| 2019 | A Hybrid Approach to Identifying Unknown Unknowns of Predictive Models. Colin Vandenhof |
| 2019 | AI-Based Request Augmentation to Increase Crowdsourcing Participation. Junwon Park, Ranjay Krishna, Pranav Khadpe, Li Fei-Fei, Michael S. Bernstein |
| 2019 | Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance. Gagan Bansal, Besmira Nushi, Ece Kamar, Walter S. Lasecki, Daniel S. Weld, Eric Horvitz |
| 2019 | Can You Explain That? Lucid Explanations Help Human-AI Collaborative Image Retrieval. Arijit Ray, Yi Yao, Rakesh Kumar, Ajay Divakaran, Giedrius Burachas |
| 2019 | Crowdsourced PAC Learning under Classification Noise. Shelby Heinecke, Lev Reyzin |
| 2019 | Fair Work: Crowd Work Minimum Wage with One Line of Code. Mark E. Whiting, Grant Hugh, Michael S. Bernstein |
| 2019 | Gamification of Loop-Invariant Discovery from Code. Andrew T. Walter, Benjamin Boskin, Seth Cooper, Panagiotis Manolios |
| 2019 | Going against the (Appropriate) Flow: A Contextual Integrity Approach to Privacy Policy Analysis. Yan Shvartzshnaider, Noah J. Apthorpe, Nick Feamster, Helen Nissenbaum |
| 2019 | How Do We Talk about Other People? Group (Un)Fairness in Natural Language Image Descriptions. Jahna Otterbacher, Pinar Barlas, Styliani Kleanthous, Kyriakos Kyriakou |
| 2019 | Human Evaluation of Models Built for Interpretability. Isaac Lage, Emily Chen, Jeffrey He, Menaka Narayanan, Been Kim, Samuel J. Gershman, Finale Doshi-Velez |
| 2019 | Interpretable Image Recognition with Hierarchical Prototypes. Peter Hase, Chaofan Chen, Oscar Li, Cynthia Rudin |
| 2019 | Learning to Predict Population-Level Label Distributions. Tong Liu, Akash Venkatachalam, Pratik Sanjay Bongale, Christopher M. Homan |
| 2019 | Not Everyone Writes Good Examples but Good Examples Can Come from Anywhere. Shayan Doroudi, Ece Kamar, Emma Brunskill |
| 2019 | Platform-Related Factors in Repeatability and Reproducibility of Crowdsourcing Tasks. Rehab K. Qarout, Alessandro Checco, Gianluca Demartini, Kalina Bontcheva |
| 2019 | Proceedings of the Seventh AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2019, Stevenson, WA, USA, October 28-30, 2019. Edith Law, Jennifer Wortman Vaughan |
| 2019 | Progression in a Language Annotation Game with a Purpose. Chris Madge, Juntao Yu, Jon Chamberlain, Udo Kruschwitz, Silviu Paun, Massimo Poesio |
| 2019 | Second Opinion: Supporting Last-Mile Person Identification with Crowdsourcing and Face Recognition. Vikram Mohanty, Kareem Abdol-Hamid, Courtney Ebersohl, Kurt Luther |
| 2019 | Studying the "Wisdom of Crowds" at Scale. Camelia Simoiu, Chiraag Sumanth, Alok Shankar Mysore, Sharad Goel |
| 2019 | Testing Stylistic Interventions to Reduce Emotional Impact of Content Moderation Workers. Sowmya Karunakaran, Rashmi Ramakrishan |
| 2019 | The Effects of Meaningful and Meaningless Explanations on Trust and Perceived System Accuracy in Intelligent Systems. Mahsan Nourani, Samia Kabir, Sina Mohseni, Eric D. Ragan |
| 2019 | Understanding the Impact of Text Highlighting in Crowdsourcing Tasks. Jorge Ramírez, Marcos Báez, Fabio Casati, Boualem Benatallah |
| 2019 | What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring. Andi Peng, Besmira Nushi, Emre Kiciman, Kori Inkpen, Siddharth Suri, Ece Kamar |
| 2019 | Who Is in Your Top Three? Optimizing Learning in Elections with Many Candidates. Nikhil Garg, Lodewijk Gelauff, Sukolsak Sakshuwong, Ashish Goel |