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Although artificial intelligence (AI) systems are becoming increasingly indispensable, research into how humans rely on these systems (AI reliance) is lagging behind.
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Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them
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Recommended for you: The Netflix Prize and the production of algorithmic culture
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An analysis of data quality: Professional panels, student subject pools, and Amazon’s Mechanical Turk
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Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
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Correctional offender management profiles for alternative sanctions (COMPAS)
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Algorithm appreciation: People prefer algorithmic to human judgment
Jennifer M. Logg, Julia A. Minson, and Don A. Moore. 2019 · 2018
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Task-Dependent Algorithm Aversion
Noah Castelo, Maarten W. Bos, and Donald R. Lehmann. 2019 · 2019
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Human Decision Making with Machine Assistance: An Experiment on Bailing and Jailing
Nina Grgić-Hlača, Christoph Engel, and Krishna P. Gummadi. 2019 · 2019
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Beauty’s in the AI of the Beholder: How AI Anchors Subjective and Objective Predictions
Lauren Rhue. 2019 · 2019
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The sociotechnical axis of cohesion for the IS discipline: Its historical legacy and its continued relevance
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Evaluating Local Interpretable Model-Agnostic Explanations on Clinical Machine Learning Classification Models. In 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS) . IEEE, Rochester, MN, USA, 7–12
Nesaretnam Barr Kumarakulasinghe, Tobias Blomberg, Jintai Liu, Alexandra Saraiva Leao, and Panagiotis Papapetrou. 2020 · 2020
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Outlier detection: Methods, models, and classification
Azzedine Boukerche, Lining Zheng, and Omar Alfandi. 2020 · 2020
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An MTurk crisis? Shifts in data quality and the impact on study results
Michael Chmielewski and Sarah C Kucker. 2020 · 2020
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Assessing trust versus reliance for technology platforms by systematic literature review
Trevor Deley and Elizabeth Dubois. 2020 · 2020
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The shape of and solutions to the MTurk quality crisis
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Adaptive trust calibration for human-AI collaboration
Kazuo Okamura and Seiji Yamada. 2020 · 2020
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Psychophysiological Modeling of Trust In Technology: Influence of Feature Selection Methods
Ighoyota Ben Ajenaghughrure, Sonia Cláudia Da Costa Sousa, and David Lamas. 2021 · 2021
Cited alongside, same era.
AI-Assisted Human Labeling: Batching for Efficiency without Overreliance
Zahra Ashktorab, Michael Desmond, Josh Andres, Michael Muller, Narendra Nath Joshi, Michelle Brachman, Aabhas Sharma, Kristina Brimijoin, Qian Pan, Christine T. Wolf, Evelyn Duesterwald, Casey Dugan, Werner Geyer, and Darrell Reimer. 2021 · 2021
Cited alongside, same era.
Does the whole exceed its parts? the effect of ai explanations on complementary team performance. In Proceedings of the 2021 CHI conference on human factors in computing systems . 1–16
Gagan Bansal, Tongshuang Wu, Joyce Zhou, Raymond Fok, Besmira Nushi, Ece Kamar, Marco Tulio Ribeiro, and Daniel Weld. 2021a · 2021
Cited alongside, same era.
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems . ACM, Yokohama Japan, 1–16
Gagan Bansal, Tongshuang Wu, Joyce Zhou, Raymond Fok, Besmira Nushi, Ece Kamar, Marco Tulio Ribeiro, and Daniel Weld. 2021b · 2021
Cited alongside, same era.
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making
Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney, Amit Dhurandhar, and Richard Tomsett. 2022 · 2022
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Understanding the Role of Explanation Modality in AI-assisted Decision-making. In Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization . ACM, Barcelona Spain, 223–233
Vincent Robbemond, Oana Inel, and Ujwal Gadiraju. 2022 · 2022
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A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making. In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (Oxford, United Kingdom) (AIES ’22) . Association for Computing Machinery, New York, NY, USA, 617–626
Max Schemmer, Patrick Hemmer, Maximilian Nitsche, Niklas Kühl, and Michael Vössing. 2022 · 2022
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A conceptual model of trust, perceived risk, and reliance on AI decision aids
Elizabeth Solberg, Magnhild Kaarstad, Maren H Rø Eitrheim, Rossella Bisio, Kine Reegrd, and Marten Bloch. 2022 · 2022
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The role of domain expertise in trusting and following explainable AI decision support systems
Sarah Bayer, Henner Gimpel, and Moritz Markgraf. 2022 · 2021
Cited alongside, same era.
Watch Me Improve—Algorithm Aversion and Demonstrating the Ability to Learn
Benedikt Berger, Martin Adam, Alexander Rühr, and Alexander Benlian. 2021 · 2021
Cited alongside, same era.
Humans rely more on algorithms than social influence as a task becomes more difficult
Eric Bogert, Aaron Schecter, and Richard T. Watson. 2021 · 2021
Cited alongside, same era.
To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making
Zana Buçinca, Maja Barbara Malaya, and Krzysztof Z. Gajos. 2021 · 2021
Cited alongside, same era.
A possible conceptualization of the information systems (IS) artifact: A general systems theory perspective 1
Sutirtha Chatterjee, Suprateek Sarker, Michael J Lee, Xiao Xiao, and Amany Elbanna. 2021 · 2021
Cited alongside, same era.
You’d Better Stop! Understanding Human Reliance on Machine Learning Models under Covariate Shift. In ACM Int. Conf. Proc. Ser. Association for Computing Machinery, 120–129
C.-W. Chiang and M. Yin. 2021 · 2021
Cited alongside, same era.
Proposal for a Regulation of the European Parliament and of the Council Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act) and Amending Certain Union Legislative Acts
EU. 2021 · 2021
Cited alongside, same era.
Who is the Expert? Reconciling Algorithm Aversion and Algorithm Appreciation in AI-Supported Decision Making
Yoyo Tsung-Yu Hou and Malte F. Jung. 2021 · 2021
Cited alongside, same era.
Improving Human Situation Awareness in AI-Advised Decision Making. In 2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS) . IEEE, Orlando, FL, USA, 1–6
Divya K. Srivastava, J. Mason Lilly, and Karen M. Feigh. 2022 · 2022
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AI-Assisted Decision-making: a Cognitive Modeling Approach to Infer Latent Reliance Strategies
Heliodoro Tejeda, Aakriti Kumar, Padhraic Smyth, and Mark Steyvers. 2022 · 2022
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Capable but Amoral? Comparing AI and Human Expert Collaboration in Ethical Decision Making. In Conf Hum Fact Comput Syst Proc . Association for Computing Machinery
S. Tolmeijer, M. Christen, S. Kandul, M. Kneer, and A. Bernstein. 2022 · 2022
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Responsible AI: Concepts, critical perspectives and an Information Systems research agenda
Polyxeni Vassilakopoulou, Elena Parmiggiani, Arisa Shollo, and Miria Grisot. 2022 · 2022
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Assessing the communication gap between AI models and healthcare professionals: Explainability, utility and trust in AI-driven clinical decision-making
Oskar Wysocki, Jessica Katharine Davies, Markel Vigo, Anne Caroline Armstrong, Dónal Landers, Rebecca Lee, and André Freitas. 2023 · 2022
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You Complete Me: Human-AI Teams and Complementary Expertise. In CHI Conference on Human Factors in Computing Systems . ACM, New Orleans LA USA, 1–28
Qiaoning Zhang, Matthew L Lee, and Scott Carter. 2022 · 2022
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Questioning the ability of feature-based explanations to empower non-experts in robo-advised financial decision-making. In 2023 ACM Conference on Fairness, Accountability, and Transparency . ACM, Chicago IL USA, 943–958
Astrid Bertrand, James R. Eagan, and Winston Maxwell. 2023 · 2023
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AI Shall Have No Dominion: on How to Measure Technology Dominance in AI-supported Human decision-making. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems . ACM, Hamburg Germany, 1–20
Federico Cabitza, Andrea Campagner, Riccardo Angius, Chiara Natali, and Carlo Reverberi. 2023 · 2023
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Improving Human-AI Collaboration With Descriptions of AI Behavior
Ángel Alexander Cabrera, Adam Perer, and Jason I. Hong. 2023 · 2023
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How Time Pressure in Different Phases of Decision-Making Influences Human-AI Collaboration
Shiye Cao, Catalina Gomez, and Chien-Ming Huang. 2023 · 2023
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Effects of AI and Logic-Style Explanations on Users’ Decisions under Different Levels of Uncertainty
Federico Maria Cau, Hanna Hauptmann, Lucio Davide Spano, and Nava Tintarev. 2023a · 2023
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Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations
Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, and Gagan Bansal. 2023 · 2023
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Are Two Heads Better Than One in AI-Assisted Decision Making? Comparing the Behavior and Performance of Groups and Individuals in Human-AI Collaborative Recidivism Risk Assessment. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems . ACM, Hamburg Germany, 1–18
Chun-Wei Chiang, Zhuoran Lu, Zhuoyan Li, and Ming Yin. 2023 · 2023
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Explainable AI (XAI): Core Ideas, Techniques, and Solutions
Rudresh Dwivedi, Devam Dave, Het Naik, Smiti Singhal, Rana Omer, Pankesh Patel, Bin Qian, Zhenyu Wen, Tejal Shah, Graham Morgan, and Rajiv Ranjan. 2023 · 2023
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What Else Do I Need to Know? The Effect of Background Information on Users’ Reliance on QA Systems. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, Singapore, 3313–3330
Navita Goyal, Eleftheria Briakou, Amanda Liu, Connor Baumler, Claire Bonial, Jeffrey Micher, Clare Voss, Marine Carpuat, and Hal Daumé III. 2023 · 2023
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How Stated Accuracy of an AI System and Analogies to Explain Accuracy Affect Human Reliance on the System
Gaole He, Stefan Buijsman, and Ujwal Gadiraju. 2023 · 2023
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Toward supporting perceptual complementarity in human-AI collaboration via reflection on unobservables
Kenneth Holstein, Maria De-Arteaga, Lakshmi Tumati, and Yanghuidi Cheng. 2023 · 2023
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Turk Wars: How AI Threatens the Workers Who Fuel It
Krystal Kauffman and Adrienne Williams. 2023 · 2023
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Towards a Science of Human-AI Decision Making: An Overview of Design Space in Empirical Human-Subject Studies. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’23) . Association for Computing Machinery, New York, NY, USA, 1369–1385
Vivian Lai, Chacha Chen, Alison Smith-Renner, Q. Vera Liao, and Chenhao Tan. 2023a · 2023
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Selective Explanations: Leveraging Human Input to Align Explainable AI
Vivian Lai, Yiming Zhang, Chacha Chen, Q. Vera Liao, and Chenhao Tan. 2023b · 2023
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Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Making
Min Hun Lee and Chong Jun Chew. 2023 · 2023
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Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time
Dirk Leffrang, Kevin Bösch, and Oliver Müller. 2023 · 2023
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Strategic Adversarial Attacks in AI-assisted Decision Making to Reduce Human Trust and Reliance. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence . International Joint Conferences on Artificial Intelligence Organization, Macau, SAR China, 3020–3028
Zhuoran Lu, Zhuoyan Li, Chun-Wei Chiang, and Ming Yin. 2023 · 2023
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Physician Detection of Clinical Harm in Machine Translation: Quality Estimation Aids in Reliance and Backtranslation Identifies Critical Errors. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, Singapore, 11633–11647
Nikita Mehandru, Sweta Agrawal, Yimin Xiao, Ge Gao, Elaine Khoong, Marine Carpuat, and Niloufar Salehi. 2023 · 2023
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Evaluating the Impact of Human Explanation Strategies on Human-AI Visual Decision-Making
Katelyn Morrison, Donghoon Shin, Kenneth Holstein, and Adam Perer. 2023a · 2023
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Evaluating the impact of human explanation strategies on human-AI visual decision-making
Katelyn Morrison, Donghoon Shin, Kenneth Holstein, and Adam Perer. 2023b · 2023
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How does Value Similarity affect Human Reliance in AI-Assisted Ethical Decision Making?. In Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society . ACM, Montr\’{e}al QC Canada, 49–57
Saumik Narayanan, Guanghui Yu, Chien-Ju Ho, and Ming Yin. 2023 · 2023
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Understanding Uncertainty: How Lay Decision-makers Perceive and Interpret Uncertainty in Human-AI Decision Making. In Proceedings of the 28th International Conference on Intelligent User Interfaces . ACM, Sydney NSW Australia, 379–396
Snehal Prabhudesai, Leyao Yang, Sumit Asthana, Xun Huan, Q. Vera Liao, and Nikola Banovic. 2023 · 2023
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“I Think You Might Like This”: Exploring Effects of Confidence Signal Patterns on Trust in and Reliance on Conversational Recommender Systems. In 2023 ACM Conference on Fairness, Accountability, and Transparency . ACM, Chicago IL USA, 792–804
Marissa Radensky, Julie Anne Séguin, Jang Soo Lim, Kristen Olson, and Robert Geiger. 2023 · 2023
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Exploring the effects of human-centered AI explanations on trust and reliance
Nicolas Scharowski, Sebastian A. C. Perrig, Melanie Svab, Klaus Opwis, and Florian Brühlmann. 2023 · 2023
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Max Schemmer, Andrea Bartos, Philipp Spitzer, Patrick Hemmer, Niklas Kühl, Jonas Liebschner, and Gerhard Satzger. 2023a · 2023
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Integrating AI in Human-Human Collaborative Ideation. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems . 1–5
Joon Gi Shin, Janin Koch, Andrés Lucero, Peter Dalsgaard, and Wendy E Mackay. 2023 · 2023
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Explanations Can Reduce Overreliance on AI Systems During Decision-Making
Helena Vasconcelos, Matthew Jörke, Madeleine Grunde-McLaughlin, Tobias Gerstenberg, Michael S. Bernstein, and Ranjay Krishna. 2023 · 2023
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The effects of explanations on automation bias
Mor Vered, Tali Livni, Piers Douglas Lionel Howe, Tim Miller, and Liz Sonenberg. 2023 · 2023
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Evaluating the Impact of Uncertainty Visualization on Model Reliance
Jieqiong Zhao, Yixuan Wang, Michelle V. Mancenido, Erin K. Chiou, and Ross Maciejewski. 2023 · 2023
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A Decision Theoretic Framework for Measuring AI Reliance. In The 2024 ACM Conference on Fairness, Accountability, and Transparency . 221–236
Ziyang Guo, Yifan Wu, Jason D Hartline, and Jessica Hullman. 2024 · 2024
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A sociotechnical system perspective on AI
Olya Kudina and Ibo van de Poel. 2024 · 2024
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Influence of Device Performance and Agent Advice on User Trust and Behaviour in a Care-taking Scenario
Ingrid Zukerman, Andisheh Partovi, and Jakob Hohwy. 2023 · 2024
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