Making AI Make Sense: Rayan Mansoor’s Role in AI Literacy at UC Davis

For many University of California, Davis, students, the quarter is shaped by lectures, coursework and campus routines. For computer engineering student Rayan Mansoor, that routine also includes helping other students make sense of artificial intelligence. As a UC Davis Library intern, he is developing AI literacy materials designed to support students and instructors in the classroom. 

A Longstanding Interest in AI 

From search engines and study tools to classroom conversations, AI has become part of the academic landscape that students navigate every day. Universities are not just watching AI gain momentum. They are working in real time to understand what its growing presence means for learning. 

Enter Mansoor, whose computer engineering background gives him a technical foundation for approaching emerging technologies in the classroom. For him, the gap between AI and everyday university experience is exactly where the work begins. 

When the UC Davis Library began rolling out applications for its inaugural internship program during the 2025-26 academic year, Mansoor was eager to apply for the open position focused on AI. Artificial intelligence has never been unfamiliar to him; he said he had long been immersed in the emerging technology sphere. 

“No other student job is involved in AI [literacy] whatsoever,” Mansoor said. “I thought it was really interesting that I would be part of that effort that universities are having nowadays to make AI literacy more accessible to undergraduates.” 

From tech-focused circles to his interest in startups, video games and robotics, Mansoor understood that the common denominator across these experiences was artificial intelligence. 

Bridging the Gap Through AI Literacy 

Mansoor approaches his internship with a commitment to fostering a level playing field, meeting his fellow students where they are and helping them approach AI with more clarity. Rather than simply introducing artificial intelligence, Mansoor works to make the technology feel more grounded and approachable. He recognizes that students do not approach these tools from the same place. Some are already familiar with them, while others have had little exposure. For many, engaging with AI is not just a matter of curiosity but of access, time and academic focus. 

“A lot of people don’t know how to use AI, or to what level universities would even let them use it,” Mansoor said. 

In high-stakes academic spaces, the apparent ease of AI can quickly turn into apprehension, leaving students to sort through what is allowed, what crosses a line and how those boundaries change depending on the course or discipline. 

Witnessing that tension, Mansoor focuses on equipping students with the skills to approach AI more clearly in the environments they already move through. 

“A lot of people’s interests lie elsewhere, and they might not even know what AI is,” he said. “I want to be a part of [making] it more common knowledge.” 

Where Engineering Meets Communication 

Working alongside his library staff supervisors Erik Fausak and Melinda Livas, Mansoor uses student experiences, library research and university guidance to help develop AI literacy materials, including modules, videos, interactive content and resources that introduce artificial intelligence in ways that connect directly to coursework. 

Mansoor’s approach is also informed by the conversations students are already having about AI across campus. 

His “Human x Machine” workshop offered one way to enter those conversations, extending the invitation broadly across UC Davis. In a more organic, low-stakes setting, participants were encouraged to share their own experiences with AI, giving Mansoor a clearer sense of how these tools were shaping the lived contexts of their education. 

Rather than functioning as a formal lecture, the exchange allowed Mansoor to hear directly about the challenges, possibilities and gray areas that evolving digital tools were bringing into academic spaces. 

“Getting an undergraduate take is the most important thing,” Mansoor said. “If I’m making modules for them, I’d want to know what they find most useful.” 

By the end of spring quarter, Mansoor is working to mark his yearlong journey with the library through a complete set of AI literacy materials. Meant to be integrated into classes through Canvas, the modules can be imported by instructors, giving students the opportunity to engage with AI as a practical resource rather than something distant or intimidating. 

He approaches the project by pulling from a range of university guidelines, allowing him to account for how AI is framed within UC Davis’ academic expectations. In doing so, he shapes materials that remain accessible while still reflecting the realities students encounter across disciplines. 

Alongside the lessons, Mansoor has also considered developing a chatbot that would allow students to interact directly with these tools. The idea, he said, is to use AI to teach AI, helping students better understand the technology’s capacity and how more specific prompts can lead to different kinds of responses. 

For Mansoor, AI literacy is about response: how students and institutions can build a dialogue with new technology as it continues to change. 

“It’s a way of keeping up with innovation,” he said.