Validated by the Machine

I didn’t plan to write this, but sometimes the world hands you the perfect example of what you’ve been trying to explain.

Yesterday I published The Classroom I Needed, criticizing universities for banning AI in classrooms instead of teaching students how to use it wisely. The irony arrived the next morning: a message from a recruiter at ASU’s W. P. Carey School of Business inviting me to apply for their MBA program.

I could almost hear the algorithm grinning.

At first, I felt irritated — maybe even mocked. The same institution that forbids students from using AI had just used AI to find me. But after a few hours, irritation gave way to something closer to clarity.

This was validation.

Not of my ego, but of my argument. The machine didn’t “read” my blog — it proved it. AI is already in the bloodstream of our institutions, quietly doing the work we pretend to resist.

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The Contradiction That Teaches

I used to see moments like this as hypocrisy. Now I see them as paradox. The contradiction isn’t evidence of deception — it’s evidence of transition, as institutions try to reconcile what they say about AI with how they already use it.

We’re caught between fear of losing control and faith that technology might make us better thinkers. And that’s the quiet gift of AI: it gives us a place to think out loud without fear of ridicule — to test ideas before exposing them to the noise of the crowd. For me, that space has become a kind of intellectual rehearsal hall, one where I can stretch, stumble, revise, and grow.

The recruiter’s message reminded me that rejecting AI outright isn’t the answer. The answer is discernment. We can acknowledge the worst parts — bias, automation without empathy, the easy slide into dependency — while still taking advantage of the best: speed, pattern recognition, and the ability to surface what humans might overlook.

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Learning From the Machine

If education is about learning to think, then AI should be part of the classroom, not banned from it. Students should be taught to challenge AI, not fear it — to ask, Why did the model choose this? What assumptions is it making? How would I rewrite its answer?

That’s how you turn a tool into a teacher.

So yes, when ASU’s algorithm selected me, I laughed. Then I nodded. Because this is what I’ve been saying all along: the future isn’t coming — it’s already here, politely sending invitations through LinkedIn.

And the right response isn’t outrage. It’s curiosity.

Closing Thought

This small exchange with ASU felt like a glimpse into the larger story I’ve been trying to tell in Fear, Faith, and the Future. Every contradiction, every irritation, every moment of surprise reminds me that progress is rarely neat. It arrives awkwardly, unevenly, and sometimes with a wink from an algorithm. What matters most isn’t whether we fear or worship the machine—but whether we stay curious enough to learn from what it’s teaching us about ourselves.