AI and Ethics Resources for Faculty

This curated list provides foundational frameworks, pedagogical guides, and professional standards for the ethical integration of artificial intelligence in higher education. These resources are designed to help faculty and instructional designers support informed, accessible, and inclusive academic practices.

UNESCO Guidance for Generative AI in Education and Research

• Content Creator: United Nations Educational, Scientific and Cultural Organization (UNESCO); authored by Fengchun Miao and Wayne Holmes.

• Description: This publication is UNESCO’s first global guidance on generative AI for education. It promotes a human-centered approach, proposing regulatory steps for data privacy and age limits, alongside frameworks for ethical validation and pedagogical design.

Harvard AI Pedagogy Project Guide

• Content Creator: metaLAB at Harvard within the Berkman Klein Center for Internet & Society.

• Description: An open-access educational platform designed to help faculty distinguish fact from hype. It features an AI starter guide, a sample classroom code of conduct, and a repository of assignments designed to encourage critical thinking about AI’s limitations.

Stanford Teaching Commons AI Teaching Guide

• Content Creator: Stanford University Teaching Commons; led by Kenji Ikemoto.

• Description: A modular, self-directed guide for instructors covering AI literacy, course policy creation, and the integration of AI into assignments. It includes “do-it-yourself” workshop kits for department-level training.

AI Meets Education at Stanford (AIMES))

• Content Creator: AI Meets Education at Stanford (AIMES), coordinated by the Center for Teaching and Learning (CTL).

• Description: A searchable library of teaching artifacts from Stanford faculty. It showcases a spectrum of approaches to handling AI, ranging from “AI Use is Assigned” to “AI Use is Prohibited,” across various disciplines.

CSU Ethical Principles AI Framework for Higher Education

• Content Creator: Dr. Shelli Wynants and the CSU Fullerton team.

• Description: A flexible foundation for responsible AI use based on seven pillars: Exploration, Transparency, Human-Centered approach, Integrity, Continuous Learning, Accessibility, and Legal Compliance. It provides strategies for faculty to mitigate bias and support inclusive pedagogy.

Duke AI Ethics Learning Toolkit

• Content Creator: Duke University Libraries and the Center for Teaching and Learning; developed by Carter Zenke and the Faculty Academy cohort.

• Description: A student-centered toolkit designed for instructors across all disciplines. It provides structured modules to help students investigate critical questions about AI bias, sustainability, and the impact of automation on human cognition.

University of Virginia: Fostering AI Literacy Pressbook

• Content Creator: Fang Yi, Jess Taggart, and Bethany Mickel.

• Description: An interactive Open Educational Resource (OER) guide that moves from basic AI concepts to the critical evaluation of AI outputs. It helps faculty make intentional course design decisions that cultivate student AI literacy.

IEEE Ethically Aligned Design (PDF)

• Content Creator: The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems.

• Description: A comprehensive vision for prioritizing human well-being in the design of AI systems. It offers actionable recommendations for transparency, accountability, and the integration of applied ethics into STEM curricula.

ACM Code of Ethics and Professional Conduct

• Content Creator: Association for Computing Machinery (ACM) Education Board.

• Description: Includes “companion case studies” specifically for computing education. These help faculty teach students how to apply ethical principles to real-world dilemmas like data privacy, algorithmic harm, and social responsibility.

EDUCAUSE AI Ethical Guidelines)

• Content Creator: EDUCAUSE Working Group; authors include Maya Georgieva and Beth Ritter-Guth.

• Description: Inspired by the 1979 Belmont Report, this report adapts core ethical principles—beneficence, justice, and respect for persons—to the higher education AI context to inform institutional policies and classroom practice.

Effortless Academic: AI Ethical Usage in Research

• Content Creator: Effortless Academic.

• Description: A framework for maintaining “cognitive sovereignty” in research. It emphasizes that researchers must take full responsibility for every citation and word they create, even when assisted by AI tools.

OER Commons AI Ethics Curated Collection

• Content Creator: OER Commons Librarians in partnership with various academic research centers.

• Description: A repository of over 110 open-access resources. It includes modules on the ethics of open education, frameworks for safe technology use, and curated materials to help faculty build foundational AI knowledge.