I read a great article on LinkedIn by Ken Shelton. He looked at two articles:

“On one side:
AI as productivity infrastructure.
On the other:
AI as compliance enforcement.

But in both cases, the conversation centers on efficiency and policing, not on whether learning itself has been redesigned for an AI-rich world. Using historical context, one could reasonably make similar arguments around the implementation of technology as well. If students are learning to “sound human” to avoid detection…If institutions are investing in increasingly sophisticated surveillance tools…If teachers are primarily using AI to move faster within the same structures…Then we have to ask, as I have shared in previous posts:

Are we adapting learning?
Or are we simply optimizing and defending legacy systems?”

I found his article more interesting than the two he shared. I especially loved his final paragraph:

“The risk isn’t just that AI is moving too fast. The risk is that our response remains reactive, oscillating between efficiency and enforcement, without addressing purpose, power, and pedagogy. Therefore, the real inflection point isn’t technological, it’s analytical and philosophical.”

My thoughts: In education, go ahead and use AI to make teaching and lessons better, use it to help students learn, and also help them understand how to use AI to enrich their learning. But don’t use it to make learning easier. Real learning has a charge to it, it needs to come with some challenge, and hardship. If the learning experience is too easy, it won’t be remembered. If there isn’t enough challenge, if the answers are provided rather than constructed, the learning will soon be forgotten. Remove being stuck, struggling, and failure, and you’ve removed the greatest part of a learning experience.

So educators need to do two things: First, they need to use AI to make what they are doing even better. And secondly, they need to shift the learning experience to one where they no longer need to worry about policing and compliance. For example: The work isn’t finished with an essay, but with students defending their points in the essay against other students with slightly different points or different perspectives. The students who wrote the essay with AI and didn’t fully comprehend the topic can’t argue their perspective as well as the ones who were willing to do the work… and if they did use AI and can then argue the points better than their peers, that only proves that they understand how to use AI as a learning tool and not a tool to do the work for them. Because the real risk of AI in education is that the AI is doing the work, the struggle, and the learning for the student.

The problem we face is how learning can be circumvented by AI. And so the challenge for educators is to make it more challenging to use AI inappropriately, and to use AI to aid in making learning experiences more challenging. This is not an easy task, but it’s one we need to figure out and do well if we want our students to be learners who will have significance in a world where AI is all around us.

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Update: Just found this LinkedIn post by William (Bill) Ferriter, and it has two awesome images to fit with the above.

Update 2: I forgot about this post: Thinking Requires Effort

“Reducing busywork, and maximizing the problem-solving time, in a community of learners who find benefit from working together, is what schools should be in service of.“