Knowledge Workers' Perspectives on AI Training for Responsible AI Use

TL;DR

This study investigates how knowledge workers are trained to use AI safely in the workplace, addressing gaps where workers risk underutilization or biased outcomes due to insufficient training. Using a multinational workshop (n=39) and 17 follow-up interviews, the authors identify nine training topics organized into foundations, tool-facing literacy, DEI/bias awareness, and worker rights/data privacy, framed across organizational and regional contexts. They propose a three-pronged approach: map training to context, imagine HCI prototyping tools as practical training aids, and scrutinize how training may embed harmful values in technology. The work offers actionable guidance for organizations and AI designers to implement responsible AI education that empowers workers while safeguarding rights and equity, with implications for policy, practice, and future interface design. A key contribution is the concept of a prototyping-repository of AI training artefacts to keep pace with fast-changing AI tools, making practical, accessible training feasible across diverse settings.

Abstract

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.