Why is this Happening, Part II: Letting Computers Do The Fun Part
Previously: Part I
Let’s leave the Stuff that Sucks aside for the moment, and ask a different question. Which Part is the Fun Part? What are we going to do with this time the robots have freed up for us?
It’s easy to get wrapped up in pointing at the parts of living that suck; especially when fantasizing about assigning work to C-3PO’s cousin. And it’s easy to spiral to a place where you just start waving your hands around at everything.
But even Bertie Wooster had things he enjoyed, that he occasionally got paid for, rather than let Jeeves work his jaw for him.
So it’s worth recalibrating for a moment: which are the fun parts?
As aggravating as it can be at times, I do actually like making computers do things. I like programming, I like designing software, I like building systems. I like finding clever solutions to problems. I got into this career on purpose. If it was fun all the time they wouldn’t have to call it “work”, but it’s fun a whole lot of the time.
I like writing (obviously.) For me, that dovetails pretty nicely with liking to design software; I’m generally the guy who ends up writing specs or design docs. It’s fun! I owned the customer-facing documentation several jobs back. It was fun!
I like to draw! I’m not great at it, but I’m also not trying to make a living out of it. I think having hobbies you enjoy but aren’t great at is a good thing. Not every skill needs to have a direct line to a career or a side hustle. Draw goofy robots to make your kids laugh! You don’t need to have to figure out a the monetization strategy.
In my “outside of work” life I think I know more writers and artists than programmers. For all of them, the work itself—the writing, the drawing, the music, making the movie—is the fun part. The parts they don’t like so well is the “figuring out how to get paid” part, or the dealing with printers part, or the weird contracts part. The hustle. Or, you know, the doing dishes, laundry, and vacuuming part. The “chores” part.
So every time I see a new “AI tool” release that writes text or generates images or makes video, I always as the same question:
Why would I let the computer do the fun part?
The writing is the fun part! The drawing pictures is the fun part! Writing the computer programs are the fun part! Why, why, are they trying to tell us that those are the parts that suck?
Why are the techbros trying to automate away the work people want to do?
It’s fun, and I worked hard to get good at it! Now they want me to let a robot do it?
Generative AI only seems impressive if you’ve never successfully created anything. Part of what makes “AI art” so enragingly radicalizing is the sight of someone whose never tried to create something before, never studied, never practiced, never put the time in, never really even thought about it, joylessly showing off their terrible AI slop they made and demanding to be treated as if they made it themselves, not that they used a tool built on the fruits of a million million stolen works.
Inspiration and plagiarism are not the same thing, the same way that “building a statistical model of word order probability from stuff we downloaded from the web” is not the same as “learning”. A plagiarism machine is not an artist.
But no, the really enraging part is watching these people show off this garbage realizing that these people can’t tell the difference. And AI art seems to be getting worse, AI pictures are getting easier spot, not harder, because of course it is, because the people making the systems don’t know what good is. And the culture is following: “it looks like AI made it” has become the exact opposite of a compliment. AI-generated glop is seen as tacky, low quality. And more importantly, seen as cheap, made by someone who wasn’t willing to spend any money on the real thing. Trying to pass off Krusty Burgers as their own cooking.
These are people with absolutely no taste, and I don’t mean people who don’t have a favorite Kurosawa film, I mean people who order a $50 steak well done and then drown it in A1 sauce. The kind of people who, deep down, don’t believe “good” is real. That it’s all just “marketing.”
The act of creation is inherently valuable; creation is an act that changes the creator as much as anyone. Writing things down isn’t just documentation, it’s a process that allows and enables the writer to discover what they think, explore how they actually feel.
“Having AI write that for you is like having a robot lift weights for you.”
AI writing is deeply dehumanizing, to both the person who prompted it and to the reader. There is so much weird stuff to unpack from someone saying, in what appears to be total sincerity, that they used AI to write a book. That the part they thought sucked was the fun part, the writing, and left their time free for… what? Marketing? Uploading metadata to Amazon? If you don’t want to write, why do you want people to call you a writer?
Why on earth would I want to read something the author couldn’t be bothered to write? Do these ghouls really just want the social credit for being “an artist”? Who are they trying to impress, what new parties do they think they’re going to get into because they have a self-published AI-written book with their name on it? Talk about participation trophies.
All the people I know in real life or follow on the feeds who use computers to do their thing but don’t consider themselves “computer people” have reacted with a strong and consistant full-body disgust. Personally, compared to all those past bubbles, this is the first tech I’ve ever encountered where my reaction was complete revulsion.
Meanwhile, many (not all) of the “computer people” in my orbit tend to be at-least AI curious, lots of hedging like “it’s useful in some cases” or “it’s inevitable” or full-blown enthusiasm.
One side, “absolutely not”, the other side, “well, mayyybe?” As a point of reference, this was the exact breakdown of how these same people reacted to blockchain and bitcoin.
One group looks at the other and sees people musing about if the face-eating leopard has some good points. The other group looks at the first and sees a bunch of neo-luddites. Of course, the correct reaction to that is “you’re absolutely correct, but not for the reasons you think.”
There’s a Douglas Adams bit that gets quoted a lot lately, which was printed in Salmon of Doubt but I think was around before that:
I’ve come up with a set of rules that describe our reactions to technologies:
Anything that is in the world when you’re born is normal and ordinary and is just a natural part of the way the world works.
Anything that’s invented between when you’re fifteen and thirty-five is new and exciting and revolutionary and you can probably get a career in it.
Anything invented after you’re thirty-five is against the natural order of things.
The better-read AI-grifters keep pointing at rule 3. But I keep thinking of the bit from Dirk Gently’s Detective Agency about the Electric Monk:
The Electric Monk was a labour-saving device, like a dishwasher or a video recorder. Dishwashers washed tedious dishes for you, thus saving you the bother of washing them yourself, video recorders watched tedious television for you, thus saving you the bother of looking at it yourself; Electric Monks believed things for you, thus saving you what was becoming an increasingly onerous task, that of believing all the things the world expected you to believe.
So, what are the people who own the Monks doing, then?
Let’s speak plainly for a moment—the tech industry has always had a certain…. ethical flexibility. The “things” in “move fast and break things” wasn’t talking about furniture or fancy vases, this isn’t just playing baseball inside the house. And this has been true for a long time, the Open Letter to Hobbyists was basically Gates complaining that other people’s theft was undermining the con he was running.
We all liked to pretend “disruption” was about finding “market inefficiencies” or whatever, but mostly what that meant was moving in to a market where the incumbents were regulated and labor had legal protection and finding a way to do business there while ignoring the rules. Only a psychopath thinks “having to pay employees” is an “inefficiency.”
Vast chunks of what it takes to make generative AI possible are already illegal or at least highly unethical. The Internet has always been governed by a sort of combination of gentleman’s agreements and pirate codes, and in the hunger for new training data, the AI companies have sucked up everything, copyright, licensing, and good neighborship be damned.
There’s some half-hearted attempts to combat AI via arguments that it violates copyright or open source licensing or other legal approach. And more power to them! Personally, I’m not really interested in the argument the AI training data violates contract law, because I care more about the fact that it’s deeply immoral. See that Vonnegut line about “those who devised means of getting paid enormously for committing crimes against which no laws had been passed.” Much like I think people who drive too fast in front of schools should get a ticket, sure, but I’m not opposed to that action because it was illegal, but because it was dangerous to the kids.
It’s been pointed out more than once that AI breaks the deal behind webcrawlers and search—search engines are allowed to suck up everyone’s content in exchange for sending traffic their way. But AI just takes and regurgitates, without sharing the traffic, or even the credit. It’s the AI Search Doomsday Cult. Even Uber didn’t try to put car manufacturers out of business.
But beyond all that, making things is fun! Making things for other people is fun! It’s about making a connection between people, not about formal correctness or commercial viability. And then you see those terrible google fan letter ads at the olympics, or see people crowing that they used AI to generate a kids book for their children, and you wonder, how can these people have so little regard for their audience that they don’t want to make the connection themselves? That they’d rather give their kids something a jumped-up spreadsheet full of stolen words barfed out instead of something they made themselves? Why pass on the fun part, just so you can take credit for something thoughtless and tacky? The AI ads want you to believe that you need their help to find “the right word”; what thay don’t tell you is that no you don’t, what you need to do is have fun finding your word.
Robots turned out to be hard. Actually, properly hard. You can read these papers by computer researchers in the fifties where they’re pretty sure Threepio-style robot butlers are only 20 years away, which seems laughable now. Robots are the kind of hard where the more we learn the harder they seem.
As an example: Doctor Who in the early 80s added a robot character who was played by the prototype of an actual robot. This went about as poorly as you might imagine. That’s impossible to imagine now, no producer would risk their production on a homemade robot today, matter how impressive the demo was. You want a thing that looks like Threepio walking around and talking with a voice like a Transformer? Put a guy in a suit. Actors are much easier to work with. Even though they have a union.
Similarly, “General AI” in the HAL/KITT/Threepio sense has been permanently 20 years in the future for at least 70 years now. The AI class I took in the 90s was essentially a survey of things that hadn’t worked, and ended with a kind of shrug and “maybe another 20?”
Humans are really, really good at seeing faces in things, and finding patterns that aren’t there. Any halfway decent professional programmer can whip up an ELIZA clone in an afternoon, and even knowing how the trick works it “feels” smarter than it is. A lot of AI research projects are like that, a sleight-of-hand trick that depends on doing a lot of math quickly and on the human capacity to anthropomorphize. And then the self-described brightest minds of our generation fail the mirror test over and over.
Actually building a thing that can “think”? Increasingly seems impossible.
You know what’s easy, though, comparatively speaking? Building a statistical model of all the text you can pull off the web.
On Friday: conclusions, such as they are.