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The Wonderful Wizarding World of Artificial Intelligence

The Wonderful Wizarding World of Artificial Intelligence

Last updated on: February 25, 2026 at 1:10 pm by James F. McGrath

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The Wonderful Wizarding World of Artificial Intelligence 2026-02-25T13:10:37-05:00 James F. McGrath

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AI can seem like magic. I have used the analogy of “showing how the magic trick is done” to refer to what I try to do when I explain the technology. Once you understand the magic trick, it will no longer seem like magic ever again. You can still find the illusion impressive, but you aren’t fooled by it.

That’s what is needed right now, when too many fall for the illusion that a chatbot that can play the game of human language must be capable of the same kind of thought that leads humans to produce language. But it is no more true in the case of language than in the case of chess or Go.

Einstein

The latest bit of “magic” that AI is bringing into our worlds is called Einstein. The name is ironic, since one imagines that the human Einstein would not be working to have learners avoid the tasks that foster learning. That’s what Einstein does. It is literally marketed to students as a tool to avoid doing coursework yourself.

I think there are a number of things that universities can and should do immediately in response to this.

Inform students that while use of this in an individual course might only risk failing that course, the use agreement for the university LMS requires them to not share their password or give others access. Use of this or other agentic AI to have it log in on their behalf is thus a violation that will lead to automatic expulsion.
Work out the IP address(es) used by this and other such agentic bots and both block them and monitor for them.
Work out behavior characteristics of agentic AI bots on platforms and work with providers to detect these.
Incorporate assessments into online courses that AI performs poorly on, just as we have been doing in our face to face classes.

It is not “merely” student learning that is at risk from this technology. Students who use it put the entire university or school at risk with respect to data security.

For educators rather than those in IT, the last point is the most crucial. Just because AI agents can log into Canvas, Moodle, or Blackboard does not suddenly make them better capable of doing student work than chatbots are without the agentic features.

One article about this technology asks what the point of homework is if AI can do it for you.

I’m glad you asked. That’s the key question.

We need to make sure that students understand the point of homework. When I get students on board with the importance of what they will get from an activity, they generally take it seriously. Often we assume it is clear why we are asking them to read something and then quiz them on it. It is not clear, unless we make it clear. Just as AI can seem like magic, so too can education. We often fail to pay attention to how we learn, what activities foster learning.

Harry Potter

Engaging with Harry Potter or any other really well known fiction can help students understand a couple of points. To pick up where we left off in the previous section, why read a novel like Harry Potter? When they read it on their own, the answers include because everyone else is (at least the first time), for enjoyment, and because fiction helps us think about aspects of life such as friendship, and the values that lead us to behave in certain ways and become certain kinds of people.

Nowadays you can drop a pdf of Harry Potter into NotebookLM and get a summary. Why not just do that? Those novels are long. NotebookLM can sum it all up in a podcast or an infographic like this one:

A thought experiment like this (or getting students to actually try out NotebookLM) can help students understand that there is a powerful tool that is really helpful when needed, but one that it would make sense to use on everything.

The point is not that the summaries tend to be bad as summaries. They are regularly very good, by any measure. The point is that summaries are not always an adequate substitute for the real thing, for the full details of an article or book.

We sometimes mislead students, quizzing them on plot points in an attempt to ensure they do the reading. That merely teaches them to try to memorize the SparkNotes version to prepare for the quiz. The point of reading literature, however, is to experience it, to lose oneself for a time in the imagined world.

AI can seem like magic, and I find NotebookLM particularly impressive. (Check out a podcast summary of my book Real Intelligence: Teaching in the Era of Generative AI for an example if you’ve never used it.) It is only by reading Harry Potter, and not merely relying on a summary, that you’ll understand that just because there’s a powerful spell available, it doesn’t mean you should use it all the time, if ever.

Do Your Homework

A recent survey indicated that, while many teens use AI when working on their homework, it is only around 10% who give in to the temptation to have it do the whole thing for them. Even if one considers how many students use it that way at least occasionally, the statistics suggest that it is a comparable problem to what it was before generative AI.

That’s important. Most students want to learn. AI hasn’t changed that. Misunderstanding of AI is certainly a contributor, but that’s true among educators as well as students.

I would say that the biggest issues at the moment are on the side of educators. I see this time and time again in the toxic /r/Professors subreddit, which is almost as disheartening as the r/ChatGPT subreddit.

A lot of educators have not taken the time to inform themselves about AI. No need to learn how to code any more than you need to understand catalytic convertors in order to be able to drive a car. I am referring to the kind of understanding that users need, not the kind required to create the thing (whether software or mechanical).
A lot of educators are creating a toxic learning environment by approaching students with the suspicion that they are all lazy and will cheat if possible.
Many educators are taking the unethical step of using so-called AI detectors even though they are a black box and have been shown to generate false positives.
Too many educators are not taking the time to redesign assessments and courses to work in the context of current technology.

The solutions are before us.

Understand the technology, so that you can help students understand what it is good for and what it is not.
That is what they need by way of preparation for the future of work. Design assignments that make it very likely that students will either do the work they are required to themselves, or otherwise fail (or at least get a poor grade).
Build an environment of trust where the rationale for what they are learning and for assessments are understood.

AI can seem like magic, and many professors are cowering like muggles facing off against technology that must not be named. There’s no sorcery, even in technology that promises to do homework for you. Yet in a sense there is a battle going on, just as one might imagine to happen between a good and evil wizard, or between healthy and toxic religion. This technology doesn’t pose an inherent threat to those who understand the value of learning, or to those who understand why AI outputs cannot be assumed to be correct. The danger, as with all technology, is with those who misuse it deliberately, and with those who misunderstand it and use it unwisely and unethically.

What my colleague Ankur Gupta and I tried to offer in our book Real Intelligence is essentially defense against the dark arts (to continue the analogy). But the most powerful protection you have is the knowledge that although AI can seem like magic, there is no real magic at work. Even when it can generate a handy infographic like the one below from our book, you can understand how it is done. And if you paid attention to this post, you’ll know that this summary does not nearly do justice to what the book as a whole offers.

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