Taking play and tinkering seriously in AI education: cases from Drag vs AI teen workshops

ABSTRACT

Learning around artificial intelligence (AI)-powered technologies that attends to power is an urgent and widely felt priority among the learning sciences and CS ed broadly. Popular approaches to AI education focus on technical skills, with far less theoretical and practical work around critical and justice-centered AI learning. Adding to this literature, we discuss tool design and observed interactions in Drag vs AI workshops, where participants use hands-on makeup art as a medium for fooling, subverting, and refusing facial recognition. Our broader analysis asks how participants make sense of the technical and political aspects of AI, as they interact with AI through the Drag vs AI workshops’ modes of aesthetic transformation, tinkering, and resistance. In this paper, we focus on participants’ embodied algorithmic tinkering with AI and affordances for justice-centered computing education. Our analysis highlights how tinkering and play modes of interaction with AI materials can promote critical and agentive learning.

KEYWORDS:

• Facial recognition
• artificial intelligence
• AI
• tinkering
• embodiment

Acknowledgments

We are so grateful to our partners in this project, the fabulous Cardi Acarrest, David Kling, Chris Castañeda, the volunteer facilitators, and partnering organizations. We also thank the creators of Drag vs. AI, Maty Cropley and the Algorithmic Justice League, for their support of this project.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1 We received explicit permission to conduct and study Drag vs AI from its designers prior to pursuing this research project.

Additional information

Funding

This work was supported by the National Science Foundation under NSF CAREER Award #1562040.