Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
10-2024
Abstract
A growing research explores the usage of AI explanations on user’s decision phases for human-AI collaborative decision-making. However, previous studies found the issues of overreliance on ‘wrong’ AI outputs. In this paper, we propose interactive example-based explanations to improve health professionals’ onboarding with AI for their better reliance on AI during AI-assisted decision-making. We implemented an AI-based decision support system that utilizes a neural network to assess the quality of post-stroke survivors’ exercises and interactive example-based explanations that systematically surface the nearest neighborhoods of a test/task sample from the training set of the AI model to assist users’ onboarding with the AI model. To investigate the effect of interactive example-based explanations, we conducted a study with domain experts, health professionals to evaluate their performance and reliance on AI. Our interactive example-based explanations during onboarding assisted health professionals in having a better reliance on AI and making a higher ratio of making ‘right’ decisions and a lower ratio of ‘wrong’ decisions than providing only feature-based explanations during the decision-support phase. Our study discusses new challenges of assisting user’s onboarding with AI for human-AI collaborative decision-making.
Keywords
Human-AI collaborative decision-making, AI assisted decision-making, Decision support system, Example-based explanations
Discipline
Artificial Intelligence and Robotics
Research Areas
Intelligent Systems and Optimization
Publication
Proceedings of the 27th European Conference on Artificial Intelligence (ECAI 2024) Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024) : Santiago de Compostela, Spain, October 19-24
Volume
392
First Page
4524
Last Page
4531
Identifier
10.3233/FAIA241044
Publisher
IOS Press
City or Country
ECAI 2024
Citation
LEE, Min Hun; NG, Renee Bao Xuan; CHOO, Silvana Xinyi; and THILARAJAH, Shamala.
Interactive example-based explanations to improve health professionals’ onboarding with AI for human-AI collaborative decision making. (2024). Proceedings of the 27th European Conference on Artificial Intelligence (ECAI 2024) Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024) : Santiago de Compostela, Spain, October 19-24. 392, 4524-4531.
Available at: https://ink.library.smu.edu.sg/sis_research/9689
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://ebooks.iospress.nl/doi/10.3233/FAIA241044