As both a subject of study and a tool for teaching and learning, AI demands new knowledge, skills, and critical thinking. Cornell is committed to expanding AI literacy and the creative, responsible use — and intentional non‑use — of AI in the learning environment.
Cornell’s Generative AI Education Working Group brings together faculty, staff, and students from across Cornell’s campuses to help guide the university’s response to AI in the classroom, ensuring that experimentation, evidence, balance, and Cornell’s academic values remain at the forefront of decisions about AI in teaching and learning.
Cornell’s AI + Education strategy is built around seven core principles:
7 Core Principles
1
the integrity of the faculty-student relation.
2
a commitment to experimentation, evidence and learning from experience.
3
the centrality of faculty judgement and expertise in the classroom.
4
responsiveness to real student needs and uses.
5
recognition of both AI ‘goods’ and ‘harms’.
6
respect for institutional and disciplinary heterogeneity.
7
the extension and renewal of Cornell’s core mission and values.
AI Education Working Group Members
- Chair: Steven Jackson, Vice-Provost for Academic Innovation and Professor, Department of Information Science and Department of Science and Technology Studies
- Thurayya Arayssi, Senior Associate Dean for Medical Education and CPD Professor of Clinical Medicine, Weill Cornell Medicine-Qatar
- Jackson Bentley, Student Representative (A&S)
- Ayham Boucher, Executive Director of AI Strategy and Innovation
- Elise Carpenter, Student Representative (Information Science major, Cornell Bowers, CALS)
- Eeshaan Chaudhuri, Student Representative (Brooks School of Public Policy)
- Amy Cheatle, Assistant Director of AI & Learning, Center for Teaching Innovation (CTI)
- Michael Clarkson, Provost’s Teaching Fellow & Teaching Professor, Department of Computer Science (Cornell Bowers)
- Doug Cohen, Director of Educational Computing, Weill Cornell Medicine
- Michelle Trillium Crow, Senior Lecturer and Director, English Language Support Office
- Jason Ezell, Head of Research & Learning Services, Olin & Uris Libraries
- Amy Godert, Director, Learning Strategies Center, Executive Director of Academic Student Success Programs
- David Alan Goldberg, Associate Professor, Operations Research and Information Engineering (Duffield Engineering)
- Udit Gupta, Assistant Professor, Department of Electrical and Computer Engineering (Duffield Engineering + Cornell Tech)
- Monique Harrison, Senior Research & Planning Associate, PBR Institutional Research Planning (SUBD)
- Guy Hoffman, Associate Professor, Department of Mechanical and Aerospace Engineering (Duffield Engineering)
- Tara Holm, Professor, Mathematics (A&S)
- Rebecca Joffrey, IT Innovation Officer, CIT
- Liz Karns, Senior Lecturer, Department of Statistics and Data Science (ILR and Bowers)
- Rene Kizilcec, Associate Professor, Department of Information Science (Bowers)
- Paul Krause, Vice Provost for External Education and Executive Director, eCornell
- Becky Lane, Associate Director for Learning Technologies, Center for Teaching Innovation (CTI)
- Amie Patchen, Environment, Climate & Health Concentration Chief, Lecturer (Veterinary College)
- Jenny Sabin, Professor and Chair of the Department of Design Tech; Arthur L. and Isabel B. Wiesenberger Professor in Architecture (AAP)
- Ashley Shea, Director for AI Literacy
- Liang Shen, Assistant Professor, Department of Clinical Anesthesiology, Weill Cornell Medicine
- Deirdre Gobeille Snyder, Lecturer, SC Johnson College of Business
- Rob Vanderlan, Executive Director, Center for Teaching Innovation (CTI)
- Andrea Stevenson Won, Associate Professor, Department of Communication (CALS)
- Malte Ziewitz, Associate Professor, Department of Science and Technology Studies (A&S)
Generative Artificial Intelligence for Education and Pedagogy
In Spring 2023, the Cornell administration assembled a committee to develop guidelines and recommendations for the use of Generative AI for education at Cornell.
Read their final report evaluating the feasibility, benefits, and limitations of using generative AI technologies in an educational setting and its impact on learning outcomes.
All-Campus Survey
In summer 2025, the working group conducted an all-campus survey of more than 700 faculty and nearly 2,000 students. The group found 70% of students were using GenAI tools once a week or more, compared with 44% of faculty. Students were also on balance more enthusiastic about the use of AI in learning, with 40% agreeing with the statement that ‘in general, GenAI tools have improved teaching and learning at Cornell’ as compared to only 16% of the faculty. But both groups reported a mix of excitement and concern, pro-learning uses and places where AI was challenging or undermining the teaching and learning process.
AI and learning questions have been incorporated into the university's major student survey instruments to benchmark trends and track sentiments and experiences over time through the New Student Survey, Senior Survey, and Cornell Undergraduate Experience Survey.
AI Literacy and AI in the Curriculum
Cornell empowers students, faculty, staff, and members of the broader public to engage with AI effectively, critically, and responsibly. Through interactive trainings, staff development efforts, and discipline-specific learning opportunities, our distinctive ‘AI in the disciplines’ approach builds AI literacy in its technical, ethical, and social dimensions, while ensuring that our AI efforts remain closely embedded in the needs and interests of individual fields and disciplines.
AI Critical Literacy Program
Starting in fall 2026, the AI Critical Literacy Program, developed by Cornell University Library and the Center for Teaching Innovation, is being offered to all incoming undergraduates at the university. This interactive program builds foundational knowledge of what LLMs are and how they work; ethical considerations and debates surrounding their use; their potential role (positive and negative) in student learning; and students’ own principles and strategies for AI use and non-use in their learning process.
Additional Literacy Opportunities
Cornell offers a growing range of AI literacy opportunities for faculty, staff, students, alumni, and the broader community. Existing programs include AI courses, certificates, workshops, and self-directed learning resources available through eCornell, Workday Learning, and campus-based initiatives.
Coming in fall 2026, Cornell will expand these offerings with additional programs for alumni, enhanced staff training and certification opportunities, initiatives for graduate and professional students, K-12 partnerships, and continuing and external education programs designed to help learners build AI knowledge and skills at every level.
Additional Literacy Opportunities
Cornell offers a growing range of AI literacy opportunities for faculty, staff, students, alumni, and the broader community. Existing programs include AI courses, certificates, workshops, and self-directed learning resources available through eCornell, Workday Learning, and campus-based initiatives.
Coming in fall 2026, Cornell will expand these offerings with additional programs for alumni, enhanced staff training and certification opportunities, initiatives for graduate and professional students, K-12 partnerships, and continuing and external education programs designed to help learners build AI knowledge and skills at every level.
AI in Teaching and Learning
The university has built exceptional instructional infrastructure — anchored by the nationally leading Center for Teaching Innovation — to support the thoughtful, balanced, and evidence‑based use of AI tools in education. This work advances effective teaching and learning while addressing challenges to academic integrity and effectiveness posed by rapid transformations in AI. Cornell’s approach includes both 'leaning in' to AI's potential to strengthen education and 'leaning out' to ensure AI doesn't replace key learning.
AI Resources from Center for Teaching Innovation
These resources aim to provide support for faculty responding to GenAI tools and their impact on learning. Common concerns and considerations are addressed in the context of AI, such as academic integrity, accessibility and ethical uses of the technology, as well as practical applications and pedagogical strategies for teaching and assignment design as you determine what approaches and policies regarding AI are the right fit for your classes.
Medical students use AI to practice communication skills
Weill Cornell Medicine is piloting MedSimAI, an AI-powered virtual patient that lets students practice diagnoses and communication skills with instant feedback, offering a cost-effective alternative to traditional actor-based training.
AI and Academic Integrity
Upholding academic integrity is essential to meaningful teaching and learning, especially as AI becomes more capable and more widely used. Cornell emphasizes clear expectations, transparent communication, and evidence‑based practices to help everyone understand when and how AI tools may be used responsibly.
AI + Academic Integrity
Explore Cornell’s guidance on AI and Academic Integrity for course‑policy language, prevention strategies, and practical recommendations that support responsible AI use across the university.
Accepting Responsibility
Accepting Responsibility is an undergraduate-focused educational program that promotes academic integrity through learning, reflection, and personal accountability. Launched as a pilot in Spring 2024 and expanded campus-wide in Fall 2026, the program supports Cornell's commitment to honesty, fairness, and respect for the intellectual work of students, faculty, and instructional staff in all academic endeavors.
Resources
For Faculty
Faculty play a central role in shaping how AI is used in teaching, research, and scholarship at Cornell. This page brings together resources, guidance, and tools to help faculty make informed decisions about the use — and intentional non-use — of AI in their courses, research, and academic work.
For Students
Students across Cornell are exploring how AI can deepen learning, spark creativity, and open doors to hands‑on experience. This page brings together essential AI resources, learning opportunities, and campus tools so you can quickly find what you need.
Get Involved
AI Undergraduate Fellows Program
The AI Undergraduate Fellows Program partners undergraduates with faculty to redesign courses and experiment with new teaching methods, then uses Cornell’s groundbreaking research on AI in teaching to assess outcomes and inform broader integration across Cornell and higher education.
Coming soon.
AI Experimenters Faculty Fellows Program
The AI Experimenters Faculty Fellows Program brings together “radical adopters” and “radical rethinkers” across the university along with specialists in the Center for Teaching Innovation and AI Innovation Hub to imagine and test new modes of pedagogy across all our fields – and then study and disseminate the results, catalyzing change at Cornell and beyond.
Enroll in an AI Innovation Course
The AI Innovation Lab offers students a two-course pathway into applied AI. Start with a foundational course that covers large language models, Retrieval Augmented Generation, and agentic AI systems. Then advance to the AI Innovation Lab course, where you’ll join a team building a real, deployable AI tool for Cornell stakeholders.
AI Innovation Hub
Through the AI Innovation Hub, the Cornell community partners with developer expertise to explore, prototype, and deploy AI‑powered solutions. Students collaborate in this work, gaining real‑world, project‑based learning experiences that support prototype development for university clients.