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As we continue the conversation about AI's growing role in education and research, we've compiled this list of helpful resources. Below, you'll find valuable guides on AI in teaching, practical frameworks for educators, and insights into university-level AI strategy. We hope these resources are useful for your own work and exploration.
This page, provided by Research, Teaching, and Learning (RTL), offers a high-level overview of Generative AI in education. It discusses its impact on teaching, and outlines the key opportunities (such as idea generation and creative inspiration) and challenges (like academic honesty, misinformation, and ethical concerns) for instructors.
This resource, developed by Research, Teaching, and Learning (RTL), offers a flexible learning path designed to help educators navigate GenAI. It guides instructors through understanding GenAI basics, crafting course policies, understanding the limitations of detection tools, redesigning assignments, and exploring the deeper ethical complexities of AI.
From RTL’s Center for Teaching & Learning (CTL), this page offers practical ideas, examples, and tools for instructors. It provides concrete resources for communicating course policies, redesigning assignments and assessments, and reflecting on the role of GenAI in the classroom.
The Berkeley AI Hub is the central portal for artificial intelligence at UC Berkeley. It connects the entire campus community with essential AI tools, training, policies, and opportunities, offering dedicated resources for students, instructors, researchers, and staff.
Learn about the Provost's Advisory Council on Artificial Intelligence (PAC-AI). This page details the council's mission, members, and charge, outlining its role in providing strategic advice on AI across instruction, research, university operations, and policy.
This advisory outlines responsible use of generative AI when working with different types of university data. It specifies which data protection levels (P1–P4) are allowed and spells out prohibited uses (like inputting student records, proprietary research, or using AI to complete academic work without instructor approval).
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