Title:
Designing a critical machine learning educational program with and for children
Designing a critical machine learning educational program with and for children
Author(s)
Arastoopour Irgens, Golnaz
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Abstract
The world is becoming increasingly reliant on artificial intelligence (AI) technologies that collect, store, and analyze our data. Such technologies improve our quality of life, but they also (re)perpetuate inequities and harm marginalized populations. As digital technologies become more ubiquitous, it will become critical for all young people to have a deep understanding of AI that empowers them to enact change in their local communities and globally. In this talk, I discuss how researchers and children collaborated to develop a critical machine learning after-school education program, in which children explored the social and ethical consequences of large-scale algorithm deployment and applied machine learning content knowledge. Findings show that children were able to 1) explain how biased training datasets could be harmful and 2) build robots for social good that used their own designed classification algorithms. Reflecting on these findings, I argue for the benefits of participatory design methods in designing critical machine learning educational environments, as well as the unresolved tensions that emerge.
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Date Issued
2022-02-10
Extent
49:10 minutes
Resource Type
Moving Image
Resource Subtype
Lecture