Journal tags: agency

One persistent piece of slopaganda you’ll hear is this:

“It’s just a tool. What matters is how you use it.”

This isn’t a new tack. The same justification has been applied to many technologies.

Leaving aside Kranzberg’s first law, large language models are the very antithesis of a neutral technology. They’re imbued with bias and political decisions at every level.

There’s the obvious problem of where the training data comes from. It’s stolen. Everyone knows this, but some people would rather pretend they don’t know how the sausage is made.

But if you set aside how the tool is made, it’s still just a tool, right? A building is still a building even if it’s built on stolen land.

Except with large language models, the training data is just the first step. After that you need to traumatise an underpaid workforce to remove the most horrifying content. Then you build an opaque black box that end-users have no control over.

Take temperature, for example. That’s the degree of probability a large language model uses for choosing the next token. Dial the temperature too low and the tool will parrot its training data too closely, making it a plagiarism machine. Dial the temperature too high and the tool generates what we kindly call “hallucinations”.

Either way, you have no control over that dial. Someone else is making that decision for you.

A large language model is as neutral as an AK-47.

I understand why people want to feel in control of the tools they’re using. I know why people will use large language models for some tasks—brainstorming, rubber ducking—but strictly avoid them for any outputs intended for human consumption.

You could even convince yourself that a large language model is like a bicycle for the mind. In truth, a large language model is more like one of those hover chairs on the spaceship in WALL·E.

Large language models don’t amplify your creativity and agency. Large language models stunt your creativity and rob you of agency.

When someone applies a large language model it is an example of tool use. But the large language model isn’t the tool.

Clearleft turned fifteen this year. We didn’t make a big deal of it. What with The Situation and all, it didn’t seem fitting to be self-congratulatory. Still, any agency that can survive for a decade and a half deserves some recognition.

Cassie marked the anniversary by designing and building a beautiful timeline of Clearleft’s history.

Here’s a post I wrote 15 years ago:

Most of you probably know this already, but I’ve joined forces with Andy and Richard. Collectively, we are known as Clearleft.

I didn’t make too much of a big deal of it back then. I think I was afraid I’d jinx it. I still kind of feel that way. Fifteen years of success? Beginner’s luck.

Despite being one of the three founders, I was never an owner of Clearleft. I let Andy and Rich take the risks and rewards on their shoulders while I take a salary, the same as any other employee.

But now, after fifteen years, I am also an owner of Clearleft.

So is Trys. And Cassie. And Benjamin. And everyone else at Clearleft.

Clearleft is now owned by an employee ownership trust. This isn’t like owning shares in a company—a common Silicon Valley honeypot. This is literally owning the company. Shares are transferable—this isn’t. As long as I’m an employee at Clearleft, I’m a part owner.

On a day-to-day basis, none of this makes much difference. Everyone continues to do great work, the same as before. The difference is in what happens to any profit produced as a result of that work. The owners decide what to do with that profit. The owners are us.

In most companies you’ve got a tension between a board representing the stakeholders and a union representing the workers. In the case of an employee ownership trust, the interests are one and the same. The stakeholders are the workers.

It’ll be fascinating to see how this plays out. Check back again in fifteen years.