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.”

The value is in the difficulty - Annotations

We’ve seen this arc before, and music is the richest analogy.

Like Bruce Sterling always says:

Whatever happens to musicians happens to everybody.

Expansion artifacts || Matt Ström-Awn, designer-leader

Compression made the information age possible by stripping things down to fit the pipes. Expansion made the AI age possible by blowing data back up again. Both operations leave marks; we’ve learned to spot compression artifacts, but we’ve only just begun to reckon with expansion artifacts. Until we do, there’s a lot of risk to manage.

AI Might Be Our Best Shot At Taking Back The Open Web | Techdirt

Not sure I buy the argument here, though I do very much look forward to local language models getting better so we can ditch the predatory peddlars of today’s slop. But this trip down memory lane to the early web of the 1990s could’ve been describing my own experience:

But the thing I do remember was the first time I came across Derek Powazek’s Fray online magazine. It was the first time I had seen a website look beautiful. This was without CSS and without Javascript. I still remember quite clearly an “issue” of Fray that used frames to create some kind of “doors” you could slide open to reveal an article inside.

Fray was what made me want to make websites:

I distinctly remember sites like prehensile tales, 0sil8 and the inimitable Fray triggering something in my brain that made me realise what it was I wanted to do with my life.

I used AI. It worked. I hated it.: Taggart Tech

There’s a fundamental problem with these tools beyond the capacity of any deployment strategy to solve: the tool requires expertise to validate, but its use diminishes expertise and stunts its growth. How does one become an expert? There are no shortcuts; there is only continuous hard work and dedication. I was once told of writing, great writers learn how to break the rules in new and ingenious ways by first learning the rules.

But how is a new developer meant to learn the rules if their day-to-day work is nothing but the babysitting of models? How will they gain the hard-won experience that allows a human in the loop to be a useful safeguard?

These models alter cognition in ways deleterious to human prosperity. In other words, for as much output as they provide, they take something important from us.

Gas Town and Bullet Hell – Petafloptimism

Matt has some smart reckons on the relationship between time and technology:

The factory bell, the railway timetable, the telegraph wire, the always-on smartphone — each imposed a new temporal discipline, each produced its own characteristic form of exhaustion, and each was eventually (partially, imperfectly) domesticated through a combination of regulation, design, and collective action.