You can call me AI

I’ve mentioned before that I’m not a fan of initialisms and acronyms. They can be exclusionary.

It bothers me doubly when everyone is talking about AI.

First of all, the term is so vague as to be meaningless. Sometimes—though rarely—AI refers to general artificial intelligence. Sometimes AI refers to machine learning. Sometimes AI refers to large language models. Sometimes AI refers to a series of if/else statements. That’s quite a spectrum of meaning.

Secondly, there’s the assumption that everyone understands the abbreviation. I guess that’s generally a safe assumption, but sometimes AI could refer to something other than artificial intelligence.

In countries with plenty of pastoral agriculture, if someone works in AI, it usually means they’re going from farm to farm either extracting or injecting animal semen. AI stands for artificial insemination.

I think that abbreviation might work better for the kind of things currently described as using AI.

We were discussing this hot topic at work recently. Is AI coming for our jobs? The consensus was maybe, but only the parts of our jobs that we’re more than happy to have automated. Like summarising some some findings. Or perhaps as a kind of lorem ipsum generator. Or for just getting the ball rolling with a design direction. As Terence puts it:

Midjourney is great for a first draft. If, like me, you struggle to give shape to your ideas then it is nothing short of magic. It gets you through the first 90% of the hard work. It’s then up to you to refine things.

That’s pretty much the conclusion we came to in our discussion at Clearleft. There’s no way that we’d use this technology to generate outputs for clients, but we certainly might use it to generate inputs. It’s like how we’d do a quick round of sketching to get a bunch of different ideas out into the open. Terence is spot on when he says:

Midjourney lets me quickly be wrong in an interesting direction.

To put it another way, using a large language model could be a way of artificially injecting some seeds of ideas. Artificial insemination.

So now when I hear people talk about using AI to create images or articles, I don’t get frustrated. Instead I think, “Using artificial insemination to create images or articles? Yes, that sounds about right.”

Every Reason Why I Hate AI and You Should Too

If I were to photocopy this article, nobody would argue that my photocopier wrote it and therefore can think. But add enough convolutedness to the process, and it looks a lot like maybe it did and can.

In reality, all we’ve created is a bot which is almost perfect at mimicking human-like natural language use, and the rest is people just projecting other human qualities on to it. Quite simply, “LLMs are doing reasoning” is the “look, my dog is smiling” of technology. In exactly the same way that dogs don’t convey their emotions via human-like facial expressions, there’s no reason to believe that even if computer could think, it’d perfectly mirror what looks like human reasoning.

The sound of inevitability | My place to put things

People advancing an inevitabilist world view state that the future they perceive will inevitably come to pass. It follows, relatively straightforwardly, that the only sensible way to respond to this is to prepare as best you can for that future.

This is a fantastic framing method. Anyone who sees the future differently to you can be brushed aside as “ignoring reality”, and the only conversations worth engaging are those that already accept your premise.

The Imperfectionist: Navigating by aliveness

Most obviously, aliveness is what generally feels absent from the written and visual outputs of ChatGPT and its ilk, even when they’re otherwise of high quality. I’m not claiming I couldn’t be fooled into thinking AI writing or art was made by a human (I’m sure I already have been); but that when I realise something’s AI, either because it’s blindingly obvious or when I find out, it no longer feels so alive to me. And that this change in my feelings about it isn’t irrelevant: that it means something.

More subtly, it feels like our own aliveness is what’s at stake when we’re urged to get better at prompting LLMs to provide the most useful responses. Maybe that’s a necessary modern skill; but still, the fact is that we’re being asked to think less like ourselves and more like our tools.

The Recurring Cycle of ‘Developer Replacement’ Hype

Here’s what the “AI will replace developers” crowd fundamentally misunderstands: code is not an asset—it’s a liability. Every line must be maintained, debugged, secured, and eventually replaced. The real asset is the business capability that code enables.

If AI makes writing code faster and cheaper, it’s really making it easier to create liability. When you can generate liability at unprecedented speed, the ability to manage and minimize that liability strategically becomes exponentially more valuable.

This is particularly true because AI excels at local optimization but fails at global design. It can optimize individual functions but can’t determine whether a service should exist in the first place, or how it should interact with the broader system. When implementation speed increases dramatically, architectural mistakes get baked in before you realize they’re mistakes.

Toolmen | A Working Library

Engaging with AI as a technology is to play the fool—it’s to observe the reflective surface of the thing without taking note of the way it sends roots deep down into the ground, breaking up bedrock, poisoning the soil, reaching far and wide to capture, uproot, strangle, and steal everything within its reach. It’s to stand aboveground and pontificate about the marvels of this bright new magic, to be dazzled by all its flickering, glittering glory, its smooth mirages and six-fingered messiahs, its apparent obsequiousness in response to all your commands, right up until the point when a sinkhole opens up and swallows you whole.

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