Ethical Considerations in Artificial Intelligence
This page of the University of Virginia Library Guide on Generative AI provides links and information about ethical considerations in artificial intelligence, including fairness and bias; privacy and security; accountability, transparency, and oversight; and societal impact.
I find this Library Guide to be an excellent way to access readings related to a range of crucial considerations for AI use. The way the content is organized to include an overview, followed by ways to learn more and dig deeper, is especially valuable for scaffolding learning.
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As artificial intelligence becomes increasingly integrated into research, teaching, scholarship, and institutional decision-making, understanding its ethical implications is critical. From algorithmic bias and surveillance to questions of accountability and global impact, the ethical landscape of AI is complex and evolving.
This guide provides a curated selection of resources to support those who are:
- Exploring the ethical dimensions of AI in their teaching or research
- Integrating AI tools into coursework or advising students
- Engaging in institutional conversations about data, automation, and policy
Resources are organized around four major areas of concern:
- Fairness and Bias
- Privacy and Security
- Accountability, Transparency, and Oversight
- Societal Impact
Each section is structured into three tiers:
- Overview – High-level overviews and foundational materials.
- Learn More – Additional context and explanation for expanded understanding.
- Dig Deeper – In-depth, detailed insights for readers looking for comprehensive information.

