Contextualizing User Perceptions about Biases for Human-Centered Explainable Artificial Intelligence-Reference-Cited by-同舟云学术

Contextualizing User Perceptions about Biases for Human-Centered Explainable Artificial Intelligence

Published:2023-04-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
language:
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Author:

Yuan Chien Wen (Tina)¹^ORCID,Bi Nanyi²^ORCID,Lin Ya-Fang³^ORCID,Tseng Yuen-Hsien⁴^ORCID

Affiliation:

1. D-School, National Taiwan University, Taiwan

2. Department of Information Management, National Taiwan University, Taiwan

3. Collaboration & Innovation Lab, College of Information Science of Technology, Penn State University, United States

4. Graduate Institute of Library and Information Studies, National Taiwan Normal University, Taiwan

Funder

National Science and Technology Council of Taiwan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3544548.3580945

Reference48 articles.

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4. Chelsea Barabas , Madars Virza , Karthik Dinakar , Joichi Ito , and Jonathan Zittrain . 2018 . Interventions over predictions: Reframing the ethical debate for actuarial risk assessment . In Conference on Fairness, Accountability and Transparency. PMLR, 62–76 . Chelsea Barabas, Madars Virza, Karthik Dinakar, Joichi Ito, and Jonathan Zittrain. 2018. Interventions over predictions: Reframing the ethical debate for actuarial risk assessment. In Conference on Fairness, Accountability and Transparency. PMLR, 62–76.

5. What Do People Really Want When They Say They Want "Explainable AI?" We Asked 60 Stakeholders.

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