‘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