#AI

Though I am no great fan of AI or its massively over-hyped potential, I also do not think it's useless. As Molly White put it:

When I boil it down, 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.

I wholeheartedly agree with those claims, and don't want to get into the specifics of them too much. Instead, I wanted to think out loud/write about why there's such a wide range of expectations and opinions on the current and future states of AI.

To get the easy one out of the way: Many of the most effusive AI hype people are in fit for the money. They're raising venture capital by saying AI, they're trying to get brought in as consultants on AI, or they're trying to sell their AI product to businesses and consumers. I don't think that's a particularly new phenomenon when it comes to new technology, though perhaps there is some novelty in how many different ways people are attempting to get their slice of the cake (companies cooking up AI models, apps trying to sell AI generation to consumers, hardware and cloud providers selling the compute necessary to do all of the above, etc.).

But once we take pure profit motive out of the way, there are I think two key areas of difference in people who believe in AI wholeheartedly and those who are neutral to critical.

The first is software development experience. Those who understand what it actually means when people say "AI is thinking" tend to have an overall more pessimistic view of the pinnacle of current AI generation strategies. In a nutshell, all of the current generative models try to ingest as much content of whatever thing they're going to be asked to output. Then, they are given a "prompt," and they are (in simplistic terms) trying to piece together an image/string of words/video that looks most likely based on what came for.

This is why these models "hallucinate" - they don't "know" anything specifically in the way you know that Washington, DC is the capital of the United States. It just knows that when a sentence starts "The capital of the United States is" it usually ends with the words "Washington, DC."

And that can be useful in some instances! This is why AI does very well on low-level coding tasks - a lot of the basics of programming is pretty repetitive and pattern-based, so an expert pattern-matcher can do fairly well at guessing the most likely outcome. But it's also why AI developer assistants produce stupid mistakes, because it doesn't "understand" the syntax or the language or even the problem statement as a fundamental unit of knowledge. It simply reads a string of text and tries to figure out what would most likely come next.

The other thing you learn from experience are edge cases, and specifically what doesn't work. This type of knowledge tends to accumulate only through having worked on a product before, and understanding how different pieces come together (or don't). AI lacks this awareness of context, focusing only what immediately surrounds the section it's working on.

But the other primary differentiator is for the layperson, who can best be understood as a consumer and it can be condensed to a single word: Taste.

I'm reminded of a quote from Ira Glass I heard on some podcast:

... all of us who do creative work … we get into it because we have good taste. But it’s like there’s a gap, that for the first couple years that you’re making stuff, what you’re making isn’t so good, OK? It’s not that great. It’s really not that great. It’s trying to be good, it has ambition to be good, but it’s not quite that good. But your taste — the thing that got you into the game — your taste is still killer, and your taste is good enough that you can tell that what you’re making is kind of a disappointment to you ...

I think this is true, and I think it's the biggest differentiator between people who think what AI is capable of right now is perfectly fine and those that think it'll all wind up being a waste of time. People who can't or are unwilling create text/images/videos on their own think that AI is a great shortcut. This is either because the quality of what the AI can produce is better than what they can do unassisted, or they don't have the taste to see the difference in the first place.

I don't know that I think there's a way to bridge that gap any more than there is to explain to people who think that criticism of any artform is "unfair" or that "well, could you do any better?" is a valid counterpoint to cultural criticism. There are simply those people whose taste is better than that what can be created only through an amalgamation of data used to train a model, and those who think that a simulacrum of art is indistinguishable (or better) than the real thing.

AI is not magic, part 1033: Accessibility

You know it's a good sign when the first thing I do after finishing an article is double-check whether the whole site is some sort of AI-generated spoof. The answer on this one was closer than you might like, but I do think it's genuine.

Jakob Nielsen, UX expert, has apparently gone and swallowed the AI hype by unhinging his jaw, if the overall subjects of his Substack are to be believed. And that's fine, people can have hobbies, but the man's opinions are now coming after one of my passions, accessibility, and that cannot stand.

OpenAI announced Sora, a new model for text-to-video, and it's ... fine? I guess? I mean, I know why they announced it - it's legitimately really cool you can type something in and a video vaguely approximating your description in really high resolution shows up.

I just don't think it's really all that useful in real-world contexts.

Don't get me wrong, I appreciate their candor in the "whoopsies" segments, but even in the show-off pieces some of the video is weird to just downright bad.

Hands are hard! I get it! But there's also quite literally a "bag lady" (a woman who appears to be carrying at least two gigantic purses), and (especially when the camera moves) the main character floats along the ground without actually walking pretty often.

Are these nitpicky things people aren't going to notice on first glance? Maybe. But remember the outrage around Ugly Sonic? People notice small (or large) discrepancies in their popular entertainment, and the brand suffers for it. To say nothing of advertisers! Imagine trying to market your brand-new (well, "new" in car definitions) car without an accurate model of said car in the ad. Or maybe you really want to buy the latest Danover.

It seems like all the current AI output has a limit of "close-ish" for things, from self-driving to video to photos to even text generation. It all requires human editing, often significant for any work of reasonable size, to pull it out of the uncanny valley.

"But look how far they've gotten in such little time!" they cry. "Just wait!"

But nobody's managed to push past that last 10% in any domain. It always requires a human touch to get it "right."

Like the fake Land Rover commercial is interesting, except imagine the difficulty of getting it to match your new product (look and name) exactly. You're almost going to have to CGI it in after, at least parts, at which point you've lost much of the benefit.

Unfortunately, "close enough" is good enough for a lot of people who are lazy, cheap or don't care about quality. The software example I'd give is there probably aren't a lot of companies who'd be willing to pay for software consultant services who are just going to use AI instead, but plenty of those people who message you on LinkedIn willing to pay you $200 for a Facebook clone absolutely are going to pay Copilot $20 a month instead.

And yes, there will be those people (especially levels removed from the actual work) who will think they can replace their employees with chatbots, and it might even work for a little bit. But poorly designed systems always have failure points, and once you hit it you're going to wind up having to scrap the whole thing. A building with a bad foundation can't be fixed through patching.

I have a feeling it's the same in other industries. I do think workers will feel the hit, especially on lower-budget products already or where people see an opportunity to cut corners. I also think our standards as a society will be relaxed a little bit in a lot of areas, simply because the mean will regress

But in good news, I think this'll shake out in a few years where people realize AI isn't replacing everything any more than Web3 did, but AI will have more utility as a tool in the toolkit of professionals. It's just gonna take a bit to get there.