A Human-Centered Approach to Ethical AI Education in Underresourced Secondary Schools

TL;DR

This paper presents a human-centered, ethical AI course for under-resourced high schools, demonstrating high student engagement and emphasizing ethical reasoning alongside AI literacy.

Contribution

It introduces a novel, college credit--bearing AI ethics course integrating asynchronous, mentorship, and discussion-based learning for underserved high school students.

Findings

97.8% course completion rate among students

Students engaged in applying ethical reasoning to AI concepts

Educators reported high engagement and perceived rigor

Abstract

National and international policy efforts increasingly promote AI literacy in K--12 education, yet access to AI tools alone is insufficient to ensure equitable and responsible participation, particularly in under-resourced contexts. Without designs that integrate ethical reasoning, human support, and opportunities for judgment, AI initiatives risk reinforcing inequities and preparing students to use powerful technologies without critically evaluating their societal consequences. To address this gap, we developed a human-centered, college credit--bearing course on Responsible and Ethical AI for students attending Title I and Title I--eligible high schools, implemented in partnership with the National Education Opportunity Network (NEON). The bichronous course integrates foundational AI concepts with ethical and socio-technical reasoning through asynchronous instruction, near-peer mentorship, and synchronous, discussion-based instruction. In its inaugural year, nearly 180 students from 12 U.S. schools completed the course, with a 97.8% completion rate. Using end-of-course survey data from students, co-teachers, and teaching fellows, this study examines academic agency, confidence with college-level expectations, critical engagement with responsible AI, and perceived post-secondary trajectory expansion. Results indicate that students were challenged to apply learning and reason about ethical tradeoffs, while educators reported high engagement, rigor, and meaningfulness relative to typical high school coursework. Overall, findings highlight the importance of human connections in advancing equitable Artificial Intelligence in Education and support ethical judgment as a core learning outcome alongside AI literacy.