We called them this because they used tools. The first proto-humans to clearly do so.
The question that we need ask ourselves today, “Are you a tool user or a tool maker?”
Everyone uses tools. But only a few people, even with access to AI and systems of leverage, choose to make tools.
Part of the gap is failing to ask the question. It generally doesn’t occur to a productive tool user to decide to slow down, risk failure, and take responsibility by making a new tool.
But new tools are one way we change things for the better.
Homo Faciens
If you have a phone, you can call anyone you like. The recipient doesn’t have to answer, but the network is an open API, available to anyone. The Bell System began as an actual networked system–many companies, using the same protocol, shared calls with each other. When Bell got greedy and stopped interconnecting, phone use became annoying–several phones on your desk, or there were simply people you couldn’t call. AT&T interconnected when it was finally more profitable to own the standard than to block it, and the government mandate then locked that in and led to the phone system we have now.
Email caught on and persisted for the same reason, but more so. There was never “the email company.” Instead, there’s a protocol, and anyone can send and receive. For free.
It’s hard to overstate how profound the idea of permission-less contact was to the flow of information and the growth of commerce and culture. Just as you could mail a letter to a stranger, you could also call or email them. When it works, it’s very powerful.
Friction was the key. Stamps cost money. Phone calls required an account and a human to dial.
The first real challenge for most users wasn’t crank calls or wrong numbers. It was spammers. Computer users who would send thousands or millions of emails or phone calls at a time, taking advantage of asymmetry. It cost them nothing, but it cost each recipient something.
Usenet, the original internet discussion layer, died from this asymmetry. No one had an incentive to create filters or clean it up at scale, so people stopped showing up.
Even with free email, the first generations of spam were mostly uneconomic, and much of it was stopped by filters. No one liked the noise, but email was useful enough that we put up with some spam.
Multiply spam by AI and the cloud and VOIP, though, and it’s obvious that open networks can’t survive. 30 junk SMS notices in one day is more than enough to turn off your notifications. How many voicemails about an approved business loan need to show up before the signal-to-noise ratio becomes simply noise?
We’re going to need to create a cost for the sender (so it can’t scale to ridiculous) as well as an identity layer (so scammers can’t be fully anonymous–reputation is earned, not invented). It might be an open protocol in the spirit of the best parts of the net, or it might be a single monopolist that figures out how to extract value from it.
A thousand years ago, people built walls around their villages because criminal marauders with nothing to lose would destroy open cities. The scale of the new digital marauding is going to be so large (and it’s coming so fast) that we’re about to see a fundamental shift in how we contact each other and who we trust.
I have no idea what it looks like on the other side of this transition, but the assumptions we’ve always made about open communication with strangers are about to change.
We have no idea.
Of course, there’s plenty of behavioral data. Say this phrase, or offer that treat, and this particular dog is likely to act in a certain way.
But our inclinations about what it’s actually like to be a dog are all inventions, reverse-engineered to give us a clue about what they might do next.
“If I were you,” is a pretty useless sentence, particularly for dogs. You’re not them, and you can’t imagine what it’s like.
The same is true for computers and for AI. We make up a story about what the computer wants, expects or thinks. But it’s simply a way to explain our guesses about behavior, not actually a statement about what it’s like to be that device or program.
You’ve probably already guessed (there I am, imagining what it’s like to be you) that the same is true for other humans. We only know for sure what it’s like to be ourselves. Everything else is speculation.
Empathy is essential, but it’s also difficult.
“Why are you taking this class?”
That seems like a fair question. After tenth grade or so, it’s a choice, after all.
One honest answer is, “I have to get a good grade to get to where I want to go.” That means certification, compliance, regurgitation. It means enrollment in the outcome, not the process. When this happens, we’re seeing a failure of the system we call education. Because that’s not learning.
One answer is, “Because I’m curious.” This is a great reason to take a class, and the instructor’s job isn’t merely to satisfy the curiosity; it’s to amplify it and turn it into a habit and the practice of the autodidact.
For many professional settings, the answer might be, “To learn how to use these tools and this insight to make a change in the world after I graduate.”
That sort of enrollment becomes a productive bargain. It gives the student agency–you don’t have to like everything the instructor has to say, you don’t have to use it when you leave, but the standard is: Is it helpful to imagine having this tool in your kit, and does this course prepare you to use the tool effectively?
Teaching is expensive, so is learning. Active enrollment on both sides is part of the bargain. Students are free to reject the pedagogy, the tools, even the aims of the current practitioners of a craft. But they’re on the hook to do that after they’ve absorbed what the instructor has to offer.
Take what you need and leave the rest.
Apophenia is the uniquely human tendency to perceive meaningful patterns or connections in random or unrelated data, events, or objects.
Humans are story telling machines. And one thing we do is turn co-incident events into more than coincidences.
When we see faces and shapes in clouds, apophenia wastes our time in the form of pareidolia. There isn’t actually a teddy bear in that cloud, or a face in that grilled cheese sandwich.
On the other hand, our ability to make out patterns is essential when trying to understand a system. Systems are nothing but non-coordinated conspiracies, individuals following their interests in response to a culture that is shaped by individuals following their interests.
The skill worth developing is the insight to tell them apart. Useful stories when needed, uncorrelated noise when there’s nothing actually going on.
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