Whether you're exploring AI for curriculum enhancement, service-oriented tasks, or research, this section offers curated resources, professional development opportunities, and updates on how AI is shaping our institutional landscape. Stay engaged with initiatives that support ethical, effective, and forward-thinking use of artificial intelligence in all aspects of life in the Nest!
Resources & Training Overview
Our Resources & Training repository equips faculty and staff with practical tools and policies for AI integration—from usage guidelines and approved tool lists to academic integrity and IT policies. Find structured support on using AI responsibly, whether you’re drafting a syllabus, advising students, or developing a new research method.
AI LibGuide
This page serves as a comprehensive resource for understanding Artificial Intelligence in the academy. It provides guidance on the ethical use of AI, tips for effective prompting, and information on how to properly cite AI-generated content. Additionally, the guide explores the impact of AI on research and learning, offering curated tools and library resources to help students and faculty navigate the evolving landscape of this technology. Thanks to Bridget Cunio for creating such an essential resource for multiple audiences.
Center for Diagrammatic & Computational Philosophy
The Center spearheads education and research at the intersection of philosophy, computation, and diagrammatic reasoning. By uniting scholars in philosophy, mathematics, and computer science, the Center applies diagrammatic and computational approaches to real-world challenges—ranging from AI development and decision-making systems to economic modeling and bioinformatics.
AI in Teaching badge
This is an exciting professional development credential that explores AI in pedagogy. It encompasses outcomes from the AAC&U’s AI, Pedagogy & The Curriculum work—such as incorporating AI literacy into the curriculum, deploying AI metrics in supervision, and recognizing emerging workplace AI competencies. This badge empowers educators to lead with confidence in the evolving AI-supported classroom.
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AI in Teaching Committee
Gathers information about emerging AI tools and their educational uses. Helps the campus stay up-to-date on new developments in AI and recommends revisions to the academic policy, academic integrity, and curriculum committees.
Chair (appointed): Anna Linnehan
Appointed Members: Tom Kushner, James Faulkner, Brendan Hall, KC Choo, Maureen Gilman, Anna Linnehan, Bridget Cunio, Boyun Woo
Elected Members (3 faculty): Ashlie Perry Banerjee, Sang-Kyu Lee, David DiSarro
Reports To: Sara Quay
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AI Internship and Career Mission
Collects and shares insights on how employers are using AI in hiring, while preparing students to navigate this evolving landscape. Examines the importance of AI knowledge across industries and identifies the specific skills and tools employers value for entry-level roles. By informing schools of emerging trends and equipping students with practical strategies, the committee helps students craft stronger applications, succeed in AI-informed interviews, and build the competencies needed for internship and career success.
Chair (appointed): Jaime Freedman
Appointed Members: Kate Chroust, Jaime Freedman, Helen Eaton, Cher Harrington, Kate Luchini, Cheri Lynch, James Faulkner, Kristy Walker
David Cox’s publications:
David Cox, Associate Director of Research at the Institute for Applied Behavioral Science, has published widely on AI and machine learning.
“Ethical Behavior Analysis in the Age of Artificial Intelligence (AI): The Importance of Understanding Model Building while Formal AI Literacy Curricula are Developed”
“Predicting the Next Response: Demonstrating the Utility of Integrating Artificial Intelligence-Based Reinforcement Learning with Behavior Science”
“A Data‐Driven, Algorithmic Approach to Recommending Hours of ABA for Individuals With ASD”
Listen In
"The Behavioral Data Science" podcast
See below for the Institute for Applied Behavioral Science Associate Director David Cox's trifecta of publications on AI and machine learning.