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.
@article{arxiv.2603.29238,
title = {An Experiential Approach to AI Literacy},
author = {Aakanksha Khandwaha and Edith Law},
journal= {arXiv preprint arXiv:2603.29238},
year = {2026}
}
Comments
Paper accepted at CHI 2026 Workshop on Data Literacy. For more details, see https://data-literacy-workshop.github.io/CHI26/