What concerns SHOULD we be discussing about using AI in Education?

What Is The Issue?

Authors:

Philip Bell | JUNE 2026

Things To Consider

There are a range of social and ethical concerns about AI to deliberate on:

Overarching Concerns about the AI Political Economy and Social Power

1. Significant environmental harms include massive water use, supercharging carbon emissions, ecological disruptions, increased air pollution, and negative impacts of quickly expanding data centers

2. Profit seeking and market capture motives of “AI in education” companies can reduce education to a for-profit commercial product

3. Homogenization of culture, thought, and knowledge through linguistic privileging, cultural bias; Global North data bias; narrowing and flattening of curriculum, assessment, and educational goals

4. “Move Fast & Break Things” approach can jeopardize education’s social contract with the public, violate the protective purpose of schooling, disrupt improvement efforts & impair social relationships

Harms that Occur During AI Model Development and Training

5. Intellectual property has been stolen for the training of AI models

6. Unfair labor practices have been documented in “digital sweatshops” as well as significant psychological harm to AI content moderators

7. “Baked-in” biased responses in AI models can produce regressive and marginalizing responses (e.g., that are racist, sexist, xenophobic)

During Use by Students, Teachers, and Educational Leaders

8. Falsehoods are promoted as true (i.e., hallucinations) and misinformation and disinformation are shared through AI systems

9. Adverse health impacts on young people (e.g., impacts on mental health and youth suicide) must be considered and countered

10. Disruption of social learning processes, cognition, and social development (e.g., offloading learning tasks onto AI systems, diminished metacognitive engagement, and diminished creativity)

11. Data privacy & student safety can be compromised; put up a defense

During Use by Teachers and Educational Leaders

12. Deprofessionalization of teaching and ed leadership by offloading tasks to AI systems and diminishing the need for human expertise

13. Encourages automation which is not a suitable replacement for human labor and jobs; education is a fundamentally human endeavor

Attending to Equity

• Groups are exploring if AI can support educational equity. However, the risks of using generative AI in education currently outweigh its benefits. We all need to make room for ethical deliberation and informed decision-making about AI in education since it is a “double-edged sword.”
• The negative impacts of AI use in society disproportionately impact
  non-dominant communities and efforts are needed to promote equity.

Recommended Actions You Can Take

Teach Based on a Social & Ethical Analysis

• Teams of educators should engage with the 13 social and ethical concerns, reflect on them, and let it guide their teaching.
• Learn how to teach against AI and how to shape a more just sociotechnical future.
• AI initiatives and products are outpacing discussion of responsible uses. Use expertise on how people learn and a “go slow and build” approach to reduce harm.

Design AI Uses with Students & Teachers

• Engage students with social and ethical concerns to collaboratively make sense of responsible engagement with AI.
• Teach: “Science and technology may raise ethical issues for which science, by itself, does not provide answers and solutions.”
• Educators should teach about the environmental and social impacts of AI systems using ethical decision-making.

ALSO SEE STEM TEACHING TOOLS

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Work is licensed under a Creative Commons Attribution-ShareAlike 4.0 Unported License. Others may adapt with attribution. Funded by the National Science Foundation (NSF). Opinions expressed are not those of any funding agency.