AI and Equity
Centering Justice in Institutional Responses
One of the most significant gaps in institutional AI discussions is the absence of critical perspectives on who benefits from AI adoption and who bears its costs. As teaching and learning leaders, we have a responsibility to ensure that our AI strategies advance rather than undermine institutional commitments to equity, inclusion, and justice.
Who Holds Power, And How Do We Redistribute It?
AI tools are not neutral technologies. They are developed primarily by corporations in wealthy countries, trained on datasets that reflect existing biases, and marketed to institutions with the resources to purchase licenses.
Consider the following equity dimensions as you begin and work on institutional AI planning – this planning might be in the guidelines, governance, faculty development activities or beyond.
Systemic Access
Justice Concerns
Practical Strategies for Equity-Centered AI Leadership
Focus on community listening. Conduct focus groups, surveys or discussions with your institutional communities to hear about – and listen sincerely to – their experiences with and concerns about AI. Include questions about access, relevance, and unintended barriers.
Center student choice. Whenever possible, make AI use optional rather than required, and provide alternative pathways for students who cannot or choose not to use AI tools. This includes offering non-AI options for assignments and ensuring that AI proficiency isn’t a hidden requirement for academic success.
Build accountability mechanisms. Create processes for community members to report problems with AI tools or policies and consider having these processes anonymous.
Data consent and governance: Advocate for transparency on how student/staff/faculty data are collected, shared and protected by AI vendors and campus systems (e.g. learning management system analytics, plagiarism detection systems, lock-down browsers). Advocate for opt-out processes and informed consent for the use of these tools when data is being collected, shared or stored.
Partner. Partner with campus equity offices, student unions, and community organizations that center justice work. Learn from their expertise and integrate these perspectives as core to the work.
Questions for Reflection and Action
As you develop AI strategies at your institution, regularly return to these questions:
- Who is benefiting from our AI initiatives, and who may be (inadvertently) excluded?
- How do our AI policies align with our institutional commitments to equity and inclusion?
- What voices are missing from our AI governance structures?
- Are we reproducing existing inequalities through AI adoption, or actively working to disrupt them?
- How can we center participatory governance in our AI work as foundational to the work?
- How can non-AI alternatives be built into course design and assessment?
- What would AI in education look like if it were designed to advance justice rather than efficiency?
- How do we build in accountability when AI-based decisions go wrong (e.g. feedback, plagiarism flags)? What transparent, community-led processes exist for review and remediation?
- What barriers exist to equitable AI use, and how might these be mitigated?
- How will we know we’ve succeeded? What indicators will tell us that our AI practices are advancing and equity and justice, no just scale or speed?
