An AI Renaissance in Education: Leaving No Mind Behind

Artificial intelligence is poised to transform education, perhaps more profoundly than any technology since the printing press. Its promise goes well beyond automating administrative tasks or making existing schools more efficient. AI may change how we teach, how we learn and, ultimately, what it means to be educated.

For most of human history, personalized education has been a privilege of the wealthy. AI offers the prospect of individualized, adaptive learning for virtually everyone, regardless of geography, income or learning ability. It could shift the focus of education from ranking students against one another to helping each student master a subject at their own pace.

But these advances raise fundamental questions. If AI can teach us almost anything, what role will human teachers play? If knowledge becomes instantly accessible, what should we be learning? And if we increasingly rely on AI to think, reason and create, what happens to our own intellectual capabilities?

I am optimistic about AI’s potential to improve education and expand human capabilities. But realizing that potential will require us to think carefully about what we gain, what we might lose and how we preserve the essential humanity of education.

Inaugural Jennings Family Distinguished Lecture at Middle Georgia State University.

From Aristotle to Artificial Intelligence

Education has gone through several major transformations.

In ancient times, education was largely a one-on-one experience available to a privileged few. Aristotle tutoring Alexander the Great represents the ideal of individualized instruction: a teacher adapting to the interests, abilities and progress of a single student. The approach was effective, but far too expensive for most people.

The Industrial Revolution brought mass education. Schools adopted a one-to-many model, organizing students into classrooms, standardized curricula and age-based grades. This dramatically expanded access to education and helped create a more literate and productive society.

But industrialized education came with compromises. Students were expected to learn the same material, at roughly the same pace, using similar methods. Those who struggled were often left behind, while those who advanced quickly were held back. Students with different learning styles, disabilities or exceptional abilities often needed support the system could not provide.

The internet began to change this model by making educational resources widely accessible. Khan Academy, for example, showed how technology could deliver high-quality instruction to millions of students at little or no cost. Yet even the best educational videos are one-way communication. They cannot respond to a student’s confusion, adjust an explanation in real time or engage in genuine dialogue.

Artificial intelligence adds this missing dimension: the ability to interact with, adapt to and respond to each learner.

In some respects, AI may let us return to the personalized education of Aristotle and Alexander, but at the scale and cost of mass education.

Personalized Learning at Scale

Perhaps the most compelling promise of AI in education is individualized instruction for every student.

Educational psychologist Benjamin Bloom identified what became known as the “Two Sigma Problem.” His research showed that students who received one-on-one tutoring performed dramatically better than those taught in conventional classrooms. The challenge was finding a practical way to give everyone that level of personal attention.

AI may finally provide a solution.

Intelligent tutoring systems can adjust the pace, complexity and presentation of lessons based on each student’s performance. Rather than following a fixed curriculum, students receive continuous feedback and guidance tailored to their needs. AI can accommodate different languages, learning preferences and abilities, including the needs of students with disabilities or who are neurodivergent.

It also enables a shift toward mastery-based learning.

In a conventional classroom, a student might score 70% on an exam and move on to the next topic, despite not understanding nearly a third of the material. Those gaps accumulate, making later learning more difficult.

With adaptive learning, the system can identify exactly which concepts the student has not mastered and provide more instruction, examples and practice until they do.

The goal becomes mastering the subject, not simply keeping up with classmates.

AI tutors can also offer something that human teachers, constrained by time and resources, cannot always provide: nearly unlimited patience and availability. Students can ask the same question repeatedly without embarrassment, explore alternative explanations and get immediate feedback whenever they need it.

Khan Academy’s Khanmigo is an early example of this approach, using generative AI to engage students in interactive learning rather than simply handing them answers.

This is more than a gain in efficiency. It could change the experience of learning itself, making education more accessible, more engaging and ultimately more effective.

Augmenting Teachers, Not Replacing Them

The implications of AI extend well beyond individual tutoring.

AI can help teachers prepare lessons, develop materials, evaluate student progress and identify students who need extra attention. By automating repetitive administrative work, it could free educators to spend more time on what they do best: teaching, mentoring and inspiring students.

In higher education, AI offers further opportunities to accelerate research, analyze complex data, create interactive simulations and push the boundaries of scientific inquiry. Universities may increasingly use AI for everything from academic advising and career counseling to admissions and administration.

I think about AI’s impact on industries in three stages: optimization, transformation and reinvention.

Optimization means doing existing tasks better, faster and more efficiently. In education, this includes automated grading, lesson preparation and administrative support.

Transformation means performing those same functions in fundamentally different ways. AI tutors, adaptive learning and human-AI collaboration could redefine how education is delivered and experienced.

Reinvention goes further, changing an industry’s economics and structure, sometimes removing humans from parts of the process altogether.

While AI may eventually reinvent some aspects of education, I believe the human teacher will remain central for the foreseeable future.

Education is not simply the transfer of information. It is a deeply human exchange of knowledge, values, perspectives and lived experience. Teachers provide inspiration, empathy, encouragement and moral guidance. They help students develop not only intellectual abilities but also character, confidence and a sense of purpose.

The relationship is also reciprocal. Teachers learn from their students, and both benefit from the experience.

AI can simulate aspects of these relationships, sometimes convincingly, but simulation is not the same as authentic human experience.

The most promising future is one in which AI augments educators rather than replaces them, making teachers more effective while preserving the human connections that make education meaningful.

The AI Literacy Imperative

As AI becomes pervasive, knowing how to work with it may become as essential as reading, writing and arithmetic.

I think of AI literacy as operating at three levels.

The first is creating AI technologies: designing algorithms, developing models, building computing infrastructure and tackling technical challenges such as safety, reliability and alignment. This requires specialized knowledge of computer science, mathematics and engineering.

The second is applying AI to real-world problems. This combines an understanding of AI’s capabilities with expertise in a specific domain, such as healthcare, education, law or business. People working at this level need to understand both the technology and the human problems they are trying to solve.

The third, and by far the broadest, is using and collaborating with AI effectively. Virtually everyone will need some understanding of how these systems work, what they can and cannot do, and how to interact with them intelligently.

This third level matters because AI differs from traditional software. Rather than simply following predetermined commands, AI systems interpret requests, generate responses and sometimes produce unexpected results.

Working well with AI requires the ability to ask good questions, communicate precisely, evaluate responses and exercise independent judgment.

It also requires understanding how AI learns from data and why its output can be unreliable.

AI is not magic. It is mathematics applied at extraordinary scale. It finds patterns and relationships in enormous collections of data, producing results that can appear remarkably intelligent. But AI systems are not infallible. They make mistakes, fabricate information and reflect the biases embedded in their training data.

In many ways, AI is a mirror of humanity, reflecting both our accumulated wisdom and our imperfections.

True AI literacy therefore requires more than technical proficiency. It includes critical thinking, ethical reasoning, problem-solving and an understanding of issues such as privacy, intellectual property and algorithmic bias.

The most successful students will not necessarily be those who know the most facts or can perform tasks AI can already do. They will be those who think independently, ask insightful questions and collaborate effectively with increasingly capable machines.

The Importance of Struggling to Learn

One of my greatest concerns about AI in education is that making learning too easy may undermine some of its most valuable benefits.

Learning is not simply about acquiring information or arriving at the right answer. Struggling with difficult problems builds critical thinking, creativity, persistence and confidence.

When we overcome an intellectual challenge, we gain more than knowledge. We gain a sense of accomplishment and greater belief in our own abilities.

Climbing a mountain would not feel the same if we could teleport to the summit.

AI risks short-circuiting this process. If students can instantly generate essays, solve math problems or produce sophisticated analyses, they may never develop the skills to do those things on their own.

We have already seen smaller versions of this with calculators, spell-checkers and GPS navigation. Each makes us more capable in some ways, but may also erode skills we no longer practice.

AI could extend this tradeoff to much broader areas of human cognition, including reasoning, writing, creativity and decision-making.

There is also the danger of excessive trust. As AI systems become more accurate and persuasive, we may become less inclined to question their conclusions. Even when a system is right 99% of the time, the remaining errors can be consequential, especially when users no longer have the skills or inclination to spot them.

The challenge for educators will be to use AI to enhance learning without eliminating the intellectual effort that makes learning valuable.

A good AI tutor should not simply provide the answer. It should help students discover the answer themselves, encouraging curiosity, reasoning and persistence.

We should use AI to expand human intelligence, not let our own intellectual capabilities atrophy through disuse.

Preserving Humanity in an AI-Powered World

Beyond intellectual dependence, AI raises broader concerns about the human side of education.

One is the risk of substituting artificial relationships for authentic human connection.

AI tutors may seem empathetic, patient and understanding. Students may even become emotionally attached to them. Yet however convincing these interactions become, AI does not share our lived experience or understand human emotion the way other people do.

This distinction is especially important for young children, who are still developing the social skills, emotional understanding and values that come from interacting with other people.

Another concern is bias and the potential narrowing of our intellectual horizons.

AI systems learn from human-generated data, inevitably absorbing the assumptions, preferences and blind spots in that data. As they increasingly recommend content, evaluate performance and shape how subjects are presented, they may subtly influence not only what students learn but also how they understand the world.

This could be particularly problematic if students encounter ideas mainly through a small number of AI systems, each offering its own filtered interpretation of knowledge.

Privacy is another important issue. Effective personalization may require extensive information about a student’s abilities, behavior, interests and learning difficulties. Protecting that data and ensuring it is not misused will be essential.

Finally, AI could worsen existing inequalities if access to the most capable systems remains uneven. The students who could benefit most from personalized learning may be the least able to get it.

I am optimistic that the low marginal cost of AI-based instruction could ultimately broaden access, but that outcome is not inevitable. It will depend on choices made by educators, policymakers and technology developers.

These challenges suggest a clear guiding principle for AI in education: technology should enhance human capabilities and opportunities while preserving our autonomy, our dignity and our relationships with one another.

Beyond the Classroom: AI and the Human Experience

Education may be one of the first institutions to feel the full implications of AI, but it is unlikely to be the last.

As AI becomes embedded in nearly every part of our lives, it could change how we acquire knowledge, solve problems, make decisions and interact with one another.

One of the most exciting possibilities is the democratization of intellectual capability.

Throughout history, our ability to learn and create has been constrained by access to information, expertise, education and resources. AI could dramatically lower these barriers, letting people explore subjects, conduct research and pursue creative work that was previously out of reach.

It could also turn education from a phase of life into a lifelong pursuit. Rather than concentrating formal learning in childhood and early adulthood, people could keep acquiring new skills, exploring new interests and engaging their curiosity throughout their lives.

In this sense, AI may represent a new stage in the evolution of human intelligence: not replacing our minds with more capable machines, but extending what each of us can accomplish by collaborating with a different form of intelligence.

But the risks extend beyond education as well.

If AI increasingly mediates how we receive information, communicate and form opinions, it may shape our sense of identity, our agency and even our relationships with one another. The implications for democracy, journalism, culture and human autonomy could be profound.

The central question is not simply whether AI will make us more productive or knowledgeable. It is whether it will make us more capable, independent and fulfilled human beings.

Toward a Universal Mind?

Marshall McLuhan observed how communication technologies reshape society. The printing press helped create the reading public, while electronic media and the internet brought us closer to a global village.

AI may be the next stage in this evolution.

Could AI create something like a “universal mind,” an interconnected web of human and artificial intelligence through which knowledge, ideas and creativity flow more freely than ever before?

Perhaps. AI could connect people to an extraordinary breadth of knowledge and capability, accelerating the exchange of ideas and expanding the boundaries of human achievement.

But a more connected intelligence does not necessarily mean a more enlightened humanity.

That will depend on whether we preserve the qualities that make human intelligence valuable: curiosity, independent thought, creativity, empathy and the capacity to make meaningful choices.

Ultimately, the future of AI in education is not simply about building better technology or more efficient schools. It is about deciding what kind of society we want to create and what qualities we want to cultivate in future generations.

The greatest opportunity is not to make human intelligence obsolete, but to amplify it.

And the greatest challenge may be ensuring that, as our machines become more capable, we do not lose the very human capabilities we are trying to extend.

This article is based on my lecture, “How AI Is Transforming Education & the Human Experience,” delivered on September 11, 2024, as the inaugural Jennings Family Distinguished Lecture at Middle Georgia State University in Macon, Georgia. This article was co-authored by AI.