AI Committees

To further guide the integration of artificial intelligence into the academic work at Tulane University, during the 2023-2024 academic year, the provost established two committees, each with a representative from each academic school, to learn more about the current campus environment and the needs and interests of the faculty. Each of these groups has recently completed their work and submitted reports detailing their insights and recommendations.

AI in Classroom Committee

The  AI in Classroom Committee was cochaired by Toni Weiss (Exec. Dir. of CELT) and  Mike Griffith (Dir of the ILC), and the other members were Visky Mayer (SLA), Paul Hutchinson (TSPHTM), Guenevere Rae (SOM), Stacy Seichnaydre (LAW), Bill Rials (SOPA), Rajat Khanna (BUS), Nicholas Mattei (SSE), Kathy Oqueli McGraw (TSSW) and Verse Shom (ARCH). The report, titled  AI in Pedagogical Practice, focuses on incorporating AI technologies into our educational practices, ensuring ethical and effective use to enhance learning experiences. Review the AI in Classroom Committee Report Executive Summary (pdf).

The Committee’s Key Recommendations

Strategic Integration and Alignment

1. Define clear educational objectives for AI use within the curriculum, ensuring that the use of AI tools aligns with broader institutional goals and student learning needs and reflects the diverse perspectives of faculty, staff and students across different academic disciplines.
2. Establish guidelines for the acceptable use of AI in coursework and assessments, clarifying when and how AI assistance is permissible. Create a standardized format to cite/acknowledge where and how AI tools were used.
3. Develop a strategy regarding the transparent use of GenAI tools for both students and faculty, including its capabilities, limitations, and the logic behind its recommendations or decisions. Emphasize the importance of ethical considerations in AI applications, promoting responsible use and decision-making.
4. Adhere to strict data privacy and security protocols, ensuring that student and faculty data are protected and used responsibly. Provide clear information to users about data collection practices, usage, and their rights regarding personal information to foster trust and transparency.

Academic Experience

5. Leverage AI to offer individualized academic experiences, adapting to individual needs, styles, and pace. Ensure that AI resources and support are accessible to all faculty and students, regardless of ability, to promote equitable learning opportunities via university-supported options for faculty and students.
6. Regularly assess the effectiveness and impact of AI tools on learning outcomes, student engagement, course objectives, and academic integrity. Solicit feedback from both faculty and students to identify areas for improvement and ensure ongoing optimization of AI integration.

Support and Development

7. Provide comprehensive training and ongoing support for faculty to effectively integrate AI tools into teaching and learning processes. These programs will allow faculty to build confidence and proficiency in AI utilization. The university must work actively to reduce barriers and create opportunities for faculty learning.

Innovation and Culture

8. Foster a growth mindset encouraging the exploration of new AI tools and approaches in teaching and learning. Remain adaptable to emerging technologies and pedagogical trends, updating guidelines and practices accordingly to stay at the forefront of educational innovation.
9. Orient students to AI tools being used, including their purpose and how they will be integrated into their future careers. Facilitate open discussions about AI's role in education and empower students to make informed decisions about their participation.
10. Consider the cultural and community context of AI use, ensuring it aligns with institutional values and respects diverse perspectives. Engage stakeholders within Tulane, New Orleans, and the wider academic community in discussions about AI integration to address concerns, promote inclusivity, and build consensus within the educational community.

The Committee further recommended that this work be supported largely through the expansion of existing centers, such as the Connolly Alexander Institute for Data Science (CAIDS), the Center for Engaged Learning and Teaching (CELT), the Innovative Learning Center (ILC), and the Center for Community Engaged Artificial Intelligence (CEAI).

University Committee on GenAI in Research

The University Committee on GenAI in Research was cochaired by Giovanni Piedemonte (VP for Research) and Noel Wong (VP for IT) and its membership included Susan Davies (TSSW), Patrick Rafail (SLA), David Crosslin (SOM)m Alessandra Bazzano (TPHTM), Onnig Dombalagian (Law), Aron Culotta (SSE), Zaid Kashef Alghata (ARCH), Eugina Leung (BUS), with ad hoc members Matthew Koenig (Exec. Dir., Intellectual Property Management), Chris Nichols (Assoc. GC for Intellectual Property), Jeremy Pelegrin (Chief Information Security Officer), Alan Clerk (Sr. Dep. Admin, Office of Research), and Mike Griffith (Dir. of Innovative Learning Center). has also recently submitted their report.

The Committee’s Key Recommendations