Students learn AI ethics through inquiry or design projects examining societal impact and bias¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends that 'Students should likewise engage in ethical reflection through AI inquiry or design projects, critically examining societal impact, justice, privacy, and bias, supported by evidence-based argumentation'. Such practices, it argues, enable learners to interrogate existing data-driven systems and envision alternatives, extending AI literacy beyond technical skills toward critical and political forms of agency.

Design Implications¶

Context¶

Requirements¶

• Support for evidence-based argumentation within the projects

Constraints¶

• The article links this to transformative AI education addressing a widening divide between those who can critically engage with AI and those who cannot

Target Learners¶

• K-12 students

Target Learning Goals¶

• critical examination of AI systems' societal impact
• envisioning alternatives to existing data-driven systems

Affordances¶

• Critical Ecological Activity Model Ai Ethics

Related Strategies¶

• Focus on Issues of Justice

Examples¶

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Key Sources¶

• Juliana Elisa Raffaghelli, Henriikka Vartiainen, Matt Bower, Martina Ronci, Chris Shelton, Kathryn MacCallum, Jihyun Lee, Mary Webb, Yousra Cthouki, David Smith. (2026). Situated AI Ethics: A Cultural-Historical and Ecological Framework for Education. Computers and Education Open. https://doi.org/10.1016/j.caeo.2026.100368