Building to Understand: Examining Teens' Technical and Socio-Ethical Pieces of Understandings in the Construction of Small Generative Language Models
This work addresses the need to support teens in developing AI literacy through hands-on activities, though it is incremental in building on prior exploratory studies.
The study investigated how constructing small generative language models helps teenagers develop technical and socio-ethical understandings of AI systems, finding that participatory workshops enabled teens to exhibit specific pieces of understanding in these areas.
The rising adoption of generative AI/ML technologies increases the need to support teens in developing AI/ML literacies. Child-computer interaction research argues that construction activities can support young people in understanding these systems and their implications. Recent exploratory studies demonstrate the feasibility of engaging teens in the construction of very small generative language models (LMs). However, it is unclear how constructing such models may foster the development of teens' understanding of these systems from technical and socio-ethical perspectives. We conducted a week-long participatory design workshop in which sixteen teenagers constructed very small LMs to generate recipes, screenplays, and songs. Using thematic analysis, we identified technical and socio-ethical pieces of understandings that teens exhibited while designing generative LMs. This paper contributes (a) evidence of the kinds of pieces of understandings that teens have when constructing LMs and (b) a theory-backed framing to study novices' understandings of AI/ML systems.