At UT Austin, we are committed to exploring applications of artificial intelligence in education in ways that are innovative and intentional. These guidelines are the result of a working group convened with stakeholders from across campus to advance the University’s AI-Responsible AI-Forward framework by providing a definition and set of principles that give central guidance for students, faculty, and staff on how to adopt AI tools in responsible and ethical ways in teaching and learning contexts.

The definition and principles are designed to foster both innovative and responsible practice. We hope that you can apply these concepts broadly to your creative pedagogical practice and academic pursuits. For more information about what constitutes acceptable use of generative AI tools at the University, please review the Information Security Office’s policy.

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 full 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, understand how these technologies work, their ethical assumptions and implications and the influence they will have on their learning, 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 working principles, applications, limitations and impacts in higher education and beyond while continuously exploring new AI capabilities and emerging tools.
• Ethics: Use AI in ways that recognize the array of ethical implications of technology use on education, 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.
• 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 and embracing the opportunity to design meaningful learning experiences and authentic assessments that help students gain disciplinary knowledge and skills.
• Balance: Use AI with an innovation and future readiness mindset, and with constant 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.
• 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, taking ownership and claiming authorship of the output of tools when appropriate.
• 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.