We should all be frustrated pragmatists

Regarding AI in education, I noticed that two separate camps starting to train.

Camp 1: Pragmatists

The first camp is made up of teachers, school leaders and consultants who focus on how AI can support the daily work of educators. These are the pragmatists. Those who use AI to reduce the workload of teachers, automate repetitive tasks, rationalize the evaluation and unlock additional time in increasingly stretched hours. They see AI as a way to improve the current system. In a global context of shortages of teachers, low morale and professional exhaustion, their objective is practical and, I would say, noble.

Camp 2: The frustrated

The second camp sees things differently. For them, AI should not be a tool to help us do what we have always done, only faster or more effectively. It is a transformative force. This group believes that the real potential of AI lies in its power to reinvent education. They are frustrated that education has not already changed and wants AI to be the spark that ignites the revolution. They want to go beyond increasing improvements and in daring redesign: new learning models, new evaluation systems and new education structures. They ask the big questions about the relevance, the goal and the future of education.

Over the past two years, I have noticed a subtle but increasing tension between these two perspectives. The second camp sometimes looks at the first, as if the use of AI to help planning or notation of lessons was somehow pedestrian, even counterproductive to a real innovation. As if something less in systemic transformation was not worth talking.

I think it’s a mistake.

Because the truth is, the two perspectives are necessary. The answer is not / or. It is both / and.

I am a frustrated pragmatist.

The frustrated pragmatist

In 2022, I wrote an article referring to the three -box solution to innovation, a model developed by Professor Vijay Govindarajan of the Tuck School of Business of Dartmouth College. I adapted and applied it to education. I then developed in my book The Ai Classroom, and even more deeply in my last book, Infinite Education. This framework offers one of the most useful objectives through which IA tackle in education. A perspective that honors both current practicality and long -term reinvention.

Basically, the model divides innovation into two key categories: linear and non -linear.

Do what we do better

Linear innovation is to optimize and improve what already exists. It is evolving, not revolutionary. It improves the current system. This can make schools more effective, help teachers manage workloads and release time to focus on what matters most.

AI is incredibly effective in this space. It can support lessons planning, generate differentiated materials, summarize evaluation data, automate comments and help communication and reports. These are not small improvements. In many schools, they change the situation.

While I work with educators from around the world, I see the excitement, relief and even joy from the discovery of the discovery of AI tools that make their lives. These teachers do not seek to revise the system, they simply try to do their job well and get some breathing margin in the process. And when AI helps them get there, it is not a “false” innovation. These are real and significant progress.

Who are we to say that it is not valid?

Who are we to reject these tools as unimportant or without imagination? This kind of thought is condescending and it is inaccurate.

Linear innovation may be the first step, but it is vital. Especially in a profession that has been pushed to its limits, finding new ways to support educators in their existing work is not a distraction of innovation. It is the foundation of this one.

But we cannot allow ourselves to stop there either.

Ask the biggest questions

Non -linear innovation does not seek to make the current system more effective, but to question it. He asks: What if the way we have always done things no longer make sense? What if there is a better model?

This kind of thought becomes crucial when new technologies arrive that do not only make old systems, but have the potential to make them obsolete. AI is one of these technologies.

For decades, education has been projected with real disturbances. Schools have existed in protected ecosystems, relatively intact by market forces or external competition. But with AI, it changes. For the first time, we see the emergence of powerful learning alternatives. Chatgpt applications that teach mathematics, schools fueled by AI and Tutors entirely in AI.

It is the real disruptive force of AI. It is not only that it automates existing processes. It presents competition at a level never seen before.

When students can access personalized and high quality learning from anywhere, at any time and little or not, schools must start asking:

• Why do we exist?
• What value do we provide that no AI system can reproduce?
• What is our deeper goal in a world where the content is infinite, and the instruction is on demand?

As I recently said on the Podcast of Joining The Dots, AI is not the ultimate objective of education; It is the lever to conduct an essential systemic reform. This is not the destination. He is the creator of Élan. The accelerator. The big boost we need to rethink the objective, design and delivery of education.

This is why I wrote an infinite education. Not just to explore AI class applications, but to provide a gaming book for non -linear innovation. A guide for schools that seek to evolve before being forced to do so.

Balancing now and next

This dual linear and non -linear innovation course requires a new type of leadership. A good leadership balances the linear and the non-linear. He manages the present while contesting his shelf life. It supports existing systems while creating new ones. It contains space for safety and disturbance.

In education, the time has come for managerial and heretical leaders. Managerial leaders maintain the functioning of the system. They maintain stability, operations, security and responsibility. Their work is essential. But we also need heretical leaders. Those who dare to imagine something different. Those who ask uncomfortable questions. Those who are not afraid to disturb their own hypotheses. These leaders are often faced with resistance, but they are the ones who advance the system.

The real educational innovation in the AI ​​era requires both types of leadership. No one is enough.

Integration, not division

So rather than choosing sides. Rather than dividing ourselves into camps, we have to choose integration.

Let’s build a culture that appreciates the two types of innovation:

Tools that help us survive today and visions that help us invent tomorrow.

Let us honor teachers using AI to recover time and energy and support those who dream of systems not yet built.

Let us stop drawing lines and start to build bridges between the present and the following, the practice and the possible, the performance engine and the innovation laboratory. Because if we can do it, we don’t only adapt to AI. We direct with it.

This is the type of education system that the future needs.