Bowen, José Antonio, and C. Edward Watson. Teaching with AI: A Practical Guide to a New Era of Human Learning. Baltimore: Johns Hopkins University Press, 2024. 238 pp. ISBN (paperback): 9781421449227.
Teaching with AI offers a timely, insightful exploration of the intersection between artificial intelligence and education, encouraging important conversations about AI’s impact and challenges. Structured in a three-part progression—Thinking with AI, Teaching with AI, and Learning with AI—Bowen and Watson skillfully navigate the philosophical, practical, and pedagogical dimensions of integrating AI into education.
The book begins by challenging preconceived notions about AI, urging educators to embrace its disruptive potential as a creative and cognitive collaborator. The assertion that “what we call cheating, businesses see as innovation” (p. 5) reframes AI tools not as threats to academic integrity but as opportunities to prepare students for real-world problem-solving. Particularly important in this section is the idea that AI may reduce inequalities in performance (p. 38) by aiding weaker writers and leveling the academic playing field. This section also highlights the iterative nature of AI as a thinking partner, a theme that resonates throughout the text. The authors’ insight that creativity thrives in “reflection, back and forth, [and] refined questions” (p. 77) is hopeful, presenting AI as a catalyst for deeper intellectual engagement rather than a shortcut for superficial tasks.
Building on the idea that AI can facilitate deeper learning, an analogy comparing the advent of talking movies to the rise of AI is especially thought-provoking: “Talking movies required new skills from actors, and the microphone allowed for a completely new style of singing” (p. 73). Just as the microphone transformed the art of performance by enabling subtler, more intimate expressions, AI provides tools that enable deeper and more dynamic approaches to thinking and creation. Throughout the text, the authors suggest that AI could reshape thinking by shifting focus from memorization to synthesis and evaluation, accelerating problem-solving, and personalizing learning that enables more self-regulated and autonomous learners. They also suggest that AI tools might enhance creativity by providing adaptive resources that enable users to experiment and take more risks, refine ideas with deeper critical reflection, and push creative boundaries. However, they caution that these tools could also weaken deep thinking, critical reasoning, and independent thought if assessments do not account for how AI might be used to bypass these cognitive processes.
The middle chapters delve into the pragmatic aspects of teaching with AI, presenting it as a tool that both supports and disrupts traditional pedagogical models. A recurring concern is how AI might amplify existing biases or create inequities, especially among students who lack familiarity with AI tools due to social or economic barriers. The authors acknowledge this challenge, advocating for equitable access and thoughtful integration of AI in classrooms. Practical suggestions—like assigning extra credit for creative prompting or having students compare AI-generated outputs from “bland” vs. creative prompts—demonstrate how educators can harness AI to foster critical thinking. The authors also address AI’s limitations throughout; for instance, they critique AI’s ability to generate quality test questions (p. 95), raise ethical questions about its misuse, and present concerns about potential inequities that may arise when policing AI use.
The book’s final section explores AI as a tool for personalized, reflective, and creative learning. Particularly compelling is an emphasis on discomfort as an essential part of the learning process. The book suggests that struggling to articulate one’s thoughts without over-relying on AI can be an invaluable exercise in clarifying ideas. The text also emphasizes the value of student voice, urging educators to make student contributions central. This emphasis is evident in the idea of using AI as a “devil’s advocate” in classroom discussions or challenging students to critique AI-generated arguments. These activities underscore how AI can serve as a springboard for higher order thinking rather than a replacement for it.
The ethical implications of AI feature prominently in the book’s latter chapters. Activities like having AI generate opposing ethical arguments and then having students apply their own moral judgment (p. 204) promote critical thinking about AI’s limitations. The suggestion of integrating AI into assessment design, such as having students improve AI-generated work or evaluate examples of poor AI output, is also noteworthy. These tasks cultivate a nuanced understanding of AI’s capabilities and shortcomings while emphasizing the irreplaceable value of human judgment and creativity.
The authors also offer some compelling insights into the writing process, emphasizing the importance of struggle and reflection to counter concerns about AI enabling students to outsource their writing. Rather than focusing solely on AI’s drawbacks, they highlight strategies to help students retain ownership of their writing and develop their ideas through effort and self-reflection. One particularly effective idea presented in the book is the use of structured questions (p. 187) as a prelude to assignments. By engaging with these prompts beforehand, students can clarify their thinking and set a strong foundation for their work. The book also highlights the importance of grappling with language as an essential part of learning. The authors illustrate how the difficulty of finding the right words can be a key step in clarifying one’s thoughts—a point exemplified by a discussion of AI-generated wedding vows. This example underscores how the struggle to articulate ideas is not just a challenge but a valuable process that deepens understanding.
One notable gap is the discussion of AI’s recursiveness and its potential risks. While the authors acknowledge AI’s role in generating content, there is little exploration of how its tendency to reiterate patterns can lead to stagnation or misinformation. Additionally, while the book touches on AI’s potential to create both equity and inequity in classrooms, more concrete examples would strengthen this discussion. The impact of AI on assessment is another area that could use more depth—at one point, the authors critique AI’s ability to generate quality test questions but could provide more effective strategies for crafting high-quality AI-generated questions (p. 95). Other missed opportunities include exploring strategies for managing suspected AI misuse and for helping educators navigate students’ ethical objections to using AI. Similarly, there is little discussion of how learning theories might inform the design and effectiveness of customized GPTs. Given AI’s growing role in tutoring and formative assessment, this would have been a valuable addition.
Overall, Teaching with AI is a thought-provoking guide for educators navigating the complexities of integrating AI into their teaching and learning practices, enriched by a diverse range of examples from a variety of disciplines that illustrate its impact across various fields. It celebrates AI’s potential to foster creativity, equity, and engagement while cautioning against its risks and limitations. The book challenges educators to rethink traditional notions of integrity, creativity, and critical thinking, offering actionable strategies to utilize AI’s power effectively and responsibly. For educators willing to adapt and innovate, this book provides both a philosophical framework and a practical toolkit for teaching with AI in the twenty-first century.
*AI assisted in suggesting edits and organizing the structure of this review.
Dana Riger, The University of North Carolina at Chapel Hill