Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making

22 May 2020

Papers citing "Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making"

10 / 10 papers shown

Title
A Mathematical Model of the Hidden Feedback Loop Effect in Machine Learning Systems Andrey Veprikov Alexander Afanasiev Anton Khritankov 40 2 0 04 May 2024
Trust, distrust, and appropriate reliance in (X)AI: a survey of empirical evaluation of user trust Roel W. Visser Tobias M. Peters Ingrid Scharlau Barbara Hammer 21 5 0 04 Dec 2023
Painting the black box white: experimental findings from applying XAI to an ECG reading setting F. Cabitza M. Cameli Andrea Campagner Chiara Natali Luca Ronzio 32 9 0 27 Oct 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
Teaching Humans When To Defer to a Classifier via Exemplars Hussein Mozannar Arvindmani Satyanarayan David Sontag 36 43 0 22 Nov 2021
Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development Aspen K. Hopkins Serena Booth 29 45 0 06 Oct 2021
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs Harini Suresh Kathleen M. Lewis John Guttag Arvind Satyanarayan FAtt 40 25 0 17 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
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,684 0 28 Feb 2017