Number one:
Do things in the most straightforward way possible. It’s easy to fall into the trap of clever solutions, or clever applications of technology, or overbuilding something because you’re anticipating the future. Don’t do it. You will hate yourself for it later when you have to maintain it.
Ethicswishing (in tech) is the belief that if you are committed to being ethical and understand technology, then you are well-equipped to build technology for social good. But the truth is that building tech for social good is a lot like having sex in a bathtub: if you don’t understand the first thing about sex, it won’t help that you’re a world-class expert in bathtubs.
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.
Your teams should be working closer to the web platform with a lot less complex abstractions. We need to relearn what the web is capable of and go back to that.
Let’s be clear, I’m not suggesting this is strictly better and the answer to all of your problems. I’m suggesting this as an intentional business tradeoff that I think provides more value and is less costly in the long run.
Everyone’s raving about this great talk by Marcin, and rightly so!
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.
This is the transcript of a fantastic talk called “The Tools We Still Need to Build with AI.”
Absorb every word!
- Tech is dominated by “true believers” and those who tag along to make money.
- Politicians seem to be forever gullible to the promises of tech.
- 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.
My new favourite blog on Tumblr.
AI is steeped in marketing drivel, built upon theft, and intent on replacing our creative output with a depressingly shallow imitation.
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.
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.
Maciej rips NASA’s Artemis programme a new one:
Advocates for Artemis insist that the program is more than Apollo 2.0. But as we’ll see, Artemis can’t even measure up to Apollo 1.0. It costs more, does less, flies less frequently, and exposes crews to risks that the steely-eyed missile men of the Apollo era found unacceptable. It’s as if Ford in 2024 released a new model car that was slower, more accident-prone, and ten times more expensive than the Model T.
When a next-generation lunar program can’t meet the cost, performance, or safety standards set three generations earlier, something has gone seriously awry.
An insightful and incisive appraisal of technology adoption. This truth hits hard:
React and the component model standardises the software developer and reduces their individual bargaining power excluding them from a proportional share in the gains. Its popularity among executives and management is entirely down to the fact that it helps them erase the various specialities – CSS, accessibility, standard JavaScript in the browser, to name a few – from the job market. Those specialities might still exist in practice – as ad hoc and informal requirements during teamwork – but, as far as employment is concerned, they’re such a small part of the overall developer job market that they might as well be extinct.
A fascinating in-depth look at the maintenance of undersea cables:
The industry responsible for this crucial work traces its origins back far beyond the internet, past even the telephone, to the early days of telegraphy. It’s invisible, underappreciated, analog.
It’s a truism that people don’t think about infrastructure until it breaks, but they tend not to think about the fixing of it, either.
I find my feelings about AI are actually pretty similar to my feelings about blockchains: they do a poor job of much of what people try to do with them, they can’t do the things their creators claim they one day might, and many of the things they are well suited to do may not be altogether that beneficial. And while I do think that AI tools are more broadly useful than blockchains, they also come with similarly monstrous costs.
A very even-handed take.
I’m glad that I took the time to experiment with AI tools, both because I understand them better and because I have found them to be useful in my day-to-day life. But even as someone who has used them and found them helpful, it’s remarkable to see the gap between what they can do and what their promoters promise they will someday be able to do. The benefits, though extant, seem to pale in comparison to the costs.
Powerful metaphors in this piece by Maria Farrell and Robin Berjon on the Waldsterben of the internet:
Our online spaces are not ecosystems, though tech firms love that word. They’re plantations; highly concentrated and controlled environments, closer kin to the industrial farming of the cattle feedlot or battery chicken farms that madden the creatures trapped within.
We all know this. We see it each time we reach for our phones. But what most people have missed is how this concentration reaches deep into the internet’s infrastructure — the pipes and protocols, cables and networks, search engines and browsers. These structures determine how we build and use the internet, now and in the future.
Owning your own piece of the Internet (to borrow a recent phrase from Anil Dash) is itself a radical act. Linking to others at will is subversive all on its own. Or as Jeremy Keith once put it, “it sounds positively disruptive to even suggest that you should have your own website.” The web still exists for everyone. And beneath this increasingly desiccated surface, there is plenty of creators still simply creating.
People create these sites simply so that they exist. They are not fed to an algorithm, or informed by any trends. It is quieter and slower, meant to tether us to a more mechanical framework of the web.
This is the analog web.
Craig and Jason are walking the walk here:
- Build your own damn platform.
- Treat social media like the tool it is.
- Build your technical skills.