This is a really thoughtful piece by Rich, who’s got conflicted feelings about large language models in the design process. I suspect a lot of people can relate to this.
What I do know is that I find LLMs useful on occasion, but every time I use one I die a little inside.
I miss being excited by technology. I wish I could see a way out of the endless hype cycles that continue to elicit little more than cynicism from me. The version of technology that we’re mostly being sold today has almost nothing to do with improving lives, but instead stuffing the pockets of those who already need for nothing. It’s not making us smarter. It’s not helping heal a damaged planet. It’s not making us happier or more generous towards each other. And it’s entrenched in everything — meaning a momentous challenge to re-wire or meticulously disconnect. I’m slowly finding my own ways of breaking free to regain a sense of self and purpose.
I Feel Like I’m Going Insane
Everywhere you look, the media is telling you that OpenAI and their ilk are the future, that they’re building “advanced artificial intelligence” that can take “human-like actions,” but when you look at any of this shit for more than two seconds it’s abundantly clear that it absolutely isn’t and absolutely can’t.
Despite the hype, the marketing, the tens of thousands of media articles, the trillions of dollars in market capitalization, none of this feels real, or at least real enough to sustain this miserable, specious bubble.
We are in the midst of a group delusion — a consequence of an economy ruled by people that do not participate in labor of any kind outside of sending and receiving emails and going to lunches that last several hours — where the people with the money do not understand or care about human beings.
Their narrative is built on a mixture of hysteria, hype, and deeply cynical hope in the hearts of men that dream of automating away jobs that they would never, ever do themselves.
Generative AI is a financial, ecological and social time bomb, and I believe that it’s fundamentally damaging the relationship between the tech industry and society, while also shining a glaring, blinding light on the disconnection between the powerful and regular people. The fact that Sam Altman can ship such mediocre software and get more coverage and attention than every meaningful scientific breakthrough of the last five years combined is a sign that our society is sick, our media is broken, and that the tech industry thinks we’re all fucking morons.
When haters deny HTML’s status as a programming language, they’re showing they don’t understand what a language really is. Language is not instructing an interlocutor what to do in a way that leaves no room for other interpretations; it is better and richer than that. Like human language, HTML is conversational. It is remarkably adept at adapting to context. It can take a different shape on any machine, from a desktop browser or an e-reader screen to a mobile app or a screen reader for the blind (so long as that device is built to present hypertext).
Hell, yeah!
Ultimately, even as HTML has become the province of professionals, it cannot be gatekept. This is what makes so many programmers so anxious about the web, and sometimes pathetically desperate to maintain the all-too-real walls they’ve erected between software engineers and web developers.
Hell, yeeeeaaaaahhh!!!
What other programmers might say dismissively is something HTML lovers embrace: Anyone can do it. Whether we’re using complex frameworks or very simple tools, HTML’s promise is that we can build, make, code, and do anything we want.
A shame that this must-read book won’t be out in time for Christmas—’twould make a great stocking filler for a lot of people I know.
A smart, incisive look at the technologies sold as artificial intelligence, the drawbacks and pitfalls of technology sold under this banner, and why it’s crucial to recognize the many ways in which AI hype covers for a small set of power-hungry actors at work and in the world.
Hypertext links are an information-density multiplier.
The way I’ve long thought about it is that traditional writing — like for print — feels two-dimensional. Writing for the web adds a third dimension. It’s not an equal dimension, though. It doesn’t turn writing from a flat plane into a full three-dimensional cube. It’s still primarily about the same two dimensions as old-fashioned writing. What hypertext links provide is an extra layer of depth. Just the fact that the links are there — even if you, the reader, don’t follow them — makes a sentence read slightly differently. It adds meaning in a way that is unique to the web as a medium for prose.
While I’ve grown more cynical about much of tech, movements like the Indieweb and the Fediverse remind me that the ideals I once loved, and that spirit of the early web, aren’t lost. They’re evolving, just like everything else.
This is how I write:
As an online writer, my philosophy is link maximalism; links add another layer to my writing, whether I’m linking to an expansion of a particular idea or another person’s take, providing evidence or citation, or making a joke by juxtaposing text and target. Links reveal personality as much as the text. Linking allows us to stretch our ideas, embedding complexity, acknowledging ambiguity, holding contradictions.
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.
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.
The rise of dot-com companies was pitched as a no consequences gold rush. We were on the precipice of a fictional future where everyone would be cashing in on the web. The reality was quite a bit more slow, and boring. Business on the web consolidated, as we now know, and left most people holding the bag. There’s no knowing exactly what will happen with AI technologies, but it wouldn’t be unreasonable to expect something far more boring and centralized than what’s being promised.
All this has happened before. All this will happen again.
Each of these cycles has been larger and lasted longer than the last, and I want to be clear: each cycle has produced genuinely useful technology. It’s just that each follows the progress of a sigmoid curve that everyone mistakes for an exponential one. There is an initial burst of rapid improvement, followed by gradual improvement, followed by a plateau. Initial promises imply or even state outright “if we pour more {compute, RAM, training data, money} into this, we’ll get improvements forever!” The reality is always that these strategies inevitably have a limit, usually one that does not take too long to find.
Develop a simple, focused app that does what it says on the tin — not one where the tin talks back at you.
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.
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.
I don’t believe the greatest societal risk is that a sentient artificial intelligence is going to kill us all. I think our undoing is simpler than that. I think that most of our lives are going to be shorter and more miserable than they could have been, thanks to the unchecked greed that’s fed this rally. (Okay, this and crypto.)
I like this analogy:
AI is like a dancing bear. This was a profitable sideshow dating back to the middle ages: all it takes is a bear, some time, and a complete lack of ethics. Today, our carnival barkers are the AI startups and their CEOs. They’re trying to convince you that if they can show you a bear that can dance, then you’ll believe it can draw, write coherent sentences, and help you with your app’s marketing strategy.
Part of the curiosity of a dancing bear is the implicit risk that it’ll remember at some point that it’s a bear, and maul whoever is nearby. The fear is a selling point. Likewise, some AI vendors have even learned that the product is more compelling if it’s perceived as dangerous. It’s common for AI startup execs to say things like, “of course there’s a real risk that an army of dancing bears will eventually kill us all. Anyway, here’s what we’re working on…” How brave of them.
As a self-initiated learner, being able to view source brought to mind the experience of a slow walk through someone else’s map.
This ability to “observe” software makes HTML special to work with.
You are not creative and then create something, you become creative by working on something, creativity is a byproduct of work.
In this way “AI” is deeply dehumanizing: Making the spaces and opportunities for people to grow and be human smaller and smaller. Applying a straitjacket of past mediocrity to our minds and spirits.
And that is what is being booed: The salespeople of mediocrity who’ve made it their mission to speak lies from power. The lie that only tech can and will save us. The lie that a bit of statistics and colonial, mostly white, mostly western data is gonna create a brilliant future. The lie that we have no choice, no alternatives.
What we’re seeing is FOMO-driven dumb money thrown at technology by people who have no hope of understanding it. Just because everybody else is and because the GPTs and image generators have cool demos.
What’s going to happen, I’m pretty sure, is that AI/ML will, inevitably, disappoint; in the financial sense I mean, probably doing some useful things, maybe even a lot, but not generating the kind of profit explosions that you’d need to justify the bubble. So it’ll pop, and my bet it is takes a bunch of the finance world with it.
This is mostly about the intersection of finance, hype, and technology, but Tim mentions something that I’ve also been saying:
I’m super impressed by something nobody else seems to talk about: Prompt parsing.
Maybe it’s because I spent formative users playing text-only adventure games, but I am way more impressed by the way generative tools do natural language parsing than I am by their output.
Subvert the status quo. Own a website. Make and share links.