Responsible Adoption of AI Tools for Teaching and Learning

Definition of Responsible Adoption of AI for Teaching and Learning

At UT Austin, we define responsible use of AI in teaching and learning as the adoption of AI that facilitates the achievement of learning outcomes and fosters human development for all members of the campus community.

Learning outcomes are course-specific and refer to the things students should know, be able to do, and the mindsets they should develop as a result of a learning experience.  The adoption of AI tools should be intentional, empowering all students and educators to take agency over their teaching and learning experiences, strengthen relationships within learning communities, uphold personal integrity, and navigate ambiguity. To use AI responsibly, students and educators must always be in the loop and show understanding of how these technologies work, their ethical assumptions and implications, and the influence they will have on careers and society.

Implementing AI in ways that are vetted, secure, safe, ethical, accessible, open and available to everyone, transparent, and honest are requirements for responsible adoption in teaching and learning environments.

Framework of Principles for Responsible Adoption of AI for Teaching and Learning

Responsible adoption of AI tools in teaching and learning includes the following principles.

• Literacy: Use AI with fluency in its principles, applications, limitations, and impacts in higher education and beyond.
• Intention: Use AI transparently and in the support the achievement of learning in and across disciplinary contexts, including knowing when and why it should and should not be used.
• Balance: Use AI with an innovation and future readiness mindset, and with the awareness of the evolving benefits and drawbacks in the context of teaching and learning across areas of study.
• Agency: Use AI in ways that maintain and enhance the agency of humans over their intellectual output, decision-making, and the teaching and learning process.
• Ethics: Use AI in ways that recognize the array of ethical implications of technology use on the environment, labor, society and other considerations, engage with those implications and consequences across contexts, and consistently practice evaluating when AI can versus should be used.
• Relationships: Use AI in ways that enhance and extend the connections between everyone within a learning community—students and their peers, faculty and students, staff and the people that they serve—rather than diminish or replace them.
• Academic Integrity: Use AI in alignment with our honor code and fundamental scholarly values such honesty, respect, and authenticity.
• Stewardship: Use AI in ways that are explicit about how data is being shared, and guardrails are established to uphold the privacy, safety, security, accessibility, intellectual property rights and right to access of everyone in our teaching and learning community.

Working Group Charge

The working group responded to the following charge:

1.0. Develop a comprehensive definition of what it means from the student, instructor, teaching assistant, and academic staff point-of-view to adopt generative AI tools in a responsible manner at the University.

2.0. Develop a framework consisting of 5-7 informed principles to help guide the responsible adoption of generative AI tools for teaching and learning at UT Austin.

3.0 Develop a set of recommendations for communicating, training, and informing the University on the responsible adoption of generative AI in teaching and learning at UT Austin.