Humans, AI, and Context: Understanding End-Users’ Trust in a Real-World Computer Vision Application

Author:

Kim Sunnie S. Y.1ORCID,Watkins Elizabeth Anne2ORCID,Russakovsky Olga1ORCID,Fong Ruth1ORCID,Monroy-Hernández Andrés1ORCID

Affiliation:

1. Department of Computer Science, Princeton University, USA

2. Intelligent Systems Research, Intel Labs, USA

Funder

Princeton SEAS Howard B. Wentz, Jr. Junior Faculty Award

Princeton Center for Information Technology Policy

Open Philanthropy Project

NSF (National Science Foundation)

Princeton SEAS Project X Fund

Publisher

ACM

Reference61 articles.

1. Amina Adadi and Mohammed Berrada . 2022 . Hartmann, Philipp and Hobert, Sebastian and Schumann , Matthias. Americas Conference on Information Systems (AMCIS) 5 (2022 ). https://doi.org/amcis2022/sig_ed/sig_ed/5 Amina Adadi and Mohammed Berrada. 2022. Hartmann, Philipp and Hobert, Sebastian and Schumann, Matthias. Americas Conference on Information Systems (AMCIS) 5 (2022). https://doi.org/amcis2022/sig_ed/sig_ed/5

2. Being Trustworthy is Not Enough: How Untrustworthy Artificial Intelligence (AI) Can Deceive the End-Users and Gain Their Trust

3. Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance

4. Michaela Benk Suzanne Tolmeijer Florian von Wangenheim and Andrea Ferrario. 2022. The Value of Measuring Trust in AI - A Socio-Technical System Perspective. https://doi.org/10.48550/ARXIV.2204.13480 10.48550/ARXIV.2204.13480

5. Michaela Benk Suzanne Tolmeijer Florian von Wangenheim and Andrea Ferrario. 2022. The Value of Measuring Trust in AI - A Socio-Technical System Perspective. https://doi.org/10.48550/ARXIV.2204.13480

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