Works for Me: Personalizing Skilled Trade Worker Training via Smart Hand Tools

Abstract

This paper explores an approach for applying Artificial Intelligence (AI) to co-design smart hand tools to personalize learning for future skilled trade workers in workforce training programs. The purpose of this research is to better understand the perspectives of workers in the skilled trades and to respond with co-designed socio-technical interventions that empower workers. The research benefits from a collaboration between The University of Texas at Austin, the City of Austin, and Austin Community College (ACC) and incorporates insights from welding instructors and students, as well as skilled trade workers and supervisors. Social science findings derived from semi-structured interviews inform tool design implemented by an interdisciplinary research team. The participatory design approach has resulted in two prototypes: a welding simulator that uses Augmented Reality (AR) and an AI-enabled (smart) rotary tool. This paper has implications for workforce development to address skilled worker shortages. Additionally, it contributes to ongoing research into AI and skilled trade work which is understudied compared to AI and knowledge work.