“In the beginner's mind there are many possibilities, but in the expert's there are few.”
Shunryu Suzuki, Zen Mind, Beginner's Mind
I have been thinking about artificial intelligence while reading Zen Mind, Beginner's Mind by Shunryu Suzuki.
When I open ChatGPT or Claude, I meet a largely empty screen. A text box waits for a prompt. I can arrive with a finished request, an unfinished thought, or only the sense that there is something I want to understand better.
Suzuki's idea offers a useful way to think about that space.
Beginner's mind is an attitude of openness. It keeps possibility alive before habit and certainty narrow the field. I can use that interface as an unusual place to practise that attitude.
The beginner's mind in this relationship belongs to the person sitting in front of the screen.
An empty screen connected to an enormous amount of prior learning
The screen looks almost empty. Behind it sits a language model shaped by patterns learned from large amounts of existing information. OpenAI describes large language models in similar terms: they learn patterns from large amounts of data and use those patterns to generate responses.
I am beginning with an open space while using a tool shaped by an enormous amount of what people have already written, explained, argued, and recorded.
I can bring the tool a question before I know exactly how to ask it. I can bring a half-built argument. I can test whether two ideas belong together. I can ask what I may be overlooking. I can change direction halfway through the exchange.
The first question can remain only a starting point.
That matters because unfinished thinking can be difficult to expose to other people.
Human conversations carry relationships, history, status, time, and expectations. Those things are valuable. They are part of what gives human conversation its depth. Those relationships also shape what we are willing to say while an idea is still forming. Sometimes the honest version is simple. I have an idea, and I'm still figuring out whether it makes sense.
With AI, I can stay with that unfinished thought for a while. I can explore it before I decide whether it deserves another person's time.
For me, that creates a different kind of thinking space.
A polished answer can close the question too soon
The same experience can also narrow a question quickly.
Within seconds, I can prompt a language model and receive a fluent answer. The answer may be useful, and it may sound complete. Fluency can make a provisional answer feel settled before I have done enough thinking of my own.
The beginner's-mind question then becomes very practical: what do I do after the first answer appears?
I can accept it and continue with my day. I can also stay curious.
I can ask another question. I can challenge an assumption. I can ask for another way to see the issue. I can read a source and discover that my original idea was too broad. I can decide that the first answer was useful only because it showed me a better question.
I use the tool to gather material to consider. I decide how long the question stays open.
At that point, beginner's mind becomes a practical way of using the tool.
This matters in K-12 communication work
K-12 communication brings together words, context, judgement, and relationships.
A message can involve history, timing, local facts, previous decisions, uncertainty, and an understanding of how people may interpret what they receive. The person doing the work brings that context.
AI can support parts of the thinking. You can use it to test whether an explanation is missing a step. You can compare different ways to organize a message. You can ask what questions a community member may still have after reading it.
You still bring the purpose. You know the people and the history around the situation. You decide which facts matter. You judge whether a suggestion fits the reality in front of you. You remain responsible for what you communicate.
I see that relationship as additive. I already have colleagues, friends, books, research, experience, and conversations that shape how I think. AI has become another place where I can work with an idea.
A colleague can tell me what experience has taught them. A friend can understand the personal history behind a question. A book can take me deeply into another person's thinking. A research paper can give me evidence that changes my view.
I can use AI to bring those influences together, question the connections I am making, and keep working before I decide what I think.
We get to have both
Human interaction remains the richer part of my life.
If I could choose only one for the rest of my life, I would choose conversations and relationships with other people every time. They carry experience, emotion, responsibility, memory, humour, disagreement, care, and stakes that matter because real people are involved.
We get to live with human relationships and AI in the same world.
That feels worth exploring.
Over the coming months, I am going to write more about AI and its relationship with K-12 communication. I want to look at what happens to thinking, creativity, judgement, learning, efficiency, and professional responsibility when AI becomes part of the way we work.
I am especially interested in the human side of that relationship.
Suzuki's sentence gives me a useful place to start. Conversational AI can draw on a remarkable breadth of learned patterns. Beginner's mind asks us to keep the question open long enough to explore beyond the first answer.
For me, using AI with a beginner's mind means treating that open possibility as part of the value.