Understanding the effect of counterfactual explanations on trust and reliance on AI for human-AI collaborative clinical decision making
Artificial intelligence (AI) is increasingly being considered to assist human decision-making in high-stake domains (e.g. health). However, researchers have discussed an issue that humans can over-rely on wrong suggestions of the AI model instead of achieving human AI complementary performance. In t...
Saved in:
Main Authors: | LEE, Min Hun, CHEW, Chong Jun |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2023
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8274 https://ink.library.smu.edu.sg/context/sis_research/article/9277/viewcontent/3610218_pvoa_cc_by.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Towards efficient annotations for a human-AI collaborative, clinical decision support system: A case study on physical stroke rehabilitation assessment
by: LEE, Min Hun, et al.
Published: (2022) -
USER-CENTRIC EXPLANATION OF MACHINE LEARNING MODEL FOR HUMAN-AI COLLABORATION
by: WANG DANDING
Published: (2021) -
A human-AI collaborative approach for clinical decision making on rehabilitation assessment
by: LEE, Min Hun, et al.
Published: (2021) -
Interactive example-based explanations to improve health professionals’ onboarding with AI for human-AI collaborative decision making
by: LEE, Min Hun, et al.
Published: (2024) -
Co-design and evaluation of an intelligent decision support system for stroke rehabilitation assessment
by: LEE, Min Hun, et al.
Published: (2020)