Tags: automation

Flood fill vs. the magic circle

Eleven years ago, I wrote:

Sometimes I consider the explosive growth of computation and think that strong AI is a near-term inevitability.

Then I remember printers.

That was just a brainfart, but Robin tackles it seriously in his thoughtful essay.

A pleasing image: if indeed AI automation does not flood fill the physical world, it will be because the humble paper jam stood in its way.

Software cannot, in fact, eat this world. Software can reflect it; encroach upon it; more than anything, distract us from it. But the real physical world is indigestible.

I am in an abusive relationship with the technology industry

The cognitive overload of AI trying to Make You More Productive™️ whilst you’re actually trying to be productive is so shockingly absurd. And yet, we are being made to feel like we are stagnating, being left behind, not good enough, that we are luddites should we not adopt this imposing technology. We are being told we’re missing out, even though we’re probably doing just fine. The technology is gaslighting us.

The Artisanal Web | Another Rodeo

I feel very seen here. This describes how I built The Session:

There are still people building the web by hand, very much like we did it in the early days. They know all about what’s possible using modern tooling, yet they choose to expend their time and attention to the craft of doing it by hand. They care about the craft, and they care about what they’re making. They believe in their unique skill and vision over engagement strategies and analytics and content algorithms. They don’t need a platform, or they’ll build their own.

If you wanted to make a really crude approximation of project management, you could say there are two main styles: waterfall and agile.

It’s not as simple as that by any means. And the two aren’t really separate things; agile came about as a response to the failures of waterfall. But if we’re going to stick with crude approximations, here we go:

• In a waterfall process, you define everything up front and then execute.
• In an agile process, you start executing and then adjust based on what you learn.

So crude! Much approximation!

It only recently struck me that the agile approach is basically a cybernetic system.

Cybernetics is pretty much anything that involves feedback. If it’s got inputs and outputs that are connected in some way, it’s probably cybernetic. Politics. Finance. Your YouTube recommendations. Every video game you’ve ever played. You. Every living thing on the planet. That’s cybernetics.

Fun fact: early on in the history of cybernetics, a bunch of folks wanted to get together at an event to geek about this stuff. But they knew that if they used the word “cybernetics” to describe the event, Norbert Wiener would show up and completely dominate proceedings. So they invented a new alias for the same thing. They coined the term “artificial intelligence”, or AI for short.

Yes, ironically the term “AI” was invented in order to repel a Reply Guy. Now it’s Reply Guy catnip. In today’s AI world, everyone’s a Norbert Wiener.

The thing that has the Wieners really excited right now in the world of programming is the idea of agentic AI. In this set-up, you don’t do any of the actual coding. Instead you specify everything up front and then have a team of artificial agents execute your plan.

That’s right; it’s a return to waterfall. But that’s not as crazy as it sounds. Waterfall was wasteful because execution was expensive and time-consuming. Now that execution is relatively cheap (you pay a bit of money to line the pockets of the worst people in exchange for literal tokens), you can afford to throw some spaghetti at the wall and see if it sticks.

But you lose the learning. The idea of a cybernetic system like, say, agile development, is that you try something, learn from it, and adjust accordingly. You remember what worked. You remember what didn’t. That’s learning.

Outsourcing execution to machines makes a lot of sense.

I’m not so sure it makes sense to outsource learning.

Measured AI | Note to Self

It’s creepy to tell people they’ll lose their jobs if they don’t use AI. It’s weird to assume AI critics hate progress and are resisting some inevitable future.

The AI Gold Rush Is Cover for a Class War

Under the guise of technological inevitability, companies are using the AI boom to rewrite the social contract — laying off employees, rehiring them at lower wages, intensifying workloads, and normalizing precarity. In short, these are political choices masquerading as technical necessities, AI is not the cause of the layoffs but their justification.

The Programmer Identity Crisis ❈ Simon Højberg ❈ Principal Frontend Engineer

I prefer my tools to help me with repetitive tasks (and there are many of those in programming), understanding codebases, and authoring correct programs. I take offense at products that are designed to think for me. To remove the agency of my own understanding of the software I produce, and to cut connections with my coworkers. Even if LLMs lived up to the hype, we would still stand to lose all of that and our craft.

I’ve been going buildless—or as Brad crudely puts it, raw-dogging websites on a few projects recently. Not just obviously simple things like Clearleft’s Browser Support page, but sites like:

• The Clearleft podcast
• Patterns Day
• UX London

They also have 0 dependencies.

Like Max says:

Funnily enough, many build tools advertise their superior “Developer Experience” (DX). For my money, there’s no better DX than shipping code straight to the browser and not having to worry about some cryptic node_modules error in between.

Making websites without a build step is a gift to your future self. When you open that project six months or a year or two years later, there’ll be no faffing about with npm updates, installs, or vulnerabilities.

Need to edit the CSS? You edit the CSS. Need to change the markup? You change the markup.

It’s remarkably freeing. It’s also very, very performant.

If you’re thinking that your next project couldn’t possibly be made without a build step, let me tell you about a phrase I first heard in the indie web community: “Manual ‘till it hurts”. It’s basically a two-step process:

1. Start doing what you need to do by hand.
2. When that becomes unworkable, introduce some kind of automation.

It’s remarkable how often you never reach step two.

I’m not saying premature optimisation is the root of all evil. I’m just saying it’s premature.

Start simple. Get more complex if and when you need to.

You might never need to.

Why “AI” projects fail

“AI” is heralded (by those who claim it to replace workers as well as those that argue for it as a mere tool) as a thing to drop into your workflows to create whatever gains promised. It’s magic in the literal sense. You learn a few spells/prompts and your problems go poof. But that was already bullshit when we talked about introducing other digital tools into our workflows.

And we’ve been doing this for decades now, with every new technology we spend a lot of money to get a lot of bloody noses for way too little outcome. Because we keep not looking at actual, real problems in front of us – that the people affected by them probably can tell you at least a significant part of the solution to. No we want a magic tool to make the problem disappear. Which is a significantly different thing than solving it.

Does AI benefit the world? – Chelsea Troy

Our ethical struggle with generative models derives in part from the fact that we…sort of can’t have them ethically, right now, to be honest. We have known how to build models like this for a long time, but we did not have the necessary volume of parseable data available until recently—and even then, to get it, companies have to plunder the internet. Sitting around and waiting for consent from all the parties that wrote on the internet over the past thirty years probably didn’t even cross Sam Altman’s mind.

On the environmental front, fans of generative model technology insist that eventually we’ll possess sufficiently efficient compute power to train and run these models without the massive carbon footprint. That is not the case at the moment, and we don’t have a concrete timeline for it. Again, wait around for a thing we don’t have yet doesn’t appeal to investors or executives.

Aboard Newsletter: Why So Bad, AI Ads?

The human desire to connect with others is very profound, and the desire of technology companies to interject themselves even more into that desire—either by communicating on behalf of humans, or by pretending to be human—works in the opposite direction. These technologies don’t seem to be encouraging connection as much as commoditizing it.

Pop Culture

Despite all of this hype, all of this media attention, all of this incredible investment, the supposed “innovations” don’t even seem capable of replacing the jobs that they’re meant to — not that I think they should, just that I’m tired of being told that this future is inevitable.

The reality is that generative AI isn’t good at replacing jobs, but commoditizing distinct acts of labor, and, in the process, the early creative jobs that help people build portfolios to advance in their industries.

One of the fundamental misunderstandings of the bosses replacing these workers with generative AI is that you are not just asking for a thing, but outsourcing the risk and responsibility.

Generative AI costs far too much, isn’t getting cheaper, uses too much power, and doesn’t do enough to justify its existence.

Ideas Aren’t Worth Anything - The Biblioracle Recommends

The fact that writing can be hard is one of the things that makes it meaningful. Removing this difficulty removes that meaning.

There is significant enthusiasm for this attitude inside the companies that produce an distribute media like books, movies, and music for obvious reasons. Removing the expense of humans making art is a real savings to the bottom line.

But the idea of this being an example of democratizing creativity is absurd. Outsourcing is not democratizing. Ideas are not the most important part of creation, execution is.

How do we build the future with AI? – Chelsea Troy

This is the transcript of a fantastic talk called “The Tools We Still Need to Build with AI.”

Absorb every word!

The mainstreaming of ‘AI’ scepticism – Baldur Bjarnason

1. Tech is dominated by “true believers” and those who tag along to make money.
2. Politicians seem to be forever gullible to the promises of tech.
3. Management loves promises of automation and profitable layoffs.

But it seems that the sentiment might be shifting, even among those predisposed to believe in “AI”, at least in part.

Because There’s No “AI” in “Failure”

My new favourite blog on Tumblr.

Rise of the Ghost Machines - The Millions

This thing that we’ve been doing collectively with our relentless blog posts and pokes and tweets and uploads and news story shares, all 30-odd years of fuck-all pointless human chatterboo, it’s their tuning fork. Like when a guitarist plays a chord on a guitar and compares the sound to a tuner, adjusts the pegs, plays the chord again; that’s what has happened here, that’s what all my words are, what all our words are, a thing to mimic, a mockingbird’s feast.

Every time you ask AI to create words, to generate an answer, it analyzes the words you input and compare those words to the trillions of relations and concepts it has already categorized and then respond with words that match the most likely response. The chatbot is not thinking, but that doesn’t matter: in the moment, it feels like it’s responding to you. It feels like you’re not alone. But you are.

The Danger Of Superhuman AI Is Not What You Think - NOEMA

Once you have reduced the concept of human intelligence to what the markets will pay for, then suddenly, all it takes to build an intelligent machine — even a superhuman one — is to make something that generates economically valuable outputs at a rate and average quality that exceeds your own economic output. Anything else is irrelevant.

By describing as superhuman a thing that is entirely insensible and unthinking, an object without desire or hope but relentlessly productive and adaptable to its assigned economically valuable tasks, we implicitly erase or devalue the concept of a “human” and all that a human can do and strive to become. Of course, attempts to erase and devalue the most humane parts of our existence are nothing new; AI is just a new excuse to do it.

Generative AI is for the idea guys

Generative AI is like the ultimate idea guy’s idea! Imagine… if all they needed to create a business, software or art was their great idea, and a computer. No need to engage (or pay) any of those annoying makers who keep talking about limitations, scope, standards, artistic integrity etc. etc.

What Are We Actually Doing With A.I. Today? – Pixel Envy

The marketing of A.I. reminds me less of the cryptocurrency and Web3 boom, and more of 5G. Carriers and phone makers promised world-changing capabilities thanks to wireless speeds faster than a lot of residential broadband connections. Nothing like that has yet materialized.