PUBLICATIONS
Sandhya Saisubramanian, Shlomo Zilberstein and Ece Kamar. Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems, AI Magazine, 2022
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Joon Sung Park, Michael S Bernstein, Robin N Brewer, Ece Kamar, Meredith Ringel Morris. Understanding the Representation and Representativeness of Age in AI Data Sets, Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 2021
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Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W Duncan Wadsworth, Hanna Wallach. Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs, Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 2021
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Jonathan Martinez, Kobi Gal, Ece Kamar, Levi HS Lelis. Improving the Performance-Compatibility Tradeoff with Personalized Objective Functions, Proceedings of the AAAI Conference on Artificial Intelligence, 2021
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Gagan Bansal, Tongshuang Wu, Joyce Zhou, Raymond Fok, Besmira Nushi, Ece Kamar, Marco Tulio Ribeiro, Daniel Weld. Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance, Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, 2021
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Ramya Ramakrishnan, Vaibhav Unhelkar, Ece Kamar, Julie Shah. A Bayesian Approach to Identifying Representational Errors, arXiv, 2021
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Joon Sung Park, Danielle Bragg, Ece Kamar, Meredith Ringel Morris. Designing an Online Infrastructure for Collecting AI Data from People with Disabilities, Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 2021
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Sahil Singla, Besmira Nushi, Shital Shah, Ece Kamar, Eric Horvitz. Understanding Failures of Deep Networks via Robust Feature Extraction, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021
Kaivalya Rawal, Ece Kamar, Himabindu Lakkaraju. Algorithmic recourse in the wild: Understanding the impact of data and model shifts, arXiv, 2020
Sandhya Saisubramanian, Ece Kamar, Shlomo Zilberstein. A Multi-objective Approach to Mitigate Negative Side Effects, Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence, 2021
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Bryan Wilder, Eric Horvitz and Ece Kamar. Learning to Complement Humans, IJCAI 2020.
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Sandhya Saisubramanian, Shlomo Zilberstein and Ece Kamar. Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems, IJCAI 2020.
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Megha Srivastava, Besmira Nushi, Ece Kamar, Shital Shah and Eric Horvitz. An Empirical Analysis of Backward Compatibility in Machine Learning Systems, KDD 2020.
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Ivan Evtimov, Weidong Cui, Ece Kamar, Emre Kiciman, Tadayoshi Kohno and Jerry Li. Security and Machine Learning in the Real World,
arXiv preprint arXiv:2007.07205
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Gagan Bansal, Besmira Nushi, Ece Kamar, Eric Horvitz and Daniel Weld. Optimizing AI for Teamwork, arXiv preprint arXiv:2004.13102
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Keri Mallari, Kori Inkpen, Paul Johns, Sarah Tan, Divya Ramesh and Ece Kamar. Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism, CHI 2020.
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Anthony Liu, Santiago Guerra, Isaac Fung, Gabriel Matute, Ece Kamar and Walter Lasecki. Towards Hybrid Human-AI Workflows for Unknown Unknown Detection, The Web Conference 2020.
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Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach and Meredith Ringel Morris. Toward Fairness in AI for People with Disabilities, ACM SIGACCESS Accessibility and Computing 2020
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Ramya Ramakrishnan, Ece Kamar, Debadeepta Dey, Eric Horvitz and Julie Shah. Blind Spot Detection for Safe Sim-to-Real Transfer, Journal of Artificial Intelligence Research 67, 191-234
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Ramprasaath R. Selvaraju, Purva Tendulkar, Devi Parikh, Eric Horvitz, Marco Ribeiro, Besmira Nushi, Ece Kamar. SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions, CVPR 2020. Dataset available here.
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Iyad Rahwan, Manuel Cebrian, Nick Obradovich, Josh Bongard, Jean-François Bonnefon, Cynthia Breazeal, Jacob W Crandall, Nicholas A Christakis, Iain D Couzin, Matthew O Jackson, Nicholas R Jennings, Ece Kamar, Isabel M Kloumann, Hugo Larochelle, David Lazer, Richard McElreath, Alan Mislove, David C Parkes, Margaret E Roberts, Azim Shariff, Joshua B Tenenbaum and Michael Wellman. Machine Behavior, Nature 2019
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Gagan Bansal, Besmira Nushi, Ece Kamar, Walter Lasecki, Daniel S. Weld and Eric Horvitz. Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance, HCOMP 2019 **Statement about author's misconduct
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Shayan Doroudi, Ece Kamar, and Emma Brunskill. Not Everyone Writes Good Examples but Good Examples Can Come from Anywhere. HCOMP 2019.
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Andi Peng, Besmira Nushi, Emre Kiciman, Kori Inkpen, Siddharth Suri, Ece Kamar. What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring, HCOMP 2019
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Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach and Meredith Ringel Morris. Toward Fairness in AI for People with Disabilities: A Research Roadmap, ACM Assets 2019
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Saleema Amershi, Andrew Begel, Christian Bird, Robert DeLine, Harald Gall, Ece Kamar, Nachiappan Nagappan, Besmira Nushi and Thomas Zimmermann. Software Engineering for Machine Learning: A Case Study, Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice 2019 Best paper award.
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Yongsung Kim, Adam Fourney and Ece Kamar. Studying Preferences and Concerns about Information Disclosure in Email Notifications, WWW 2019
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Gagan Bansal, Besmira Nushi, Ece Kamar, Walter Lasecki, Daniel S. Weld and Eric Horvitz. Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff, AAAI 2019 **Statement about author's misconduct
Ramya Ramakrishnan, Ece Kamar, Besmira Nushi, Debadeepta Dey, Julie Shah and Eric Horvitz. Overcoming Blind Spots in the Real World: Leveraging Complementary Abilities for Joint Execution, AAAI 2019
Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Jure Leskovec. Faithful and Customizable Explanations of Black Box Models, AIES 2019
Besmira Nushi, Ece Kamar and Eric Horvitz. Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure, HCOMP 2018.
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Ramya Ramakrishnan, Ece Kamar, Debadeepta Dey, Julie Shah and Eric Horvitz. Discovering Blind Spots in Reinforcement Learning, AAMAS 2018.
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Avi Segal, Kobi Gal, Ece Kamar, Eric Horvitz and Grant Miller. Optimizing Interventions via Offline Policy Evaluation: Studies in Citizen Science. AAAI, 2018.
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Sean Andrist, Dan Bohus, Ece Kamar and Eric Horvitz. What Went Wrong and Why? Diagnosing Situated Interaction Failures in the Wild. International Conference on Social Robotics 2017.
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Elliot Salisbury, Ece Kamar and Meredith Morris. Toward Scalable Social Alt Text: Conversational Crowdsourcing as a Tool for Refining Vision-to-Language, HCOMP 2017 (Best paper award)
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Harmanpreet Kaur, Mitchell Gordon, Yiwei Yang, Jeffrey P. Bigham, Jaime Teevan, Ece Kamar and Walter S. Lasecki. Crowdmask: Using Crowds to Preserve Privacy in Crowd-powered Systems via Progressive Filtering. HCOMP 2017.
Debarun Kar, Subhasree Sengupta, Ece Kamar, Eric Horvitz and Milind Tambe. Believe It or Not: Modeling Adversary Belief Formation in Stackelberg Security Games with Varying Information. Advances in Cognitive Systems 2017.
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Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Eric Horvitz. Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration, AAAI 2017.
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Besmira Nushi, Ece Kamar, Donald Kossmann and Eric Horvitz. On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems, AAAI 2017.
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Joseph Chee Chang, Saleema Amershi and Ece Kamar. Revolt: Collaborative Crowdsourcing for Labeling Machine Learning Datasets, CHI 2017
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Niloufar Salehi, Jaime Teevan, Shamsi Iqbal and Ece Kamar. Communicating Context to the Crowd for Complex Writing Tasks, CSCW 2017 (Honorable mention award).
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Ece Kamar. Hybrid workplaces of the future. XRDS: The ACM Magazine for Students 2016.
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Cathy Wu, Ece Kamar and Eric Horvitz. Clustering for Set Partitioning with a Case Study in Ridesharing, IEEE Intelligent Transportation Systems Conference (IEEE ITSC), November 2016. (Best paper award).
Cathy Wu, K. Shankari, Ece Kamar, Randy Katz, David Culler, Christos Papadimitriou, Eric Horvitz and Alexandre Bayen. Optimizing the Diamond Lane: A More Tractable Carpool Problem and Algorithms, IEEE Intelligent Transportation Systems Conference, 2016.
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Ece Kamar. Directions in Hybrid Intelligence: Complementing AI Systems with Human Intelligence. IJCAI Invited Talk: Early Career Spotlight Track. 2016. Talk Slides
Avi Segal, Ya'akov Gal, Ece Kamar, Eric Horvitz, Alex Bower and Grant Miller. Intervention Strategies for Increasing Engagement in Volunteer-Based Crowdsourcing. In Proceedings of IJCAI 2016.
Ofra Amir, Ece Kamar, Andrey Kolobov and Barbara Grosz. Interactive Teaching Strategies for Agent Training. In Proceedings of IJCAI 2016.
Shayan Doroudi, Ece Kamar, Emma Brunskill and Eric Horvitz. Toward a Learning Science for Complex Crowdsourcing Tasks. In Proceedings of CHI 2016.
Ece Kamar, Ashish Kapoor and Eric Horvitz. Identifying and Accounting for Task-Dependent Bias in Crowdsourcing. In Proceedings of HCOMP 2015.
Christopher Lin, Andrey Kolobov, Ece Kamar and Eric Horvitz. Metareasoning for Planning Under Uncertainty. In Proceedings of IJCAI 2015.
Ece Kamar and Eric Horvitz. Planning for Crowdsourcing Hierarchical Tasks. In Proceedings of AAMAS 2015.
Margaret Mitchell, Dan Bohus and Ece Kamar. Crowdsourcing Language Generation Templates for Dialogue Systems. In Proceedings of INLG and SIGDIAL 2014.
Christopher Lin, Ece Kamar and Eric Horvitz. Signals in the Silence: Models of Implicit Feedback in a Recommendation System for Crowdsourcing. In Proceedings of AAAI 2014 - (Version updated with corrections).
Adish Singla, Eric Horvitz, Ece Kamar and Ryen White. Stochastic Privacy. In Proceedings of AAAI 2014 (Extended Version with Proofs).
Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, and Ashish Kapoor. Gauss Meets Canadian Traveler: Shortest-Path Problems with Natural Dynamics. In Proceedings of AAMAS 2014.
Walter Lasecki, Jamie Teevan and Ece Kamar. Information Extraction and Manipulation Threats in Crowd-Powered Systems. In Proceedings of CSCW 2014.
Andrew Mao, Ece Kamar, Yiling Chen, Eric Horvitz, Megan E. Schwamb, Chris J. Lintott, and Arfon M. Smith. Volunteering vs. Work for Pay: Incentives and Tradeoffs in Crowdsourcing. In Proceedings of HCOMP 2013.
Andrew Mao, Ece Kamar, and Eric Horvitz. Why Stop Now? Predicting Worker Engagement in Online Crowdsourcing. In Proceedings of HCOMP 2013.
Ece Kamar, Ashish Kapoor and Eric Horvitz. Lifelong Learning for Acquiring the Wisdom of the Crowd. In Proceedings of IJCAI 2013.
Stephanie Rosenthal, Dan Bohus, Ece Kamar and Eric Horvitz. Look versus Leap: Computing Value of Information with High-Dimensional Streaming Evidence. In Proceedings of IJCAI 2013.
Ece Kamar and Eric Horvitz. Light at the End of the Tunnel: A Monte Carlo Approach to Computing Value of Information. In Proceedings of AAMAS 2013.
Ece Kamar, Ya’akov (Kobi) Gal and Barbara J. Grosz. Modeling Information Exchange Opportunities For Effective Human-Computer Teamwork. In Artificial Intelligence Journal, 2013.
Ece Kamar, Severin Hacker and Eric Horvitz. Combining Human and Machine Intelligence in Large-scale Crowdsourcing. In Proceedings of AAMAS 2012.
William Wang, Dan Bohus, Ece Kamar and Eric Horvitz. Crowdsourcing the Acquisition of Natural Language Corpora: Methods and Observations. In Proceedings of SLT 2012.
Ece Kamar. Reasoning Effectively Under Uncertainty for Human-Computer Teamwork. Ph.D. Thesis, Harvard University, May 2010.
Ece Kamar, Ya’akov Gal and Barbara J. Grosz. Modeling User Perception of Interaction Opportunities for Effective Teamwork. SIN09, In Proceedings of IEEE SocialCom 2009.
Ece Kamar and Eric Horvitz. Collaboration and Shared Plans in the Open World: Studies of Ridesharing. IJCAI 2009, Technical Paper
Ece Kamar and Eric Horvitz. Generating Shared Transportation Plans Under Varying Preferences: Ridesharing Models and Mechanisms. Microsoft Research Technical report, MSR-TR-2009-2011, April 2009.
Ece Kamar, Ya’akov Gal and Barbara J. Grosz. Incorporating Helpful Behavior into Collaborative Planning. In Proceedings of AAMAS 2009.
Ece Kamar, Eric Horvitz and Chris Meek. Mobile Opportunistic Commerce: Mechanisms, Architecture, and Application. In Proceedings of AAMAS 2008.
Workshop Papers and Short Papers
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Sarah Tan, Julius Adebayo, Kori Inkpen and Ece Kamar. Investigating Human + Machine Complementarity for Recidivism Predictions. NIPS Workshop on Ethical, Social and Governance Issues in AI
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Yongsung Kim, Adam Fourney and Ece Kamar. Studying Preferences and Concerns about Information Disclosure in Email Notifications
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Himabindu Lakkaraju, Ece Kamar Rich Caruana and Jure Leskovec. Interpretable & Explorable Approximations of Black Box Models. FATML Workshop, KDD 2017.
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Amulya Yadav, Hau Chan, Albert Jiang, Eric Rice, Ece Kamar, Barbara Grosz, Milind Tambe. POMDPs for Assisting Homeless Shelters - Computational and Deployment Challenges. AAMAS 2016 IDEAS Workshop
Amulya Yadav, Ece Kamar, Barbara Grosz, Milind Tambe. HEALER: POMDP Planning for Scheduling Interventions among Homeless Youth. Demonstration Paper at AAMAS 2016
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Besmira Nushi, Ece Kamar, Donald Kossmann and Eric Horvitz. A Human-in-the-loop Approach for Troubleshooting Machine Learning Systems, NIPS Workshop on Future of Interactive Learning Machines 2017.
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Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Eric Horvitz. Discovering Unknown Unknowns of Predictive Models, NIPS Workshop on Reliable Machine Learning in the Wild 2017.
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Ece Kamar and Lydia Manikonda. Complementing the Execution of AI Systems with Human Computation, AAAI Workshop on Crowdsourcing, Deep Learning and Artificial Intelligence Agents 2017.
Ece Kamar. Hybrid Intelligence and the Future of Work. In Proceedings of the Productivity Decomposed: Getting Big Things Done with Little Microtasks Workshop at CHI 2016.
Cathy Wu, Ece Kamar and Eric Horvitz. Clustering for Set Partitioning: A Case Study in Carpooling. In Proceedings of the Workshop on Optimization for Machine Learning (OPT) at NIPS 2015.
Walter. S. Lasecki, Jaime Teevan and Ece Kamar. The Cost of Asking Crowd Workers to Behave Maliciously. In Proceedings of the Workshop on Human-Agent Interaction Design and Models (HAIDM 2015) at AAMAS 2015.
Walter S. Lasecki, Mitchell Gordon, Jaime Teevan, Ece Kamar and Jeff P. Bigham. Preserving Privacy in Crowd-Powered Systems. In Proceedings of the Workshop on Human-Agent Interaction Design and Models (HAIDM 2015) at AAMAS 2015.
Walter Lasecki, Ece Kamar and Dan Bohus. Conversations in the Crowd: Collecting Data for Task-Oriented Dialog Learning. In Proceedings of the Human Computation Workshop on Scaling Speech and Language Understanding and Dialog through Crowdsourcing at HCOMP 2013.
Dan Bohus, Ece Kamar and Eric Horvitz. Towards Situated Collaboration. In NAACL Workshop on Future Directions and Challenges in Spoken Dialog Systems: Tools and Data, 2012.
Ece Kamar and Eric Horvitz. Incentives for Truthful Reporting in Crowdsourcing. In Proceedings of AAMAS 2012, Short paper.
Ece Kamar and Eric Horvitz. Incentives and Truthful Reporting in Consensus-centric Crowdsourcing. Microsoft Research Technical report, MSR-TR-2012-16, February 2012.
Paul Bennett, Ece Kamar and Gabriella Kazai. MSRC at TREC 2011 Crowdsourcing Track. In Proceedings of TREC 2011.
Ece Kamar and Eric Horvitz. Jogger: Models for Context-Sensitive Reminding. In Proceedings of AAMAS 2011, Short paper.
Ece Kamar and Eric Horvitz. Investigation of Principles of Context-Sensitive Reminding. Microsoft Research Technical report, MSR-TR-2010-174, October 2010.
Ece Kamar. Managing Helpful Behavior in Collaborative Activities of Heterogeneous Agent Groups. IJCAI 2009, Doctoral Consortium Abstract
Ece Kamar, Barbara J. Grosz and David Sarne. Modeling User Perception of Interaction Opportunities in Collaborative Human-Computer Settings. In Proceedings of AAAI 2007, Student Abstract and Poster Program
Ece Kamar and Barbara J. Grosz. Applying MDP Approaches For Estimating Outcome of Interaction in Collaborative Human-Computer Settings. In Proceedings of Workshop on Multi-agent Sequential Decision Making in Uncertain Domains (MSDM) 2007.
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