The Gaze of Others

This case study follows Reema, a hijab-wearing Afghan-American university student, as she navigates the ethical and technological challenges of AI-driven gaze tracking during a remote biology exam. Using EyeThentic, a proctoring system that scans students’ faces and monitors their eye movements, Reema is asked to remove her hijab for facial verification—placing her in a conflict between religious observance and academic policy. Though she complies under pressure, the AI’s algorithm—trained primarily on white American faces—flags her for suspected cheating based on misread gaze patterns and facial cues. Without her knowledge, her data is stored, shared with federal databases, and later contributes to her being flagged at U.S. customs. The case highlights how algorithmic bias, lack of cultural sensitivity, and opaque data-sharing practices can harm marginalized students. It also raises pressing questions about privacy, religious freedom, and the ethics of surveillance technology in education. Reema’s experience reflects broader concerns about AI governance, digital dignity, and the urgent need for inclusive design in academic and biometric systems.

Publication Details

Journal
VTechWorks (Virginia Tech)
Published
2025-06-01
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

The Gaze of Others

VTechWorks (Virginia Tech)
Ethics and Social Impacts of AI
article

The Gaze of Others

article en

Abstract

This case study follows Reema, a hijab-wearing Afghan-American university student, as she navigates the ethical and technological challenges of AI-driven gaze tracking during a remote biology exam. Using EyeThentic, a proctoring system that scans students’ faces and monitors their eye movements, Reema is asked to remove her hijab for facial verification—placing her in a conflict between religious observance and academic policy. Though she complies under pressure, the AI’s algorithm—trained primarily on white American faces—flags her for suspected cheating based on misread gaze patterns and facial cues. Without her knowledge, her data is stored, shared with federal databases, and later contributes to her being flagged at U.S. customs. The case highlights how algorithmic bias, lack of cultural sensitivity, and opaque data-sharing practices can harm marginalized students. It also raises pressing questions about privacy, religious freedom, and the ethics of surveillance technology in education. Reema’s experience reflects broader concerns about AI governance, digital dignity, and the urgent need for inclusive design in academic and biometric systems.

VTechWorks (Virginia Tech)
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Ethics and Social Impacts of AI
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