The Machines Are Reading

Something strange showed up in my numbers this week.

A thousand visitors came through one of my pages in a single day. That’s more than I usually see in a month. For about an hour, I thought I’d struck gold.

Then I looked closer. Almost every one of those visitors read exactly one page and left. Not one of them stayed to look around. Not one of them signed up. A thousand people, and not a single one of them acted like a person.

So I checked the other counter I keep. That one filters out machines. It told me it had blocked 955 bot requests. Most of them announced themselves as bots right up front. They weren’t hiding. They came to read, and they made no bones about what they were.

That was the moment it sank in. The machines are reading what I write. Not someday. Right now. Every day.

I don’t know exactly which companies sent them. My counter doesn’t say. But I know what they look like, and I know what they’re for. These are the crawlers that feed the AI tools millions of people use. Some of them gather writing to train the machines. Some of them fetch pages on the spot, when somebody asks a question and the machine goes looking for an answer.

Either way, the result is the same. What gets written on the internet becomes what the machine knows. And what the machine knows becomes what it tells you.

When you ask an AI a question, the answer doesn’t come from nowhere. It comes from us. From the words people have put out into the world. Good words and bad words. Careful words and careless ones. Truth and nonsense, all poured into the same bucket.

The machine doesn’t know the difference on its own. It learns from what it’s fed. If it’s fed honest writing, it has a fighting chance at honest answers. If it’s fed junk, it serves junk back to you with a straight face.

We talk a lot about whether we can trust the machine. We don’t talk much about whether the machine can trust us.

Every one of us is part of the record now. Every review you write. Every post you share. Every comment you leave in anger at midnight. Somewhere, some crawler may be reading it. And some day, some piece of it may come back to somebody else as an answer.

That’s a responsibility none of us asked for. But we have it anyway.

I’m telling you because I think it’s one of the most important things a regular person can understand about AI right now. You aren’t just a user. You’re a teacher. Whether you like it or not, you’re helping shape what these machines say.

what do we do with that?

The first thing is simple. Write like it matters. Because it does. When you put something out in public, say what you know and say where you got it. Mark your guesses as guesses. Admit what you’re not sure of. That’s good manners with people. It turns out it’s good practice for the machines, too.

The second thing is to be careful what you pass along. A lot of what spreads online is wrong. Some of it is wrong on purpose. When you share it, you’re not just fooling your friends. You’re adding weight to the pile the machines learn from. Every false thing repeated becomes a little more likely to come back as an answer.

The third thing is the one I keep coming back to. Hold the machine to account when it answers you. Ask it what its answer rests on. Ask it what it can’t do. Ask it if what it’s telling you can be undone. If the answer came from a bad source, those questions are how you’ll catch it.

That’s the circle,we feed the machines. The machines feed us. If nobody in the middle is checking, the bad stuff goes around and around and gets louder every time. But if regular people start checking, the circle starts to clean itself. One honest question at a time.

I’ll tell you how this changed my own thinking. For a long time I measured my work by how many people read it. That’s the number everybody watches. Views, visitors and clicks. But this week showed me that a whole new kind of reader is out there. One that never clicks a button, never leaves a comment and never says thank you.

And that reader might carry my words further than any person ever could.

That’s humbling. It also makes me want to be more careful. If the machines are going to learn from what I write, I want them to learn something true. I want them to learn that a person can be held to a standard and should be. That evidence matters. That limits should be named out loud. That a confident voice isn’t the same thing as a right answer.

If even a little of that gets into the bucket, it was worth writing.

The next time you post something, picture two readers. One is your neighbor. The other is a machine that will remember every word and may repeat it to a stranger years from now. Write for both of them. Be honest enough for the neighbor and careful enough for the machine.

And the next time a machine answers your question, remember where that answer came from. It came from all of us. Which means all of us have a hand in making it better.

The machines are reading. Let’s give them something worth learning.

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This post was drafted with AI governed assistance and reviewed and directed by Michael S. Faust Sr. before publication.

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