Games of Representation: Developing Card-Based Activities to Teach About Representation and Bias in AI Datasets

Katherine S. Moore; Helen Zhang; Irene Lee

AAAI 2026technical0 citations

Games of Representation: Developing Card-Based Activities to Teach About Representation and Bias in AI Datasets

Katherine S. Moore, Helen Zhang, Irene Lee

Abstract

Adolescents struggle to understand bias and representation in AI, particularly the concept of how datasets used in machine learning can be representative of populations or not. Within early experiments in teaching about investigating bias in AI systems using the Developing AI Literacy (DAILy) curriculum, we observed participating youth struggling to understand what it meant to be represented in the output of AI tools. For example, when using Google Image Search with prompts such as “physicist” and “outdoor recreation,” participating youth did not understand the question, “Are you represented in this outcome?” We saw an opportunity to address this challenge using the Kapor Foundation

BibTeX

@inproceedings{aaai2026_gamesofrepresent,
  title = {Games of Representation: Developing Card-Based Activities to Teach About Representation and Bias in AI Datasets},
  author = {Katherine S. Moore and Helen Zhang and Irene Lee},
  booktitle = {AAAI 2026},
  year = {2026}
}