Introduction

Salman Khan’s Brave New Words emerges at a pivotal moment in educational history, when artificial intelligence (AI) is alternately celebrated as a transformative force and denounced as a threat to the human dimensions of teaching. Drawing on his rich experience as the founder of Khan Academy, a globally renowned non-profit organization producing freely available educational videos and exercises, Khan weaves a conversational narrative that eschews dry technical jargon in favor of vivid case studies and practitioner anecdotes. This book is geared toward readers who are new to AI, whether as a parent, teacher, or education policy maker. Rather than serving as a step-by-step guide or an exhaustive chronicle of AI’s evolution, the book offers a practitioner’s reflection on how emerging technologies can be adapted to align with institutional goals and real-world classrooms. Khan brings readers into his conversations with education innovators. The author’s enthusiasm for AI technology in education sometimes outpaces a deeper engagement with its long-term social and pedagogical implications.

A Casual Scholarly Conversation

Salman Khan writes with a casual conversational style that bridges the gap between AI scholar and layperson. Rather than cloaking his insights in dense academic prose, he opts for clear language and anecdotes modeling the pedagogical openness and accessibility that he advocates. Khan removes technical jargon so readers can focus on the book’s proposition that the emerging uses of AI can positively transform education.

Khan incorporates interviews and concise storytelling vignettes from the perspectives of parents, classroom teachers, school administrators, and education researchers to document instances of AI experiments in use. These case-based accounts include adaptive math exercises deployed in under-resourced schools and AI-facilitated historical simulations in humanities courses. The author is transparent about his reliance on pilot studies, pilot program feedback, and his own institution’s data, acknowledging their strengths as well as their limitations. Khan invites the reader to consider an open-ended exploration of what AI might become in the hands of thoughtful educators.

Conversations With AI as a Pedagogical Choice

Throughout the book, Khan explores how AI can be designed as a “Socratic tutor,” a pseudo-collaborator that prompts students with questions rather than supplying ready-made answers. Khan recounts failed attempts to get GPT-3.5 to perform as a Socratic tutor. It was not until GPT-4 was available that this could be achieved, and the book shares how by using the simple prompt: “You will be a Socratic tutor. I will be your student. Don’t give me answers” (p. 31). Khan’s approach to applying a dialogic tradition to the use of AI in education is recognizably aligned with constructivist scaffolding, to incrementally push the learner slightly beyond their current abilities.

The reliance on Socratic dialogue for educational use of AI begins to fray when we consider what human dialogue offers that an algorithm cannot. True Socratic dialogue is laden with emotional nuance, cultural reference points, and nonverbal cues, all of which an AI tutor can only approximate. While Khan shows how AI can simulate empathy by offering reassurance before a daunting problem, it lacks genuine affective understanding. Cultural idioms or community-specific values may be flattened into generic responses, and the absence of shared lived experience may leave machine-mediated exchanges feeling hollow. In this sense, AI conversations risk becoming transactional exchanges of prompts and replies, rather than rich, mutual explorations of ideas.

Might the overreliance on AI-driven questioning threaten to displace the relational heart of teaching? Human tutors attune not only to what students answer, but also to why they hesitate, what emotions surface, and how individual identities shape inquiry. Khan’s own examples of memory-driven personalization, where the system recalls a student’s love of soccer to frame future lessons, demonstrates the promise of adaptive learning. A strength of AI is in looking backwards at a massive amount of data. In this soccer-loving-student scenario, AI may correctly remember a past interest of a learner but have no access to data to show that the learner is no longer interested in soccer. As a pedagogical tool, AI conversations hold real potential, if educators critically calibrate its use to preserve empathy, context-sensitivity, and cultural richness that define human dialogue.

Ethical and Equitable Use of AI in Education

The book’s techno-optimism risks glossing over the reality that real-time AI interactions require substantial broadband connectivity and that global disparities in telecommunications infrastructures can render even the most advanced tools moot in under-resourced settings. Educational technologies are ever evolving. Using AI is not a panacea for resolving funding, policy, and systemic inequality in education.

AI reflects and reproduces existing power structures, decisions about which voices get digitized, whose histories are digitized, and whose cultural frameworks inform the defaults of machine learning models. Khan’s Brave New Words portrays the assumption that bias can be engineered away through fair algorithms and the collection, reporting, and analysis of data. This reliance on AI technology may be an underestimation of the complex social and political concerns that exist in education.

AI’s Place in Educational Practice

Khan stresses that artificial intelligence will not replace teachers but rather empower them to engage in more meaningful educational interactions. He posits that AI would shoulder routine tasks, freeing educators to cultivate deeper mentoring relationships, personalized instruction, and creative curriculum design. Unwittingly, he echoes the techno-optimism advocated by proponents of new educational technologies throughout history.

Khan’s commitment to individualized learning permeates Brave New Words, reflecting the origins of the Khan Academy in offering tailored video lessons to learners at their own pace. This book pays little attention to the educational roles of the relational dynamics of student-to-student or student-to-teacher interactions. He argues repeatedly that personalized pathways, driven by adaptive algorithms, unlock each student’s unique potential more effectively than one-size-fits-all instruction. A reader might see Khan’s pursuit as exactly that which he is rallying against, as he advocates building a better, more complex one-technology-for-all educational tool. This insistence on individualization privileges the solitary learner’s journey and risks underplaying the value of human interactions.

Similarly, Khan’s treatment of standardized testing and learner autonomy deserves academic perusal. The book presents testing data as a neutral metric of progress, often citing improvements in quiz scores following AI interventions, while dismissing broader critiques that standardized exams can narrow curricula and entrench inequities. Testing, at its best, provides actionable feedback; at its worst, it incentivizes teaching to the test and overlooks the holistic development of critical thinking and creativity. His support for data-driven assessments aligns with his emphasis on measurable gains but ignores how overreliance on test scores can distort educational priorities. Although autonomy is well established as an effective drive for learning, students require not only adaptive prompts but also opportunities to collaborate, debate, and co-construct knowledge, practices that standardized testing alone cannot capture.

Closing Comments

First and foremost, Khan frames AI adoption as a challenge of an attitudinal leap. The book succeeds as a reflective, example-driven narrative that encourages educators to engage with AI not as passive consumers of technology but as active co-designers of new pedagogical pathways. His vivid case studies, from adaptive tutoring experiments to AI-assisted humanities simulations, offer concrete illustrations of how institutions’ use of emerging tools can align with their core educational vision, mission, values, and purpose. Khan demonstrates an approach for using AI not only as a tool, but also as a digital collaborator in instructional design. In practice, deploying AI responsibly requires more than a willingness to try new tools; it demands structural literacy about policy contexts, critical awareness of ethical trade-offs, and ongoing reflection on how technology reshapes power and relationships in the classroom.

Looking ahead, several critical questions emerge from what is written in the book. First, which pedagogical values, formative assessment, autonomy, or socio-emotional learning, should guide AI integration into education? Second, how can educators safeguard their professional agency and maintain trust with students when AI assumes more automated roles in feedback, grading, or personalized support? Finally, what level of data collection and reporting is required for AI to effectively track progress and tailor responses without infringing on student privacy? By addressing these questions, educators, technologists, and policymakers will inform how AI in education evolves in ways that may affirm both human dignity and pedagogical rigor. One question that arises from what is not written in the book is: “How might AI be used to initiate, build, and foster relationships between actors within the digital classroom setting, such as learner-to-learner?”

Acknowledgements

I would like to express my sincere gratitude to Dr. Peggy Lynn MacIsaac for her insightful editorial support and thoughtful guidance; her careful scrutiny and encouragement were instrumental in shaping the clarity and depth of this review.

Book Review: Brave New Words - How AI Will Revolutionize Education (and Why It's a Good Thing) by Taoufik Boulhrir is licensed under a Creative Commons Attribution 4.0 International License.