I have spent much of my career thinking about technology and education. I earned a degree in educational technology, have facilitated professional learning around technology, and have always been an early adopter. I am usually one of the first people to download a new platform, experiment with new software, or try a new gadget to see what it might make possible for teaching and learning.
The funny thing is that many of the technologies I learned about earlier in my career are now obsolete. Others have been replaced by tools we could not have imagined at the time.
What has remained remarkably consistent is good instructional design.
The tools change. The platforms change. The possibilities change. Yet, as educators, we eventually find ourselves returning to the same fundamental question:
What do students actually need to learn?
AI has made that question both more urgent and more complicated.
Much of the conversation about AI in education has understandably focused on what the technology can do. Can it write an essay? Solve a problem? Analyze a text? Create a presentation? Summarize an article? And, of course, can students use it to avoid doing the work we have assigned them?
Those are legitimate questions.
But I think there is a more important one underneath them:
What is worth learning even when AI can do it for us?
The Product Is Not Always the Point
As an English teacher, department chair, and professional learning facilitator, I think about this constantly.
AI can produce an essay. It can generate a thesis, suggest evidence, summarize a text, organize an argument, revise sentences, correct grammar, and create a polished final product.
So, does that mean students no longer need to learn to write?
I don't think the answer is that simple.
Because when I teach students to write, the essay is not the only thing I am teaching them to produce.
Writing requires students to figure out what they think.
They encounter ideas. They wrestle with them. They decide whether they agree. They push back. They extend someone else's thinking. They search for evidence. They make connections. Sometimes they discover that the idea they started with doesn't quite hold up, so they revise it.
Then they have to communicate that thinking clearly enough for someone else to understand.
The essay may be the product.
But thinking is part of what we are developing through the process.
AI's ability to produce the product does not necessarily eliminate the human need for the process.
That distinction matters.
What Are We Really Teaching?
The more I think about AI, and I find myself thinking about it more every day, the more it pushes me back toward questions I have been asking throughout my career.
When students leave my classroom, what do I actually want them to know and be able to do?
Who do I want them to become?
I teach English Language Arts, and I lead a department of educators who teach it. We teach reading and writing, but those labels don't fully capture what I hope students are learning in our courses.
I want them to be able to encounter an idea and think deeply about it.
I want them to read and listen closely enough to understand what someone else is saying before deciding what they think about it.
I want them to question ideas, challenge them, extend them, connect them to something else, and sometimes change their minds when they encounter information that challenges their initial claims.
I want them to recognize weak reasoning and distinguish it from an argument that is well supported.
I want them to communicate what they think through writing and speaking.
I want them to listen to each other.
I want them to work with other people.
I want them to develop empathy and consider perspectives beyond their own.
I want them to think about their thinking and develop the capacity to share those thoughts confidently with others.
Ultimately, I want them to leave our classrooms better prepared to participate thoughtfully in the world as critical thinkers, problem solvers, communicators, global citizens, and kind, decent human beings.
Those capacities extend far beyond an English classroom.
Perhaps that is why the arrival of AI doesn't make me want to abandon the fundamentals of what we teach. It makes me want to examine them more carefully.
“Can AI Do It?” Is the Wrong Test
There is a temptation to divide learning into two categories: things humans can do and things AI can do.
But I don't think that distinction will serve us for very long.
AI can already perform tasks we have traditionally considered worth learning, and its capabilities will continue to change.
So the question cannot simply be:
Can AI do this?
A better question might be:
Even if AI can do this, what does a human still need to understand, practice, experience, or be capable of doing for themselves?
We have encountered versions of this question before.
Calculators can perform arithmetic, but students still need enough mathematical understanding and number sense to reason quantitatively and recognize when an answer doesn't make sense.
GPS can tell us where to turn, but following directions is not the same as understanding where we are.
Search engines can retrieve enormous amounts of information in seconds, but retrieving information is not the same as understanding it, evaluating it, or knowing what to do with it.
The existence of the tool did not make the underlying human understanding irrelevant.
Instead, technology changed the relationship between what we needed to know and do ourselves and what we could reasonably ask a tool to do for us.
AI requires us to examine that relationship again. This time, however, the questions reach much further into the processes of thinking, creating, communicating, and learning.
That is where I believe educators have important work to do.
We Need to Learn Alongside Our Students
I don't believe our responsibility is to protect education from AI. I'm not convinced that is even possible.
AI is already part of the world our students inhabit. They are using it, sometimes thoughtfully and sometimes not, regardless of our attempts to prohibit, restrict, detect, or control it.
That does not mean anything goes.
Nor does it mean our job is to embrace every new AI tool simply because it exists.
It means we need to learn.
We need to experiment.
We need to pay attention to what these technologies make possible, where they genuinely improve learning, where they interfere with it, and what they reveal about practices we may have taken for granted.
And we may need to figure some of this out alongside our students.
The technology is developing too quickly for educators to wait until someone else has determined all the answers, packaged them into a professional development session, and handed us the official set of instructions.
That pace of change can feel unsettling. However, I also find it intellectually exciting.
AI gives us an opportunity to reconsider not only how we teach, but what education is ultimately for.
Start With Reflection
That feels like an enormous question.
So perhaps we don't begin by redesigning education.
Perhaps we begin by reflecting on our own instructional practice.
Reflection has been central to my practice for years. Long before AI entered this conversation, I believed that educators grow by deliberately examining what we are doing, what our students are experiencing, what we are learning from the results, and what we might do differently the next time.
We plan. We teach. We observe what happens. We listen to students. We look at what they produce. We think about what worked, what didn't, and what we might change.
Then we go back in and try again.
AI doesn't make that cycle less important.
If anything, I think it makes reflection more necessary.
Before asking which AI tool we should use or whether students should be allowed to use it, we can begin with something more fundamental:
What do I want my students to know, understand, and be able to do long after they have left my classroom?
And perhaps:
Who do I hope they are becoming through the process?
Then:
Which parts of the learning experience are essential to developing those capacities?
Only then can we ask better questions about AI.
Where can it extend the learning?
Where might it interfere with the learning?
What can it reasonably do for students?
What must students still experience and practice for themselves?
And what might AI allow teachers and students to do that we could not do before?
I don't have definitive answers to all of those questions.
I don't think any of us does yet.
But after decades of technological change in education, I find something almost reassuring about where AI has brought me.
Back to the same question I have been asking all along:
What is worth learning?
The technology will keep changing.
Our responsibility to wrestle thoughtfully with that question should not.