Real Intelligence: Teaching in the Era of Generative AI

Teaching With Generative AI Without Losing the Humanities

Generative AI has unsettled classrooms almost overnight. Real Intelligence: Teaching in the Era of Generative AI responds with something more useful than alarm: a practical, thoughtful guide for educators who want to understand the technology, keep students doing meaningful work, and use AI critically rather than pretending it isn’t there.

James F. McGrath, a humanities professor, and Ankur Gupta, a computer science professor, write from opposite sides of the same conversation. That combination gives the book its distinctive value: it explains large language models in plain language while staying rooted in the realities of teaching, discussion, writing, and assessment in the humanities.

🤖 What the Book Covers

The opening chapters explain what generative AI is, how large language models work, and where they remain limited. From there, the book examines common responses that often fail—surveillance, detection tools, and handwritten closed-book exams—and offers alternatives that put the learning process at the center.

Later chapters move into concrete teaching ideas, including:

• assignment designs that make AI use visible or irrelevant
• ways to teach students how to evaluate AI-generated output
• strategies for oral exams, journals, reading responses, and in-class work
• creative uses such as games, role-playing, fiction writing, and image-based projects
• approaches that ask students to tackle wicked problems, work locally, analyze texts, and engage with artifacts or archaeological sites

💡 Beyond Workarounds: Pedagogy That Makes Sense

One of the book’s central claims is that the most effective responses to AI are not merely defensive. The authors argue that many assignments which resist easy AI answers are also better learning experiences. By focusing on process, revision, discussion, and demonstrated thinking, instructors can address academic integrity while helping students develop the skills that matter in the humanities.

📚 A Humanities and Computer Science Conversation

The collaboration between McGrath and Gupta is central to the book’s approach. McGrath brings years of teaching across religious studies, first-year seminars, and core humanities courses. Gupta brings expertise in computer science and AI, including research on computation and the humanities. Together they explain both what the technology does and what it cannot replace.

Who This Book Is For

The primary audience is humanities professors at universities and colleges, but the authors also note that much of the material applies to high school teaching and that broader principles can transfer to earlier grades. Readers outside education who want a clearer understanding of generative AI’s capabilities, limitations, and social implications will also find useful context here.

Why It Matters

The book does not promise that AI will solve teaching problems or that it will destroy the humanities. Instead, it offers a grounded middle path: understand the tools, redesign the work, and keep the human elements of teaching and learning at the center. For educators looking for practical next steps rather than panic, this is a considered and useful companion.