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Exploring the Effects of Machine Learning Literacy Interventions on Laypeople’s Reliance on Machine Learning Models

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Chun-Wei Chiang,

Ming YinAuthors Info & Claims

IUI '22: Proceedings of the 27th International Conference on Intelligent User Interfaces

Pages 148 - 161

https://doi.org/10.1145/3490099.3511121

Published: 22 March 2022 Publication History

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Abstract

Today, machine learning (ML) technologies have penetrated almost every aspect of people’s lives, yet public understandings of these technologies are often limited. This highlights the urgent need of designing effective methods to increase people’s machine learning literacy, as the lack of relevant knowledge may result in people’s inappropriate usage of machine learning technologies. In this paper, we focus on an ML-assisted decision-making setting and conduct a human-subject randomized experiment to explore how providing different types of user tutorials as the machine learning literacy interventions can influence laypeople’s reliance on ML models, on both in-distribution and out-of-distribution examples. We vary the existence, interactivity and scope of the user tutorial across different treatments in our experiment. Our results show that user tutorials, when presented in appropriate forms, can help some people rely on ML models more appropriately. For example, for those individuals who have relatively high ability in solving the decision-making task themselves, receiving a user tutorial that is interactive and addresses the specific ML model to be used allows them to reduce their over-reliance on the ML model when they could outperform the model. In contrast, low-performing individuals’ reliance on the ML model is not affected by the presence or the type of user tutorial. Finally, we also find that people perceive the interactive tutorial to be more understandable and slightly more useful. We conclude by discussing the design implications of our study.

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Cited By

Lu ZWang DYin M(2024)Does More Advice Help? The Effects of Second Opinions in AI-Assisted Decision MakingProceedings of the ACM on Human-Computer Interaction10.1145/36537088:CSCW1(1-31)Online publication date: 26-Apr-2024
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cover image ACM Conferences

IUI '22: Proceedings of the 27th International Conference on Intelligent User Interfaces

March 2022

888 pages

ISBN:9781450391443

DOI:10.1145/3490099

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Published: 22 March 2022

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