On the Nature of Bias Percolation: Assessing Multiaxial Collaboration in Human-AI Systems

Andi Peng, Besmira Nushi, Kori Inkpen, Emre Kiciman, Ece Kamar

Designing for Digital Agency: Equity Perspectives and AI in K-12 Education

Ariam Mogos, Laura McBain, Carissa Carter, Megan Stariha, Lisa Kay Solomon

Measuring Social Biases of Crowd Workers using Counterfactual Queries

Bhavya Ghai, Q. Vera Liao, Yunfeng Zhang, Klaus Mueller

Getting Fairness Right: Towards a Toolbox for Practitioners

Boris Ruf, Chaouki Boutharouite, Marcin Detyniecki

Designing for Human-Centered AI in the U.S.Child-Welfare System

Devansh Saxena, Shion Guha

The “Crooked Set Up”: Algorithmic Fairness and the Organizational Citizen

Elizabeth Anne Watkins

A Call for Universities to Develop Requirements for Community Engagement in AI Research

Emily Black, Joshua Williams, Michael Madaio, Priya Donti

Learning to Diversify from Human Judgments: Research Directions and Open Challenges

Emily Denton, Hansa Srinivasan, Dylan Baker, Jilin Chen, Alex Beutel, Tulsee Doshi, Ed H. Chi

Crowdworkers Are Not Judges: Rethinking Crowdsourced VignetteStudies as a Risk Assessment Evaluation Technique

Emma Lurie, Deirdre K. Mulligan

Bias as a Distinct Factor in Human Ratings of Machine Labeling

Eric P.S Baumer, Amin Hosseiny Marani

A Human in the Loop is Not Enough: The Need for Human-Subject Experiments in Facial Recognition

Forough Poursabzi-Sangdeh, Samira Samadi, Jennifer Wortman Vaughan, Hanna Wallach

Responsible AI and Its Stakeholders

Gabriel Lima, Meeyoung Cha

Designing AI with Monsters

Graham Dove

Profit, Fairness, or Both? Setting Priorities in Data Annotation

Gunay Kazimzade, Milagros Miceli

Fair and Responsible AI: A Focus on the Ability to Contest

Henrietta Lyons, Eduardo Velloso, Tim Miller

Emerging Perspectives on Medical Decision Support: Co-Designing XAI

Henrik Mucha, Sebastian Robert

“Public(s)-in-the-Loop”: Facilitating Deliberation of Algorithmic Decisions in Contentious Public Policy Domains

Hong Shen, Ángel Alexander Cabrera, Adam Perer, Jason Hong

Your AI Boss Says, "You are Fired, but Your Colleague Got Promoted!"

Hyanghee Park, Daehwan Ahn, Kartik Hosanagar, Joonhwan Lee

Exploring User Opinions of Fairness in Recommender Systems

Jessie Smith, Nasim Sonboli, Casey Fiesler, Robin Burke

Evidence-based Explanation to Promote Fairness in AI Systems

Juliana Jansen Ferreira, Mateus de Souza Monteiro

Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics

Donald Martin Jr., Vinodkumar Prabhakaran, Jill Kuhlberg, Andrew Smart, William S. Issac

Need for Organizational Performance Metrics to Support Fairness in AI

Michael A. Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach

What Do Users Want in an Explanation?: User Preferences for AI Explainability in Context-Aware Systems

Morteza Behrooz, Julia Haines, Marco Zamarato, Paige Pritchard, Andrew Smart

Lessons from the Deployment of an Algorithmic Tool in Child Welfare

Riccardo Fogliato, Maria De-Arteaga, Alexandra Chouldechova

Explaining Quantitative Measures of Fairness

Scott M. Lundberg

Trust Evolution Over Time in Explainable AI for Fake News Detection

Sina Mohseni, Fan Yang, Shiva Pentyala, Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric Ragan

How Does Perceived Fairness Differ? Exploring Multicultural Landscape for Ethical AI Design

Sullam Jeoung, Youngsam Chun

Implications of Conversational Artificial Intelligence

Tonya Nguyen, Niloufar Salehi

Harnessing Explanations to Bridge AI and Humans

Vivian Lai, Samuel Carton, Chenhao Tan

AI-Mediated Exchange Theory

Xiao Ma, Taylor W. Brown