Why "Irreplaceable"?

“Will AI replace teachers?” 

This question reveals more about the beliefs and assumptions people have about teaching and learning than anything else.

To us, the answer is clear: No, AI will not replace teachers. The core components of learning – human agency; the relationships between students, teachers, and content; essential skills; and much more – are timeless. 

But that’s not the whole story. AI will replace some tasks in education, and AI has the potential to substantially change many aspects of the experience of school, for both teachers and students. Some for the better, and others for the worse. 

In this book, we draw lessons from learning science, education research, classroom experience, history, and more to surface both the timeless truths that have emerged in education and also how the technology of our time – artificial intelligence – is interacting with these truths. We affirm what is irreplaceable, and offer insight not only into what is changing now, but into how elements of education might continue to change in the coming years as the technology matures.

In this first blog post, we preview a selection of what the book explores in greater detail – including (near the end) the one timeless truth that gives structure to our book.

Enduring skills and attitudes

While talk of “transforming” education is almost a cliché now, a look at history shows that in the past technology has indeed had a transformative impact on learning (Dedehayir & Steinert, 2016).

• Writing changed our relationship with information and memory.

• The printing press democratized access to knowledge.

• The dictionary and encyclopedia aggregated and organized language and meaning.

• The calculator commodified computational ability.

• The word processor and personal computer accelerated the work of writing.

• The internet enabled more rapid, asynchronous, and remote collaboration. (Gleick, 2011; Ong, 1982)

And yet, despite these dramatic technological changes over these centuries, the skills we teach students largely remain the same. Whereas once we asked students to draw graphs by hand and then interpret them, now students use calculators to draw graphs—and then interpret them. Whereas once we taught students to find sources in the library and analyze them, now we still teach students to find sources at the library – and also now on the internet, too — and then analyze them. Interpretation, analysis, critical thinking: objectives like these remain the same no matter how rapidly the technological world advances. 

These changing technologies do allow us to do new kinds of work, but they do not change the core mechanisms that drive meaningful learning and shape our human experience. Students with AI, like students before them, will still stumble to figure out how to form the right question. Students with AI will still develop incomplete mastery – even when an AI is supporting their efforts. Students with AI will still need time and experience to learn to interact with each other. As long as we are human, this will remain. 

Messy human connection

There’s a vision among some members of society that perfectly tuned AI tutors can teach every student individually in a kind of perfectly frictionless, personalized learning environment. Who will need school when this happens? Won’t students be able to accelerate learning beyond what might be conceivable today, and won’t all students have the opportunity to become superachievers?

The good news is that improvements in AI tutors will continue to increase the amount of learning that students are able to pursue on their own. As technology grows more capable – and the development of today’s generative AI technology likely marks the greatest leap in capability of our lifetimes – it will increasingly shift the balance of knowledge and skill transfer further outside of the classroom, so students can achieve a greater degree of mastery on their own, even if it is not total. This is an enormous leap forward for learning.

The “bad” news (for believers in the utopian AI tutor vision), is that even if all students could achieve perfect mastery outside of class, purpose, accountability, and making meaning from what they have learned depends on their experiences interacting with each other. The classroom is where our ideas meet reality, it’s where our understanding is challenged by other people’s understanding, it’s where our assumptions are tested and our connections with others are built and strengthened. The classroom is where diverse perspectives meet. It’s where we learn to build bridges across real differences and see through perceived differences to the underlying points of agreement we can build mutual understanding from. While more and more can be learned outside of class, the classroom remains essential for bringing that learning into the world, recognizing that we are social beings whose knowledge and skills gain meaning from the way they unpredictably and complexly affect and are affected by others.

This human connection, which is built through messy interactions, is one of the elements of school and learning that we argue is irreplaceable.

The ecosystem of learning

This kind of connection has endured across time – and it is built in three contexts. From the School of Athens to medieval tutors to our modern school system, the work of formal education has been made of: teachers preparing outside of class, students doing work outside of class, and the classroom itself, where teachers and students meet. These three contexts endure. What has changed over time, however, is what we can do in these three contexts.

Presently, each of these three contexts has new opportunities and risks brought by artificial intelligence. The challenge of our time, therefore, is discovering and developing the positive use cases for AI in each of these settings while also reducing the negative impacts – as rapidly as possible. 

We won’t accomplish the development of this positive future by ignoring or dismissing AI, nor will we accomplish it by blindly embracing it. In Irreplaceable, we seek to accelerate our path towards a positive alternative future (Facer, 2011) by looking at AI through the lens of learning science and what we know works in education.

To do this, our book is structured around the opportunities and risks that arise in all three contexts of school. The book is organized into three sections, one for each context, and for each context we identify different ways AI serves as an assistant to our human-centered work:

• Part I is about AI for teachers. It explores how teachers have access now to AI as a research assistant, planning assistant, and feedback assistant.

• Part II is about AI for students. It explores how students have increasing access to AI as learning assistants and doing assistants.

• And Part III is about AI in the classroom. It explores

  how AI is growing as an administrative assistant and as a teaching assistant.

Each part takes a balanced approach to what is possible, recognizing risks of the erosion of learning and human agency while exploring and sharing paths towards new, research-based learning and agency opportunities.

While the grammar of school remains the same, AI’s presence in all of these settings and its ability to make connections across these settings combine to create an ecosystem for learning that will ultimately serve students and teachers alike. It will grow through fits and starts – and we are only in the infancy of its development – but it will increasingly provide greater and greater utility that poses challenging questions to teachers while also introducing new opportunities to advance learning.

Conclusion

We are living in a time that is gradually eroding student agency – and therefore the agency of humans of the future. Algorithmic feeds are determining what students watch, read, and buy; social media is outsourcing self-worth to external metrics; optimization culture is providing “best practices” for everything; highly involved parenting is reducing children’s decision-making; and in an effort to make learning accessible, teachers are providing increasingly detailed instructions that lead towards more compliance than critical thinking. 

The result is environments that may be training children to ask “Where do you want me to go?” instead of “Where could I take this?”

AI risks exacerbating this erosion of agency. If students – and teachers – delegate our thinking and become over-reliant on AI, we risk shortcutting learning, reducing the power of human voice, and sleepwalking into our future.

But the opposite is also true. AI puts a creative team in the hands of every student, it provides opportunity for students who struggle to more readily reach proficiency, it enables students to reach farther and do more. If we scaffold the responsible use of AI, we increase students’ ability to create the future.

Success in our AI future depends on principled engagement. But what should be our principles? That is what remains timeless.

In this time of increasingly rapid technological change, we need something to ground our work in education. The elements of learning we describe here are only some of the key ideas we explore in Irreplaceable. They have been with us throughout technological transformations in the past, and they will, in all likelihood, endure through the technological transformations we encounter in the future. 

And these are only a few of many other elements of teaching and learning that we discuss throughout the book – both conceptual and practical. What they all look like in the classroom, how teachers and school leaders can engage with them in professional learning, and how technologists can design new tech-enabled experiences with them in mind – these and more, we dive into in greater detail in the book, and we look forward to exploring some of them here, in our blog post series leading up to the book.

Pre-Order Here.

Works Cited:

Facer, K. (2011). Learning futures: Education, technology and social change. Routledge.

Gleick, J. (2011). The information: A history, a theory, a flood. HarperCollins.

Ong, W. J. (1982). Orality and literacy: The technologizing of the word. Routledge