Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making

7 January 2020

Papers citing "Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making"

30 / 80 papers shown

Title
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models Esma Balkir S. Kiritchenko I. Nejadgholi Kathleen C. Fraser 21 36 0 08 Jun 2022
Causal Explanations for Sequential Decision Making Under Uncertainty Samer B. Nashed Saaduddin Mahmud C. V. Goldman S. Zilberstein CML 43 4 0 30 May 2022
A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making Max Schemmer Patrick Hemmer Maximilian Nitsche Niklas Kühl Michael Vossing 24 55 0 10 May 2022
Interactive Model Cards: A Human-Centered Approach to Model Documentation Anamaria Crisan Margaret Drouhard Jesse Vig Nazneen Rajani HAI 37 87 0 05 May 2022
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation Maria De-Arteaga Alexandra Chouldechova Artur Dubrawski 30 4 0 29 Apr 2022
Designing for Responsible Trust in AI Systems: A Communication Perspective Q. V. Liao S. Sundar 27 100 0 29 Apr 2022
Exploring How Anomalous Model Input and Output Alerts Affect Decision-Making in Healthcare Marissa Radensky Dustin Burson Rajya Bhaiya Daniel S. Weld 24 0 0 27 Apr 2022
Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation Vivian Lai Samuel Carton Rajat Bhatnagar Vera Liao Yunfeng Zhang Chenhao Tan 29 130 0 25 Apr 2022
Factors that influence the adoption of human-AI collaboration in clinical decision-making Patrick Hemmer Max Schemmer Lara Riefle Nico Rosellen Michael Vossing Niklas Kühl 30 11 0 19 Apr 2022
Calibrating Trust of Multi-Hop Question Answering Systems with Decompositional Probes Kaige Xie Sarah Wiegreffe Mark O. Riedl ReLM 24 12 0 16 Apr 2022
Should I Follow AI-based Advice? Measuring Appropriate Reliance in Human-AI Decision-Making Max Schemmer Patrick Hemmer Niklas Kühl Carina Benz G. Satzger 17 56 0 14 Apr 2022
Towards Explainable Evaluation Metrics for Natural Language Generation Christoph Leiter Piyawat Lertvittayakumjorn M. Fomicheva Wei-Ye Zhao Yang Gao Steffen Eger AAML ELM 27 20 0 21 Mar 2022
Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 19 1 0 30 Jan 2022
HIVE: Evaluating the Human Interpretability of Visual Explanations Sunnie S. Y. Kim Nicole Meister V. V. Ramaswamy Ruth C. Fong Olga Russakovsky 66 114 0 06 Dec 2021
Teaching Humans When To Defer to a Classifier via Exemplars Hussein Mozannar Arvindmani Satyanarayan David Sontag 36 43 0 22 Nov 2021
Interpreting Deep Learning Models in Natural Language Processing: A Review Xiaofei Sun Diyi Yang Xiaoya Li Tianwei Zhang Yuxian Meng Han Qiu Guoyin Wang Eduard H. Hovy Jiwei Li 17 44 0 20 Oct 2021
Exploring The Role of Local and Global Explanations in Recommender Systems Marissa Radensky Doug Downey Kyle Lo Z. Popović Daniel S. Weld University of Washington LRM 13 20 0 27 Sep 2021
Explaining Autonomous Decisions in Swarms of Human-on-the-Loop Small Unmanned Aerial Systems Ankit Agrawal J. Cleland-Huang 16 14 0 05 Sep 2021
The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies Riccardo Fogliato Alexandra Chouldechova Zachary Chase Lipton 24 31 0 03 Sep 2021
Explanation-Based Human Debugging of NLP Models: A Survey Piyawat Lertvittayakumjorn Francesca Toni LRM 42 79 0 30 Apr 2021
Increasing the Speed and Accuracy of Data LabelingThrough an AI Assisted Interface Michael Desmond Zahra Ashktorab Michelle Brachman Kristina Brimijoin Evelyn Duesterwald ... Catherine Finegan-Dollak Michael J. Muller N. Joshi Qian Pan Aabhas Sharma 26 50 0 09 Apr 2021
To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making Zana Buçinca M. Malaya Krzysztof Z. Gajos 28 299 0 19 Feb 2021
Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs Harini Suresh Steven R. Gomez K. Nam Arvind Satyanarayan 34 126 0 24 Jan 2021
Debiased-CAM to mitigate image perturbations with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 24 18 0 10 Dec 2020
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making Charvi Rastogi Yunfeng Zhang Dennis L. Wei Kush R. Varshney Amit Dhurandhar Richard J. Tomsett HAI 32 108 0 15 Oct 2020
The Role of Domain Expertise in User Trust and the Impact of First Impressions with Intelligent Systems Mahsan Nourani J. King Eric D. Ragan 22 98 0 20 Aug 2020
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance Gagan Bansal Tongshuang Wu Joyce Zhou Raymond Fok Besmira Nushi Ece Kamar Marco Tulio Ribeiro Daniel S. Weld 39 578 0 26 Jun 2020
Does Explainable Artificial Intelligence Improve Human Decision-Making? Y. Alufaisan L. Marusich J. Bakdash Yan Zhou Murat Kantarcioglu XAI 22 93 0 19 Jun 2020
Trust in AutoML: Exploring Information Needs for Establishing Trust in Automated Machine Learning Systems Jaimie Drozdal Justin D. Weisz Dakuo Wang Gaurav Dass Bingsheng Yao Changruo Zhao Michael J. Muller Lin Ju Hui Su 44 125 0 17 Jan 2020
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,684 0 28 Feb 2017