AI Natives Lab

Higher education has now welcomed students deeply engaged with AI. These AI natives of Higher Education are not merely tech-savvy; they have never known their context without AI. For them, interaction with AI systems is routine, intuitive, and fluent. After higher education, in their workplace, their civic engagement, and their personal lives they will share the contexts and content of a full human life with machine cognitive agents. 

Like the digital natives that fluently saw and built the future of the Internet, AI natives adapt rapidly to new tools, integrate the outputs into their world and work naturally, and possess an intuitive grasp of interaction and systems-level thinking. They do not need remedial exposure to technology; they need an environment that challenges and accelerates their capabilities. They have much to teach us, and they will build the next stage of human civilization.

The Sawyer AI Natives Laboratory is an outgrowth of The Readability Consortium, structured as a real-world accelerator, not a traditional classroom or research-only space. It bridges the university to the rapidly shifting external environment, functioning as a direct pipeline for its members into industry, government, and research organizations. It dovetails with ongoing funded efforts, particularly TRC research focused on human-AI communication, readability, and interface design. It allows AI natives to teach us about the future they leave to build.

Mentorship

Sawyer AI Natives Laboratory members receive access to cutting edge AI tools and intensive mentorship from faculty and external partners across industry and government sectors, and in return mentor us. Mentorship is performance-centered, replicating the demands of external research and development, and in many cases embedded within real-world operational environments. The mentorship is bidirectional, with members and senior laboratory staff exchanging knowledge, mediated by AI. 

The structure emphasizes independence, requiring students to engage real-world challenges directly. It prepares students for internships, fellowships, and professional roles, with mentorship focused not only on technical skills but also on effective collaboration, communication, and delivery. A twice yearly “AI Demo Day” will showcase this work to the world.