Coding with Purpose: Learning AI in Rural California

TL;DR

This paper presents an autoethnographic case study of a Latinx high school student's informal AI learning in an agricultural community, emphasizing the importance of inclusive AI education for social justice.

Contribution

It highlights how informal learning pathways and community context influence AI education and advocates for redesigning AI curricula to be more inclusive of marginalized groups.

Findings

AI is learned outside formal classrooms in community settings.

Personal background influences social-justice oriented AI applications.

Inclusive AI education can empower vulnerable communities.

Abstract

We use an autoethnographic case study of a Latinx high school student from an agricultural community in California to highlight how AI is learned outside classrooms and how her personal background influenced her social-justice oriented applications of AI technologies. Applying the concept of learning pathways from the learning sciences, we argue that redesigning AI education to be more inclusive with respect to socioeconomic status, ethnoracial identity, and gender is important in the development of computational projects that address social-injustice. We also learn about the role of institutions, power structures, and community as they relate to her journey of learning and applying AI. The future of AI, its potential to address issues of social injustice and limiting the negative consequences of its use, will depend on the participation and voice of students from the most vulnerable communities.