HCMar 31

An Experiential Approach to AI Literacy

arXiv:2603.2923829.0h-index: 1
AI Analysis

This addresses the challenge of applying AI in real-world workflows for workers across various sectors, though it appears incremental in educational methods.

The paper tackles the problem of AI literacy gaps among workers by proposing an experiential approach that integrates daily experiences through storytelling to develop practical knowledge and concrete AI use cases.

Despite AI tools becoming more prevalent and applicable to a variety of workplaces, workers consistently report uncertainty about where AI applies, what problems it can help solve, and how it fits into real workflows. In other words, there is a gap between `knowing' and `doing' when it comes to AI literacy. We propose an experiential form of AI literacy which integrates participant's daily experiences into the learning experience by brainstorming grounded AI use cases through storytelling. We introduce a novel pedagogical approach that helps individuals move away from abstract notions of AI towards practical knowledge of how AI would (or would not) work in different workflows, contexts, and situations. Through this approach, we anticipate two major outcomes: (1) enhanced AI literacy for stakeholders within a variety of work sectors and (2) concrete AI use cases developed through participatory design that are grounded in AI literacy and participant's expertise.

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