Knowledge Workers' Perspectives on AI Training for Responsible AI Use

要旨

AI expansion has accelerated workplace adoption of new technologies. Yet, it is unclear whether and how knowledge workers are supported and trained to safely use AI. Inadequate training may lead to unrealized benefits if workers abandon tools, or perpetuate biases if workers misinterpret AI-based outcomes. In a workshop with 39 workers from 26 countries specializing in human resources, labor law, standards creation, and worker training, we explored questions and ideas they had about safely adopting AI. We held 17 follow-up interviews to further investigate what skills and training knowledge workers need to achieve safe and effective AI in practice. We synthesize nine training topics participants surfaced for knowledge workers related to challenges around understanding what AI is, misinterpreting outcomes, exacerbating biases, and worker rights. We reflect how these training topics might be addressed under different contexts, imagine HCI research prototypes as potential training tools, and consider ways to ensure training does not perpetuate harmful values.

著者
Angie Zhang
The University of Texas at Austin, Austin, Texas, United States
Min Kyung Lee
University of Texas at Austin, Austin, Texas, United States
DOI

10.1145/3706598.3714100

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714100

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Workplace Interactions and Wellbeing

G416+G417
6 件の発表
2025-04-28 23:10:00
2025-04-29 00:40:00
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