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ETHICAL Principles AI Framework for Higher Education

by Wynants, S., Childers, G., De La Torre Roman, Y. , Budar-Turner, D., & Vasquez, P. (2025) at California State University, Fullerton.  Licensed under CC BY-NC 4.0 
 

Introduction

The ETHICAL Principles AI Framework for Higher Education is designed to provide a flexible and adaptable foundation for the responsible use of Artificial Intelligence (AI) across diverse academic contexts. This framework recognizes the rapidly evolving nature of AI technologies and the varying needs of different departments, colleges, and institutions.

Our goal is to offer a set of guiding principles that can be readily interpreted and applied to individual circumstances, ensuring relevance and utility as AI continues to advance. The framework intentionally avoids rigid definitions, allowing users to contextualize and adapt these principles to their unique environments, academic settings, and as technologies change.
By providing this framework under a Creative Commons license, we encourage its widespread use, modification, and adaptation. We invite departments, colleges, and other institutions to tailor these principles to their specific needs, fostering a culture of responsible AI use that aligns with their values and objectives.

It is important to note that this framework is not prescriptive. Instead, it serves as a starting point for developing more detailed policies, guidelines, and educational programs. The specific implementation of these principles, including how to address potential AI limitations and biases, should be determined by individual units or institutions based on their unique contexts and evolving understanding of AI technologies.

As laws and regulations surrounding AI-generated content and its use in academia continue to develop, this framework provides a stable ethical foundation that can accommodate future legal and technological changes. We encourage users of this framework to stay informed about current developments and to interpret these principles in light of the most up-to-date information available.

By adopting and adapting this ETHICAL Principles AI Framework, institutions can foster a thoughtful, responsible, inclusive, and innovative approach to AI integration in higher education, promoting ethical considerations while embracing the potential of these transformative technologies.

What follows is an accessible infographic of the framework, and then a more detailed description of each of the ethical principles of the framework, ending with recommended practical application strategies for implementing the framework across an institution.
 

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This image is described in full below.
 

ETHICAL Principles AI Framework for Higher Education


Exploration and Evaluation

Critically assess and evaluate AI tools and outputs.

  • Encourage students, faculty, staff, and administrators to explore and experiment with AI tools safely
  • Encourage the development of AI literacy across all levels of the institution
  • Explore AI’s capabilities and limitations, including potential biases and risks (e.g., privacy, security) in AI systems and their outputs
  • Understand that skepticism, reflection, critical analysis, and adaptability are necessities when engaging with AI
  • Verify the accuracy and reliability of AI-generated content
  • Assess the appropriateness of AI use for specific tasks or assignments
  • Develop skills to craft and refine prompts for AI interactions, encouraging more accurate, relevant, and useful outcomes


Transparency and Accountability

Maintain openness about AI use in academic and administrative contexts

  • Communicate AI policies and guidelines to all campus stakeholders
  • Encourage open dialogue about AI's role in higher education
  • Clearly communicate when and how AI is being used in courses, research, or administrative processes
  • Disclose the limitations and potential biases of AI tools used in academic settings
  • Provide clear information about data collection and usage in AI applications
  • Implement a system for regular AI audits to assess the impact and effectiveness of AI implementations on campus and share those results with the campus community
  • Establish mechanisms for reporting AI-related concerns or issues


Human-Centered Approach

Prioritize human judgment and decision-making in AI applications.

  • Use AI as a tool to augment human capabilities, not replace them
  • Ensure AI complements rather than replaces human expertise and judgment
  • Ensure decisions affecting individuals are made or reviewed by humans
  • Promote critical thinking and evaluation of AI-generated content
  • Design AI implementations that enhance human capabilities and creativity
  • Prioritize the well-being and agency of students and faculty in AI adoption
  • Regularly assess the psychological and social impacts of AI integration on the campus community


Integrity and Academic Honesty

Uphold academic and professional standards when using AI and promote responsible AI use in learning and research

  •  Develop and follow clear guidelines for responsible AI use in academic work
  • Properly attribute AI-generated content in assignments and research
  • Educate the campus community on citation, attribution, and ethical use methods of AI-generated content and AI tools
  • Use AI tools in ways that align with institutional values and ethics
  • Develop best practices for integrating AI tools into curriculum and pedagogy
  • Encourage faculty to design curriculum and assessments that promote responsible use of AI and enhance student learning, as appropriate
  • Promote ethical considerations in AI development and deployment on campus
     

Continuous Learning and Innovation

Foster ongoing education about AI technologies and their implications.

  • Provide and engage in regular AI literacy training and professional development for the campus community
  • Integrate AI literacy into curriculum across disciplines
  • Stay informed about emerging AI technologies and their potential impacts
  • Adapt AI practices based on new developments and ethical and environmental considerations
  • Foster an environment that encourages AI-driven innovation in education
  • Foster a culture of sharing lessons learned from AI implementations
  • Support the development of novel AI applications tailored to educational needs
  • Collaborate with industry partners to bring cutting-edge AI technologies to campus
  • Support faculty and student initiatives to explore innovative AI uses in education
  • Encourage interdisciplinary collaborations in AI exploration and application
  • Establish partnerships with other educational institutions to share best practices and lessons learned in AI implementation


Accessibility and Inclusivity

Ensure AI use promotes equity and inclusive opportunities

  • Ensure AI tools are accessible to users with diverse needs and abilities
  • Provide alternative options for those who cannot or choose not to use AI tools
  • Actively seek diverse perspectives and representation in AI development, implementation, and policymaking
  • Regularly assess AI tools for potential biases or discriminatory outcomes
  • Actively work to mitigate biases in AI systems that may result in unfair or discriminatory outcomes
  • Develop recommendations for creating AI prompts and interactions that are inclusive and align with culturally relevant and anti-racist pedagogy
  • Consider the long-term impacts of AI use on learning outcomes and educational equity


Legal and Ethical Compliance

Adhere to relevant laws, regulations, and ethical standards in AI use.

  • Respect data privacy and security regulations when using AI systems
  • Comply with copyright and intellectual property laws when using AI-generated content
  • Follow institutional and professional ethical guidelines in AI applications
  • Stay informed about evolving AI regulations and adjust practices accordingly
  • Develop ethical guidelines specific to AI use in research, teaching, and administration
  • Develop clear policies on the ownership and use of AI-generated intellectual property created within the
    institution
  • Establish an AI ethics review board to oversee high-impact AI projects


Practical Application Strategies for the ETHICAL Principles AI Framework

To implement this framework effectively across higher education, we encourage:

  1. For Faculty/Instructors:
    • Apply the framework when incorporating AI tools in curriculum, teaching, and assessment
    • Engage in peer and campus discussions about ethical AI applications
    • Participate in AI professional development offered by the institution
  2. For Staff:
    • Apply the framework when considering and using AI tools for administrative tasks
    • Engage in peer and campus discussions about ethical AI applications
    • Participate in AI professional development offered by the institution
  3. For Students:
    • Review your syllabus and engage with your instructors to understand how best to integrate AI tools in each specific context. Recognize that AI policies and expectations may vary across courses,
      instructors, and even individual assignments
    • Engage in class discussions about ethical AI applications
    • Participate in AI literacy programs offered by the institution
  4. For Administrators:
    • Use the framework when creating AI policies/guidelines for the campus, evaluating AI applications
      for the campus, and communicating AI information to the campus
    • Participate in AI professional development
    • Establish a centralized resource hub for campus AI exploration, experimentation, and innovation
      information


Recommendation for Continuous Improvement of this Framework:

  • Regularly evaluate the effectiveness of the ETHICAL AI framework
  • Continue to gather feedback from all users to refine and improve the AI framework
  • Adapt the framework as new AI technologies and challenges emerge

The ETHICAL Principles AI Framework - Project Summary

As part of the 2024-2025 AAC&U Institute on AI, Pedagogy, and the Curriculum , a California State University, Fullerton (CSUF) team pursued this project to advance equitable AI integration in higher education while addressing critical concerns about bias, academic integrity, and technological accessibility. Their work stemmed from a commitment to prepare students for an AI-driven world while upholding CSUF’s strategic focus on social justice and inclusive pedagogy.

The team, led by Shelli Wynants, consisted of experts from various CSU Fullerton fields:

  • Philip Vasquez: Director of Diversity, Inclusion, and Equity Programs
  • Greg Childers: Director of CSUF's GE Program
  • Donna Budar-Turner: Director of Student Conduct
  • Yessica De La Torre: Director of Assessment
  • Shelli Wynants: Faculty Champion & Quality Online Inclusive Learning Design Coordinator

Overall Purpose of the Framework

The ETHICAL Principles AI Framework for Higher Education aims to provide a flexible and adaptable foundation for the responsible use of Artificial Intelligence across diverse academic contexts. It offers a set of guiding principles that can be readily interpreted and applied to individual circumstances, ensuring relevance and utility as AI continues to advance, while intentionally avoiding rigid definitions to allow users to contextualize and adapt these principles to their unique environments and as technologies change. (See Introduction of the Framework for more information)

Project Development Stages

  1. Foundation through Collaboration (Fall 2024)

The multidisciplinary team engaged with the AAC&U Institute on AI, Pedagogy, and Curriculum to:

  • Learn about national standards, diverse campus policies and projects
  • Gather insights from peer institutions
  • Examine campus survey results to assess campus-wide AI needs
  1. Framework Co-Creation (2024-2025)

Developed through:

  • Reading a variety of existing literature on ethics and AI in education
  • Brainstorming with AI to gain insights on consistencies across the literature
  • Engaging in multiple dialogue sessions with team, institute partners, and our institute advisor/mentor (Jose Bowen)
  • Multiple drafts, with collected feedback from a variety of campus constituents

Core output: The ETHICAL Principles Framework with seven pillars.

  1. Campus-Wide Sharing of Framework (February 2025)

Next Strategic Steps

Our team will be exploring

  • Case Study Development (examples of how units/departments/campus individuals have used and adapted the framework for their work)
  • Professional Development Expansion (providing more learning options to address areas on the framework that campus would like to explore more)
  • Continuous Improvement (learning from others who have used and adapted the framework, as it has a Creative Commons license and will be shared widely)

Primary Sources

Akgun, S., Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings . AI Ethics 2, 431–440.

California Department of Education. (2023). Learning with AI, Learning about AI .  

Common Sense Media. (2024). Generative AI in K-12 Education: Challenges and Opportunities . White Paper.

European Commission: Directorate-General for Education, Youth, Sport and Culture. (2022). Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators . Publications Office of the European Union.

Hibbert, M. et al. (2024). A Framework for AI Literacy . Educause.

Ma, L., & Zhao, D. (2024). Prospects and Ethical Considerations of Generative Artificial Intelligence in Higher Education . SHS Web of Conferences.

Mills, K., et al. (2024). AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology . Digital Promise.

Office of the Director of National Intelligence. (2020). Artificial Intelligence Ethics Framework for the Intelligence Community .

Additional Resources

AI for Education & Cubero, V. (2023). Updated Framework: How to Use AI Responsibly EVERY Time .

Cornell University - Center for Teaching Innovation. Ethical AI for Teaching and Learning .

Takabori, A. Top 10 Ethical AI Practices to Teach K-12 Students . Carnegie Learning.

University of Lincoln - Digital Education. Ethical Considerations for AI .

 

"ETHICAL Principles AI Framework for Higher Education" by Wynants, S., Childers, G., De La Torre Roman, Y. , Budar-Turner, D., & Vasquez, P. (2025) at California State University, Fullerton is licensed under CC BY-NC 4.0 
 

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