizing
William Boag, Harini Suresh, Bianca Lepe and Catherine D'Ignazio
Testing Concerns about Technology's Behavioral Impacts with N-of-one Trials
Nathan Matias, Eric Pennington and Zenobia Chan
The AI Ethics Money Problem: It's @ FAccT
Meg Young, Michael Katell and Peaks Krafft
The Alchemy of Trust: The Creative Act of Designing Trustworthy Socio-Technical Systems
Lauren Thornton, Bran Knowles and Gordon Blair
The Algorithmic Imprint
Upol Ehsan, Ranjit Singh, Jacob Metcalf and Mark Riedl
The Case for a Legal Compliance API for the Enforcement of the EU’s Digital Services Act on Social Media Platforms
Catalina Goanta, Thales Bertaglia and Adriana Iamnitchi
The Conflict Between Explainable and Accountable Decision-Making Algorithms
Gabriel Lima, Nina Grgić-Hlača, Jinkeun Jeong and Meeyoung Cha
The Death of the Legal Subject: How Predictive Algorithms Are (Re)constructing Legal Subjectivity
Katrina Geddes
The Effects of Crowd Workers Biases in Fact-Checking Tasks
Tim Draws, David La Barbera, Michael Soprano, Kevin Roitero, Davide Ceolin, Alessandro Checco and Stefano Mizzaro
The Fallacy of AI Functionality
Inioluwa Deborah Raji, I. Elizabeth Kumar, Aaron Horowitz and Andrew Selbst
The forgotten margins of AI ethics
Abeba Birhane, Elayne Ruane, Thomas Laurent, Matthew S. Brown, Johnathan Flowers, Anthony Ventresque and Christopher L. Dancy
The Long Arc of Fairness: Formalisations and Ethical Discourse
Pola Schwöbel and Peter Remmers
The Model Card Authoring Toolkit: Toward Community-centered, Deliberation-driven AI Design
Hong Shen, Leijie Wang, Wesley Hanwen Deng, Ciell, Ronald Velgersdijk and Haiyi Zhu
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations
Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz and Marzyeh Ghassemi
The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models
Greg d'Eon, Jason d'Eon, James R. Wright and Kevin Leyton-Brown
The Values Encoded in Machine Learning Research
Abeba Birhane, Pratyusha Kalluri, Dallas Card, William Agnew, Ravit Dotan and Michelle Bao
Theories of Gender in Natural Language Processing
Hannah Devinney, Jenny Björklund and Henrik Björklund
Towards a multi-stakeholder value-based assessment framework for algorithmic systems
Mireia Yurrita, Dave Murray-Rust, Agathe Balayn and Alessandro Bozzon
Towards Designing Responsible Trust in AI Systems: A Communication Perspective
Q.Vera Liao and S. Shyam Sundar
Towards Fair Unsupervised Learning
Francois Buet-Golfouse and Islam Utyagulov
Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection
Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So and Catherine D'Ignazio
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation
Angelina Wang, Vikram Ramaswamy and Olga Russakovsky
Trade-offs between Group Fairness Metrics in Societal Resource Allocation
Tasfia Mashiat, Xavier Gitiaux, Huzefa Rangwala, Patrick Fowler and Sanmay Das
Treatment Effect Risk: Bounds and Inference
Nathan Kallus
Trucks Don’t Mean Trump: Diagnosing Human Error in Image Analysis
J.D. Zamfirescu-Pereira, Jerry Chen, Emily Wen, Allison Koenecke, Nikhil Garg and Emma Pierson
Uncertainty Estimation and the Social Planner’s Problem: Why Sample Complexity Matters
Cyrus Cousins
Understanding and being understood: user strategies for identifying and recovering from mistranslations in machine translation-mediated chat
Samantha Robertson and Mark Díaz
Understanding Lay Users' Needs of Counterfactual Explanations for Everyday Recommendations
Ruoxi Shang, K. J. Kevin Feng and Chirag Shah
What Does it Mean for a Language Model to Preserve Privacy?
Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri and Florian Tramèr
What is Proxy Discrimination?
Michael Carl Tschantz
What is the Bureaucratic Counterfactual? Categorical versus Algorithmic Prioritization in U.S. Social Policy
Rebecca Johnson and Simone Zhang
What People Think AI Should Infer From Faces
Severin Engelmann, Chiara Ullstein, Orestis Papakyriakopoulos and Jens Grossklags
When learning becomes impossible
Nicholas Asher and Julie Hunter
Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem
Sasha Costanza-Chock, Inioluwa Deborah Raji and Joy Buolamwini
Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging
Riccardo Fogliato, Shreya Chappidi, Matthew Lungren, Paul Fisher, Diane Wilson, Michael Fitzke, Mark Parkinson, Eric Horvitz, Kori Inkpen and Besmira Nushi