and another thing: they’re not stranded. please don’t put in the newspaper that they’re stranded.
Well, three months in to an eight day mission, the Boeing Starliner made it back to earth, leaving its former crew hanging around at the orbital truckstop until February. What a bizarre episode in the history of human spaceflight, although my favorite part was when the spaceship started making strange noises .
It’s surprisingly hard to find a number for the actual amount of money NASA has handed Boeing so far for this rickety-ass “space” “ship”, but it seems to be somewhere in the $3–4 billion range?
And I know, in the annals of US tax dollars being misspent that number is very small, but while all this is going on the Chandra X-ray Observatory is basically holding a bake sale to stay in operation? Imagine what that money could have been spent on! That’s basically two full space telescopes, or one telescope with enough money left over to staff it forever. That’s two or three deep space probes. That’s a whole lot of fun science we could have done, instead of paying for an empty capsule cooling in the middle of the desert.
Software Forestry 0x01: Somewhere Between a Flower Pot and a Rainforest
“Software” covers a lot of ground. As there are a lot of different kinds and ecosystems of forests, there are a lot of kinds and ecosystems of software. And like forests, each of those kinds of software has their own goals, objectives, constraints, rules, needs.
One of the big challenges when reading about software “processes” or “best practices” or even just plain general advice is that people so rarely state up front what kind of software they’re talking about. And that leads to a lot of bad outcomes, where people take a technique or a process or an architecture that’s intrinsically linked to its originating context out of that context, recommend it, and then it gets applied to situations that are wildly inappropriate. Just like “leaves falling off” means something very different in an evergreen redwood forest than it does in one full of deciduous oak trees, different kinds of software projects need different care. As practitioners, it’s very easy for us to talk past each other.
(This generally gets cited in cases like “if you aren’t a massive social network with a dedicated performance team you probably don’t need React,” but also, pop quiz: what kind of software were all the signers of the Agile Manifesto writing at the time they wrote and signed it?1)
So, before we delve into the practice of Software Forestry, let’s orient ourselves in the landscape. What kinds of software are there?
As usual for our industry, one of the best pieces written on this is a twenty-year old Joel On Software Article,2 where he breaks software up into Five Worlds:
- Shrinkwrap (which he further subdivides into Open Source, Consultingware, and Commercial web based)
- Internal
- Embedded
- Games
- Throwaway
And that’s still a pretty good list! I especially like the way he buckets not based on design or architecture but more on economic models and business contraints.
I’d argue that in the years since that was written, “Commercial web-based” has evolved to be more like what he calls “Internal” than “Shrinkwrap”; or more to the point, those feel less like discrete categories than they do like convenient locations on a continuous spectrum. Widening that out a little, all five of those categories feel like the intersections of several spectrums.
I think spectrums are a good way to view the landcape of modern software development. Not discrete buckets or binary yes/no questions, but continuous ranges where various projects land somewhere in between the extremes.
And so, in the spirit of an enthusiastic “yes, and”, I’d like to offer up what I think are the five most interesting or influential spectrums for talking about kinds of software, which we can express as questions sketching out a left-to-right spectrum:
- Is it a Flower Pot or a Sprawling Forest?
- Does it Run on the Customer’s Computers or the Company’s Computers?
- Are the Users Paid to Use It or do they Pay to Use It?
- How Often Do Your Customers Pay You?
- How Much Does it Matter to the Users?
Is it a Flower Pot or a Sprawling Forest?
This isn’t about size or scale, necessarily, as mich as it is about overall “complexity”, the number of parts. On one end, you have small, single-purpose scripts running on one machine, on the other end, you have sprawling systems with multiple farms or clusters interacting with each other over custom messaging busses.
How many computers does it need? How many different applications work together? Different languages? How many versions do you have to maintain at once? What scale does it operate at?3 How many people can draw an accurate diagram from memory?
This has huge impacts on not only the technology, but things like team structure, coordination, and planning. Joel’s Shrinkwrap and Internal categories are on the right here, the other three are more towards the left.
Does it Run on the Customer’s Computers or the Company’s Computers?
To put that another way, how much of it works without an internet connection? Almost nothing is on one end or the other; no one ships dumb terminals or desktop software that can’t call home anymore.
Web apps are pretty far to the right, depending on how complex the in-browser client app is. Mobile apps are usually in the middle somewhere, with a strong dependency on server-side resources, but also will usually work in airplane mode. Single-player Games are pretty far to the left, only needing server components for things like updates and achievement tracking; multiplayer starts moving right. Embedded software is all the way to the left. Joel’s Shrinkwrap is left of center, Internal is all the way to the right.
This has huge implications for development processes; as an example, I started my career in what we then called “Desktop Software”. Deployment was an installer which got burned to a disk. Spinning up a new test system was unbelievably easy, pull a fresh copy of the installer and install it into a VM! Working in a micoservice mesh environment, there are days that feels like the software equivalent of greek fire, a secret long lost. In a world of sprawling services, spinning up a new environment is sometimes an insurmountable task.
A final way to look at this: how involved do your users have to be with an update?
Are the Users Paid to Use It or do they Pay to Use It?
What kind of alternate options do the people actually using the software have? Can they use something else? A lot of times you see this talked about as being “IT vs commercial,” but it’s broader than that. On the extreme ends here, the user can always choose to play a different mobile game, but if they want to renew their driver’s license, the DMV webpage is the only game in town. And the software their company had custom built to do their job is even less optional.
Another very closely related way of looking at this: Are your Customers and Users the same people? That is, are the people looking at the screen and clicking buttons the same people who cut the check to pay for it? The oft-repeated “if you’re not the customer you’re the product” is a point center-left of this spectrum.
The distance between the people paying and the people using has profound effects on the design and feedback loops for a software project. As an extreme example, one of the major—maybe the most significant—differences between Microsoft and Apple is that Microsoft is very good at selling things to CIOs, and Apple is very good at selling things to individuals, and neither is any good at selling things the other direction.
Bluntly, the things your users care about and that you get feedback on are very, very different depending on if they paid you or if they’re getting paid to use it.
Joel’s Internal category is all the way to the left here, the others are mostly over on the right side.
How Often Do Your Customers Pay You?
This feels like the aspect that’s exploded in complexity since that original Joel piece. The traditional answer to this was “once, and maybe a second time for big upgrades.” Now though, you’ve got subscriptions, live service models, “in-app purchases”, and a whole universe of models around charging a middle-man fee on other transactions. This gets even stranger for internal or mostly-internal tools, in my corporate life, I describe this spectrum as a line where the two ends are labeled “CAPEX” and “OPEX”.
Joel’s piece doesn’t really talk about business models, but the assumption seems to be a turn-of-the-century Microsoft “pay once and then for upgrades” model.
How Much Does it Matter to the Users?
Years and years ago, I worked on one of the computer systems backing the State of California’s welfare system. And on my first day, the boss opened with “however you feel about welfare, politically, if this system goes down, someone can’t feed their kids, and we’re not going to let that happen.” “Will this make a kid hungry” infused everything we did.
Some software matters. Embedded pacemakers. The phone system. Fly-by-wire flight control. Banks.
And some, frankly, doesn’t. If that mobile game glitches out, well, that’s annoying, but it was almost my appointment time anyway, you know?
Everyone likes to believe that what they’re working on is very important, but they also like to be able to say “look, this isn’t aerospace” as a way to skip more testing. And thats okay, there’s a lot of software that if it goes down for an hour or two, or glitches out on launch and needs a patch, that’s not a real problem. A minor inconvenience for a few people, forgotten about the next day.
As always, it’s a spectrum. There’s plenty of stuff in the middle: does a restaurant website matter? In the grand scheme of things, not a lot, but if the hours are wrong that’ll start having an impact on the bottom line. In my experience, there’s a strong perception bias towards the middle of this spectrum.
Joel touches on this with Embedded, but mostly seems to be fairly casual about how critical the other categories are.
There are plenty of other possible spectrums, but over the last twenty years those are the ones I’ve found myself thinking about the most. And I think the combination does a reasonable job sketching out the landscape of modern software.
A lot of things in software development are basically the same regardless of what kind of software you’re developing, but not everything. Like Joel says, it’s not like Id was hiring consultants to make UML diagrams for DOOM, and so it’s important to remember where you are in the landscape before taking advice or adopting someone’s “best practices.”
As follows from the name, Software Forestry is concerned with forests—the bigger systems, with a lot of parts, that matter, with paying customers. In general, the things more on the right side of those spectrums.
As Joel said 22 years ago, we can still learn something from each other regardless of where we all stand on those spectrums, but we need to remember where we’re standing.
Next Time: What We Talk About When We Talk About Tech Debt
- I don’t know, and the point is you don’t either, because they didn’t say.
- This almost certainly wont be the last Software Forestry post to act as extended midrash on a Joel On Software post.
- Is it web scale?
That’s How You Do That
I’ve never been convinced that “debates” are a useful contribution to presidential campaigns; the idea that the candidates are going to do some kind of good faith high school debate club show is the same kind of pundit class galaxy brained take as “there are undecided voters." But then again, we’ve found ourselves with a system where the most powerful person in the world is selected by 6000 low-information people in rural Pennsylvania, so that results in some strange artifacts.
That said.
There’s your choice America. I can’t think of another occasion with that stark a contrast between candidates for anything. Both the best and the worst debate performance I’ve ever seen, on the same stage. Once again, Harris is proving that the way to deal with the convicted felon is to call him on his bullshit as clearly as possible and to his face. You love to see it.
With that said, I wish, I really wish, that some debate moderator would open with “so, we all know this isn’t about policy, this is about appearances and vibes, so I’m going to abandon the prepared questions and open with this: What’s your best joke?” Maybe move into the Voight-Kampff questions after that.
Internet Archive Loses Appeal
In an unsurprising but nevertheless depressing ruling, the Internet Archive’s has lost its appeal in the case about their digital library. (Ars, Techdirt.)
So let me get this straight; out of everything that happened in 2020, the only people facing any kinds of legal consequences are the Internet Archive, for checks notes letting people read some books?
Software Forestry 0x00: Time For More Metaphors
Software is a young field. Creating software as a mainstream profession is barely 70 years old, depending on when you start counting. Its legends are still, if just, living memory.
Young enough that it still doesn’t have much of its own language. Other than the purely technical jargon, it’s mostly borrowed words. What’s the verb for making software? Program? Develop? Write? Similarly, what’s the name for someone who makes software? Programmer? Developer? We’ve settled, more or less, on Engineer, but what we do has little in common with other branches of engineering. Even the word “computer” is borrowed; not that long ago a computer was something like an accountant, a person who computed.1 None of this is a failing, but it is an indication of how young a field this is.
This extends to the metaphors we use to talk about the practice of creating that software. Metaphors are a cognitive shortcut, a way to borrow a different context to make the current one easier to talk about. But they can also be limiting, you can trap yourself in the boundaries of the context you borrowed.
Not that we’re short on metaphors, far from it! In keeping with the traditions of American Business, we use a lot of terms from both Sports (“Team”, “Sprint,” “Scrum”) and the Military (“Test Fire,” “Strategy vs. Tactics”). The seminal Code Complete proposed “Construction”. Knuth called it both an Art and a branch of Literature. We co-opted the term “Architecture” to talk about larger designs. In recent years, you see a lot of talk about “Craft.” “Maintenance-Oriented Programming.” For a while, I used movies. (The spec is the script! Specialized roles all coming together! But that was a very leaky abstraction.)
The wide spread of metaphors in use shows how slippery software can be, how flexible it is conceptually. We haven’t quite managed to grow a set of terms native to the field, so we keep shopping around looking for more.
I bring this up because what’s interesting about the choice of metaphors isn’t so much the direct metaphors themselves but the way they reflect the underlying philosophy of the people who chose them.
There’s two things I don’t like about a lot of those borrowed metaphors. First, most of them are Zero Sum. They assume someone is going to lose, and maybe even worse, they assume that someone is going to win. I’d be willing to entertain that that might be a useful way to think about a business as a whole in some contexts, but for a software team, that’s useless to the point of being harmful. There’s no group of people a normal software team interacts with that they can “beat”. Everyone succeeds and fails together, and they do it over the long term.
Second, most of them assume a clearly defined end state: win the game, win the battle, finish the building. Most modern software isn’t like that. It doesn’t get put in a box in Egghead anymore. Software is an ongoing effort, it’s maintained, updated, tended. Even software that’s not a service gets ongoing patches, subscriptions, DLC, the next version. There isn’t a point where it is complete, so much as ongoing refinement and care. It’s nurtured. Software is a continuous practice of maintenance and tending.
As such, I’m always looking for new metaphors; new ways of thinking about how we create, maintain, and care for software. This is something I’ve spent a lot of time stewing on over the last two decades and change. I’ve watched a lot of otherwise smart people fail to find a way to talk about what they were doing because they didn’t have the language. To quote every informercial: there has to be a better way.
What are we looking for? Situations where groups of people come together to accomplish a goal, something fundamentally creative, but with strict constraints, both physical and by convention. Where there’s competition, but not zero sum, where everyone can be successful. Most importantly, a conceptual space that assumes an ongoing effort, without a defined ending. A metaphor backed by a philosophy centered around long-term commitment and the way software projects sprawl and grow.
“Gardening” has some appeal here, but that’s a little too precious and small-scale, and doesn’t really capture the team aspect.2 We want something larger, with people working together, assuming a time scale beyond a single person’s career, something focused on sustainable management.
So, I have a new software metaphor to propose: Software Forestry.
These days, software isn’t built so much as it’s grown, increment by increment. Software systems aren’t a garden, they’re a forest, filled with a whole ecosystem of different inhabitants, with different sizes, needs, uses. It’s tended by a team of practitioners who—like foresters—maintain its health and shape that growth. We’re not engineers as much as caretakers. New shoots are tended, branches pruned, fertilizer applied, older plants taken care of, the next season’s new trees planned for. But that software isn’t there for its own sake, and as foresters we’re most concerned with how that software can serve people. We’re focused on sustainability, we know now that the new software we write today is the legacy software of tomorrow. Also “Software Forestry” means the acronym is SWF, which I find hilarious. And personally, I really like trees.3 Like with trees, if we do out jobs right this stuff will still be there long after we’ve moved on.
It’s easy to get too precious about this, and let the metaphor run away with you; that’s why there were all those Black Belts and Ninjas running around a few years ago. I’m not going to start an organization to certify Software Rangers.4 But I think a mindset around care and tending, around seasons, around long-term stewardship, around thinking of software systems as ecosystems, is a much healthier relationship to the software industry we actually have than telling your team with all seriousness that we have to get better at blocking and tackling. We’re never going to win a game, because there’s no game to win. But we might grow a healthy forest of software, and encourage healthier foresters.
Software Forestry is a new weekly feature on Icecano. Join us on Fridays as we look at approaches to growing better software. Next Time: What kind of software forests are we growing?
-
My grandmother was a “civillian computer” during the war, she computed tables describing when and how to release bombs from planes to hit a target; the bombs in those tables were larger than normal, needing new tables computed late in the war. She thought nothing of this at the time, but years later realized she had been working out tables for atomic bombs. Her work went unused, she became a minister.
- Gardening seems to pop up every couple of years; searching the web turns up quite a few abandoned swings at Software Gardening as a concept.
- I did briefly consider “Software Arborists”, but that’s a little too narrow.
- Although I assume the Dúnedain would make excellent programmers.
Ableist, huh?
Well! Hell of a week to decide I’m done writing about AI for a while!
For everyone playing along at home, NaNoWriMo, the nonprofit that grew up around the National Novel Writing Month challenge, has published a new policy on the use of AI, which includes this absolute jaw-dropper:
We also want to be clear in our belief that the categorical condemnation of Artificial Intelligence has classist and ableist undertones, and that questions around the use of Al tie to questions around privilege.
Really? Lack of access to AI is the only reason “the poors” haven’t been able to write books? This is the thing that’s going to improve access for the disabled? It’s so blatantly “we got a payoff, and we’re using lefty language to deflect criticism,” so disingenuine, and in such bad faith, that the only appropriate reaction is “hahahha Fuck You.”
That said, my absolute favorite response was El Sandifer on Bluesky:
"Fucking dare anyone to tell Alan Moore, to his face, that working class writers need AI in order to create."; immediately followed by "“Who the fuck said that I’ll fucking break his skull open” said William Blake in a 2024 seance."
It’s always a mistake to engage with Bad Faith garbage like this, but I did enjoy these attempts:
You Don't Need AI To Write A Novel - Aftermath
NaNoWriMo Shits The Bed On Artificial Intelligence – Chuck Wendig: Terribleminds
There’s something extra hilarious about the grifters getting to NaNoWriMo—the whole point of writing 50,000 words in a month is not that the world needs more unreadable 50k manuscripts, but that it’s an excuse to practice, you gotta write 50k bad words before you can get to 50k good ones. Using AI here is literally bringing a robot to the gym to lift weights for you.
If you’re the kind of ghoul that wants to use a robot to write a book for you, that’s one (terrible) thing, but using it to “win” a for-fun contest that exists just to provide a community of support for people trying to practice? That’s beyond despicable.
The NaNoWriMo organization has been a mess for a long time, it’s a classic volunteer-run non-profit where the founders have moved on and the replacements have been… poor. It’s been a scandal engine for a decade now, and they’ve fired everyone and brought in new people at least once? And the fix is clearly in; NoNoWiMo got a new Executive Director this year, and the one thing the “AI” “Industry” has at the moment is gobs of money.
I wonder how small the bribe was. Someone got handed a check, excuse me, a “sponsorship”, and I wonder how embarrassingly, enragingly small the number was.
I mean, any amount would be deeply disgusting, but if it was, “all you have to do is sell out the basic principles non-profit you’re now in charge of and you can live in luxury for the rest of your life” that’s still terrible but at least I would understand. But you know, you know, however much money changed hands was pathetically small.
These are the kind of people who should be hounded out of any functional civilization.
And then I wake up to the news that Oprah is going to host a prime time special on The AI? Ahhhh, there we go, that’s starting to smell like a Matt Damon Superbowl Ad. From the guest list—Bill Gates?—it’s pretty clearly some high-profile reputation laundering, although I’m sure Oprah got a bigger paycheck than those suckers at NaNoWriMo. I see the discourse has already decayed through a cycle of “should we pre-judge this” (spoiler: yes) and then landed on whether or not there are still “cool” uses for AI. This is such a dishonest deflection that it almost takes my breath away. Whether or not it’s “cool” is literally the least relevant point. Asbestos was pretty cool too, you know?
And Another Thing… AI Postscript
I thought I was done talking about The AI for a while after last week’s “Why is this Happening” trilogy (Part I, Part II, Part III,) but The AI wasn’t done with me just yet.
First, In one of those great coincidences, Ted Chiang has a new piece on AI in the New Yorker, Why A.I. Isn’t Going to Make Art (and yeah, that’s behind a paywall, but cough).
It’s nice to know Ted C. and I were having the same week last week! It’s the sort of piece where once you start quoting it’s hard to stop, so I’ll quote the bit everyone else has been:
The task that generative A.I. has been most successful at is lowering our expectations, both of the things we read and of ourselves when we write anything for others to read. It is a fundamentally dehumanizing technology because it treats us as less than what we are: creators and apprehenders of meaning. It reduces the amount of intention in the world.
Intention is something he locks onto here; creative work is about making lots of decisions as you do the work which can’t be replaced by a statistical average of past decisions by other people.
Second, continuing the weekend of coincidences, the kids and I went to an Anime convention this past weekend. We went to a panel on storyboarding in animation, which was fascinating, because storyboarding doesn’t quite mean the same thing in animation that it does in live-action movies.
At one point, the speaker was talking about a character in a show he had worked on named “Ai”, and specified he meant the name, not the two letters as an abbreviation, and almost reflexively spitted out “I hate A. I.!” between literally gritted teeth.
Reader, the room—which was packed—roared in approval. It was the kind of noise you’d expect to lead to a pitchfork-wielding mob heading towards the castle above town.
Outside of the more galaxy-brained corners of the wreckage of what used to be called twitter or pockets of techbros, real people in the real world hate this stuff. I can’t think of another technology from my lifetime that has ever gotten a room full of people to do that. Nothing that isn’t armed can be successful against that sort of disgust; I think we’re going to be okay.
Happy Bell Riots to All Who Celebrate
Stay safe out there during one of the watershed events of the 21st century! I was going to write something about how the worst dystopia Star Trek could imagine in the mid-90s is dramatically, breathtakingly better than the future we actually got, but jwz has the roundup of people who already did.
Can you imagine the real San Franciso of 2024 setting aside a couple of blocks for homeless people to live? To hand out ration cards? For there to be infrastructure?
Like all good Science Fiction, Deep Space Nine doesn’t say a lot about the future, but it sure says an awful lot about the time in which it was written.
Why is this Happening, Part III: Investing in Shares of a Stairway to Heaven
We’ve talked a lot about “The AI” here at Icecano, mostly in terms ranging from “unflattering” to “extremely unflattering.” Which is why I’ve found myself stewing on this question the last few months: Why is this happening?
The easy answer is that, for starters, it’s a scam, a con. That goes hand-in-hand with it also being hype-fueled bubble, which is finally starting to show signs of deflating. We’re not quite at the “Matt Damon in Superbowl ads” phase yet, but I think we’re closer than not to the bubble popping.
Fad-tech bubbles are nothing new in the tech world, in recent memory we had similar grifts around the metaverse, blockchain & “web3”, “quantum”, self-driving cars. (And a whole lot of those bubbles all had the same people behind them as the current one around AI. Lots of the same datacenters full of GPUs, too!) I’m also old enough to remember similar bubbles around things like bittorrent, “4gl languages”, two or three cycles on VR, 3D TV.
This one has been different, though. There’s a viciousness to the boosters, a barely contained glee at the idea that this will put people out of work, which has been matched in intensity by the pushback. To put all that another way, when ELIZA came out, no one from MIT openly delighted at the idea that they were about to put all the therapists out of work.
But what is it about this one, though? Why did this ignite in a way that those others didn’t?
A sentiment I see a lot, as a response to AI skepticism, is to say something like “no no, this is real, it’s happening.” And the correct response to that is to say that, well, asbestos pajamas really didn’t catch fire, either. Then what happened? Just because AI is “real” it doesn’t mean it’s “good”. Those mesothelioma ads aren’t because asbestos wasn’t real.
(Again, these tend to be the same people who a few years back had a straight face when they said they were “bullish on bitcoin.”)
But I there’s another sentiment I see a lot that I think is standing behind that one: that this is the “last new tech we’ll see in our careers”. This tends to come from younger Xers & elder Millennials, folks who were just slightly too young to make it rich in the dot com boom, but old enough that they thought they were going to.
I think this one is interesting, because it illuminates part of how things have changed. From the late 70s through sometime in the 00s, new stuff showed up constantly, and more importantly, the new stuff was always better. There’s a joke from the 90s that goes like this: Two teams each developed a piece of software that didn’t run well enough on home computers. The first team spent months sweating blood, working around the clock to improve performance. The second team went and sat on a beach. Then, six months later, both teams bought new computers. And on those new machines, both systems ran great. So who did a better job? Who did a smarter job?
We all got absolutely hooked on the dopamine rush of new stuff, and it’s easy to see why; I mean, there were three extra verses of “We Didn’t Light the Fire” just in the 90s alone.
But a weird side effect is that as a culture of practitioners, we never really learned how to tell if the new thing was better than the old thing. This isn’t a new observation, Microsoft figured out to weaponize this early on as Fire And Motion. And I think this has really driven the software industry’s tendency towards “fad-oriented development,” we never built up a herd immunity to shiny new things.
A big part of this, of course, is that the press tech profoundly failed. A completely un-skeptical, overly gullible press that was infatuated shiny gadgets foisted a whole parade of con artists and scamtech on all of us, abdicating any duty they had to investigate accurately instead of just laundering press releases. The Professionally Surprised.
And for a long while, that was all okay, the occasional CueCat notwithstanding, because new stuff generally was better, and even if was only marginally better, there was often a lot of money to be made by jumping in early. Maybe not “private island” money, but at least “retire early to the foothills” money.
But then somewhere between the Dot Com Crash and the Great Recession, things slowed down. Those two events didn’t help much, but also somewhere in there “computers” plateaued at “pretty good”. Mobile kept the party going for a while, but then that slowed down too.
My Mom tells a story about being a teenager while the Beatles were around, and how she grew up in a world where every nine months pop music was reinvented, like clockwork. Then the Beatles broke up, the 70s hit, and that all stopped. And she’s pretty open about how much she misses that whole era; the heady “anything can happen” rush. I know the feeling.
If your whole identity and worldview about computers as a profession is wrapped up in diving into a Big New Thing every couple of years, it’s strange to have it settle down a little. To maintain. To have to assess. And so it’s easy to find yourself grasping for what the Next Thing is, to try and get back that feeling of the whole world constantly reinventing itself.
But missing the heyday of the PC boom isn’t the reason that AI took off. But it provides a pretty good set of excuses to cover the real reasons.
Is there a difference between “The AI” and “Robots?” I think, broadly, the answer is “no;” but they’re different lenses on the same idea. There is an interesting difference between “robot” (we built it to sit outside in the back seat of the spaceship and fix engines while getting shot at) and “the AI” (write my email for me), but that’s more about evolving stories about which is the stuff that sucks than a deep philosophical difference.
There’s a “creative” vs “mechanical” difference too. If we could build an artificial person like C-3PO I’m not sure that having it wash dishes would be the best or most appropriate possible use, but I like that as an example because, rounding to the nearest significant digit, that’s an activity no one enjoys, and as an activity it’s not exactly a hotbed of innovative new techniques. It’s the sort of chore it would be great if you could just hand off to someone. I joke this is one of the main reasons to have kids, so you can trick them into doing chores for you.
However, once “robots” went all-digital and became “the AI”, they started having access to this creative space instead of the physical-mechanical one, and the whole field backed into a moral hazard I’m not sure they noticed ahead of time.
There’s a world of difference between “better clone stamp in photoshop” and “look, we automatically made an entire website full of fake recipes to farm ad clicks”; and it turns out there’s this weird grifter class that can’t tell the difference.
Gesturing back at a century of science fiction thought experiments about robots, being able to make creative art of any kind was nearly always treated as an indicator that the robot wasn’t just “a robot.” I’ll single out Asimov’s Bicentennial Man as an early representative example—the titular robot learns how to make art, and this both causes the manufacturer to redesign future robots to prevent this happening again, and sets him on a path towards trying to be a “real person.”
We make fun of the Torment Nexus a lot, but it keeps happening—techbros keep misunderstanding the point behind the fiction they grew up on.
Unless I’m hugely misinformed, there isn’t a mass of people clamoring to wash dishes, kids don’t grow up fantasizing about a future in vacuuming. Conversely, it’s not like there’s a shortage of people who want to make a living writing, making art, doing journalism, being creative. The market is flooded with people desperate to make a living doing the fun part. So why did people who would never do that work decide that was the stuff that sucked and needed to be automated away?
So, finally: why?
I think there are several causes, all tangled.
These causes are adjacent to but not the same as the root causes of the greater enshittification—excuse me, “Platform Decay”—of the web. Nor are we talking about the largely orthogonal reasons why Facebook is full of old people being fooled by obvious AI glop. We’re interested in why the people making these AI tools are making them. Why they decided that this was the stuff that sucked.
First, we have this weird cultural stew where creative jobs are “desired” but not “desirable”. There’s a lot of cultural cachet around being a “creator” or having a “creative” jobs, but not a lot of respect for the people actually doing them. So you get the thing where people oppose the writer’s strike because they “need” a steady supply of TV, but the people who make it don’t deserve a living wage.
Graeber has a whole bit adjacent to this in Bullshit Jobs. Quoting the originating essay:
It's even clearer in the US, where Republicans have had remarkable success mobilizing resentment against school teachers, or auto workers (and not, significantly, against the school administrators or auto industry managers who actually cause the problems) for their supposedly bloated wages and benefits. It's as if they are being told ‘but you get to teach children! Or make cars! You get to have real jobs! And on top of that you have the nerve to also expect middle-class pensions and health care?’
“I made this” has cultural power. “I wrote a book,” “I made a movie,” are the sort of things you can say at a party that get people to perk up; “oh really? Tell me more!”
Add to this thirty-plus years of pressure to restructure public education around “STEM”, because those are the “real” and “valuable” skills that lead to “good jobs”, as if the only point of education was as a job training program. A very narrow job training program, because again, we need those TV shows but don’t care to support new people learning how to make them.
There’s always a class of people who think they should be able to buy anything; any skill someone else has acquired is something they should be able to purchase. This feels like a place I could put several paragraphs that use the word “neoliberalism” and then quote from Ayn Rand, The Incredibles, or Led Zeppelin lyrics depending on the vibe I was going for, but instead I’m just going to say “you know, the kind of people who only bought the Cliffs Notes, never the real book,” and trust you know what I mean. The kind of people who never learned the difference between “productivity hacks” and “cheating”.
The sort of people who only interact with books as a source of isolated nuggets of information, the kind of people who look at a pile of books and say something like “I wish I had access to all that information,” instead of “I want to read those.”
People who think money should count at least as much, if not more than, social skills or talent.
On top of all that, we have the financializtion of everything. Hobbies for their own sake are not acceptable, everything has to be a side hustle. How can I use this to make money? Why is this worth doing if I can’t do it well enough to sell it? Is there a bootcamp? A video tutorial? How fast can I start making money at this?
Finally, and critically, I think there’s a large mass of people working in software that don’t like their jobs and aren’t that great at them. I can’t speak for other industries first hand, but the tech world is full of folks who really don’t like their jobs, but they really like the money and being able to pretend they’re the masters of the universe.
All things considered, “making computers do things” is a pretty great gig. In the world of Professional Careers, software sits at the sweet spot of “amount you actually have to know & how much school you really need” vs “how much you get paid”.
I’ve said many times that I feel very fortunate that the thing I got super interested in when I was twelve happened to turn into a fully functional career when I hit my twenties. Not everyone gets that! And more importantly, there are a lot of people making those computers do things who didn’t get super interested in computers when they were twelve, because the thing they got super interested in doesn’t pay for a mortgage.
Look, if you need a good job, and maybe aren’t really interested in anything specific, or at least in anything that people will pay for, “computers”—or computer-adjacent—is a pretty sweet direction for your parents to point you. I’ve worked with more of these than I can count—developers, designers, architects, product people, project managers, middle managers—and most of them are perfectly fine people, doing a job they’re a little bored by, and then they go home and do something that they can actually self-actualize about. And I suspect this is true for a lot of “sit down inside email jobs,” that there’s a large mass of people who, in a just universe, their job would be “beach” or “guitar” or “games”, but instead they gotta help knock out front-end web code for a mid-list insurance company. Probably, most careers are like that, there’s the one accountant that loves it, and then a couple other guys counting down the hours until their band’s next unpaid gig.
But one of the things that makes computers stand out is that those accountants all had to get certified. The computer guys just needed a bootcamp and a couple weekends worth of video tutorials, and suddenly they get to put “Engineer” on their resume.
And let’s be honest: software should be creative, usually is marketed as such, but frequently isn’t. We like to talk about software development as if it’s nothing but innovation and “putting a dent in the universe”, but the real day-to-day is pulling another underwritten story off the backlog that claims to be easy but is going to take a whole week to write one more DTO, or web UI widget, or RESTful API that’s almost, but not quite, entirely unlike the last dozen of those. Another user-submitted bug caused by someone doing something stupid that the code that got written badly and shipped early couldn’t handle. Another change to government regulations that’s going to cause a remodel of the guts of this thing, which somehow manages to be a surprise despite the fact the law was passed before anyone in this meeting even started working here.
They don’t have time to learn how that regulation works, or why it changed, or how the data objects were supposed to happen, or what the right way to do that UI widget is—the story is only three points, get it out the door or our velocity will slip!—so they find someting they can copy, slap something together, write a test that passes, ship it. Move on to the next. Peel another one off the backlog. Keep that going. Forever.
And that also leads to this weird thing software has where everyone is just kind of bluffing everyone all the time, or at least until they can go look something up on stack overflow. No one really understands anything, just gotta keep the feature factory humming.
The people who actually like this stuff, who got into it because they liked making compteurs do things for their own sake keep finding ways to make it fun, or at least different. “Continuous Improvement,” we call it. Or, you know, they move on, leaving behind all those people whose twelve-year old selves would be horrified.
But then there’s the group that’s in the center of the Venn Diagram of everything above. All this mixes together, and in a certain kind of reduced-empathy individual, manifests as a fundamental disbelief in craft as a concept. Deep down, they really don’t believe expertise exists. That “expertise” and “bias” are synonyms. They look at people who are “good” at their jobs, who seem “satisfied” and are jealous of how well that person is executing the con.
Whatever they were into at twelve didn’t turn into a career, and they learned the wrong lesson from that. The kind of people who were in a band as a teenager and then spent the years since as a management consultant, and think the only problem with that is that they ever wanted to be in a band, instead of being mad that society has more open positions for management consultants than bass players.
They know which is the stuff that sucks: everything. None of this is the fun part; the fun part doesn’t even exist; that was a lie they believed as a kid. So they keep trying to build things where they don’t have to do their jobs anymore but still get paid gobs of money.
They dislike their jobs so much, they can’t believe anyone else likes theirs. They don’t believe expertise or skill is real, because they have none. They think everything is a con because thats what they do. Anything you can’t just buy must be a trick of some kind.
(Yeah, the trick is called “practice”.)
These aren’t people who think that critically about their own field, which is another thing that happens when you value STEM over everything else, and forget to teach people ethics and critical thinking.
Really, all they want to be are “Idea Guys”, tossing off half-baked concepts and surrounded by people they don’t have to respect and who wont talk back, who will figure out how to make a functional version of their ill-formed ramblings. That they can take credit for.
And this gets to the heart of whats so evil about the current crop of AI.
These aren’t tools built by the people who do the work to automate the boring parts of their own work; these are built by people who don’t value creative work at all and want to be rid of it.
As a point of comparison, the iPod was clearly made by people who listened to a lot of music and wanted a better way to do so. Apple has always been unique in the tech space in that it works more like a consumer electronics company, the vast majority of it’s products are clearly made by people who would themselves be an enthusiastic customer. In this field we talk about “eating your own dog-food” a lot, but if you’re writing a claims processing system for an insurance company, there’s only so far you can go. Making a better digital music player? That lets you think different.
But no: AI is all being built by people who don’t create, who resent having to create, who resent having to hire people who can create. Beyond even “I should be able to buy expertise” and into “I value this so little that I don’t even recognize this as a real skill”.
One of the first things these people tried to automate away was writing code—their own jobs. These people respect skill, expertise, craft so little that they don’t even respect their own. They dislike their jobs so much, and respect their own skills so little, that they can’t imagine that someone might not feel that way about their own.
A common pattern has been how surprised the techbros have been at the pushback. One of the funnier (in a laugh so you don’t cry way) sideshows is the way the techbros keep going “look, you don’t have to write anymore!” and every writer everywhere is all “ummmmm, I write because I like it, why would I want to stop” and then it just cuts back and forth between the two groups saying “what?” louder and angrier.
We’re really starting to pay for the fact that our civilization spent 20-plus years shoving kids that didn’t like programming into the career because it paid well and you could do it sitting down inside and didn’t have to be that great at it.
What future are they building for themselves? What future do they expect to live in, with this bold AI-powered utopia? Some vague middle-management “Idea Guy” economy, with the worst people in the world summoning books and art and movies out of thin air for no one to read or look at or watch, because everyone else is doing the same thing? A web full of AI slop made by and for robots trying to trick each other? Meanwhile the dishes are piling up? That’s the utopia?
I’m not sure they even know what they want, they just want to stop doing the stuff that sucks.
And I think that’s our way out of this.
What do we do?
For starters, AI Companies need to be regulated, preferably out of existence. There’s a flavor of libertarian-leaning engineer that likes to say things like “code is law,” but actually, turns out “law” is law. There’s whole swathes of this that we as a civilization should have no tolerance for; maybe not to a full Butlerian Jihad, but at least enough to send deepfakes back to the Abyss. We dealt with CFCs and asbestos, we can deal with this.
Education needs to be less STEM-focused. We need to carve out more career paths (not “jobs”, not “gigs”, “careers”) that have the benefits of tech but aren’t tech. And we need to furiously defend and expand spaces for creative work to flourish. And for that work to get paid.
But those are broad, society-wide changes. But what can those of us in the tech world actually do? How can we help solve these problems in our own little corners? We can we go into work tomorrow and actually do?
It’s on all of us in the tech world to make sure there’s less of the stuff that sucks.
We can’t do much about the lack of jobs for dance majors, but we can help make sure those people don’t stop believing in skill as a concept. Instead of assuming what we think sucks is what everyone thinks sucks, is there a way to make it not suck? Is there a way to find a person who doesn’t think it sucks? (And no, I don’t mean “Uber for writing my emails”) We gotta invite people in and make sure they see the fun part.
The actual practice of software has become deeply dehumanizing. None of what I just spent a week describing is the result of healthy people working in a field they enjoy, doing work they value. This is the challenge we have before us, how can we change course so that the tech industry doesn’t breed this. Those of us that got lucky at twelve need to find new ways to bring along the people who didn’t.
With that in mind, next Friday on Icecano we start a new series on growing better software.
Several people provided invaluable feedback on earlier iterations of this material; you all know who you are and thank you.
And as a final note, I’d like to personally apologize to the one person who I know for sure clicked Open in New Tab on every single link. Sorry man, they’re good tabs!
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.
Why is this Happening, Part I: The Stuff That Sucks
When I was a kid, I had this book called The Star Wars Book of Robots. It was a classic early-80s kids pop-science book; kids are into robots, so let’s have a book talking about what kinds of robots existed at the time, and then what kinds of robots might exist in the future. At the time, Star Wars was the spoonful of sugar to help education go down, so every page talked about a different kind of robot, and then the illustration was a painting of that kind of robot going about its day while C-3PO, R2-D2, and occasionally someone in 1970s leisureware looked on. So you’d have one of those car factory robot arms putting a sedan together while the droids stood off to the side with a sort of “when is Uncle Larry finally going to retire?” energy.
The image from that book that has stuck with me for four decades is the one at the top of this page: Threepio, trying to do the dishes while vacuuming, and having the situation go full slapstick. (As a kid, I was really worried that the soap suds were going to get into his bare midriff there and cause electrical damage, which should be all you need to know to guess exactly what kind of kid I was at 6.)
Nearly all the examples in the book were of some kind of physical labor; delivering mail, welding cars together, doing the dishes, going to physically hostile places. And at the time, this was the standard pop-culture job for robots “in the future”, that robots and robotic automation were fundamentally physical, and were about relieving humans from mechanical labor.
The message is clear: in the not to distant future we’re all going to have some kind of robotic butler or maid or handyman around the house, and that robot is going to do all the Stuff That Sucks. Dishes, chores, laundry, assorted car assembly, whatever it is you don’t want to do, the robot will handle for you.
I’ve been thinking about this a lot over the last year and change since “Generative AI” became a phrase we were all forced to learn. And what’s interesting to me is the way that the sales pitch has evolved around which is the stuff that sucks.
Robots, as a storytelling construct, have always been a thematically rich metaphor in this regard, and provide an interesting social diagnostic. You can tell a lot about what a society thinks is “the stuff that sucks” by looking at both what the robots and the people around them are doing. The work that brought us the word “robot” itself represented them as artificially constructed laborers who revolted against their creators.
Asimov’s body of work, which was the first to treat robots as something industrial and coined the term “robotics” mostly represented them as doing manual labor in places too dangerous for humans while the humans sat around doing science or supervision. But Asimov’s robots also were always shown to be smarter and more individualistic than the humans believed, and generally found a way to do what they wanted to do, regardless of the restrictions from the “Laws of Robotics.”
Even in Star Wars, which buries the political content low in the mix, it’s the droids where the dark satire from THX-1138 pokes through; robots are there as a permanent servant class doing dangerous work either on the outside of spaceships or translating for crime bosses, are the only group shown to be discriminated against, and have otherwise unambiguous “good guys” ordering mind wipes of, despite consistently being some of the smartest and most capable characters.
And then, you know, Blade Runner.
There’s a lot of social anxiety wrapped up in all this. Post-industrial revolution, the expanding middle classes wanted the same kinds of servants and “domestic staff” as the upper classes had. Wouldn’t it be nice to have a butler, a valet, some “staff?” That you didn’t have to worry about?
This is the era of Jeeves & Wooster, and who wouldn’t want a “gentleman’s gentleman” to do the work around the house, make you a hangover cure, drive the car, get you out of scrapes, all while you frittered your time away with idiot friends?
(Of course, I’m sure it’s a total coincidence this is also the period where the Marxists & Socialist thinkers really got going.)
But that stayed asperational, rather than possible, and especially post-World War II, the culture landed on sending women back home and depending on the stay-at-home mom handle “all that.”
There’s a lot of “robot butlers” in mid-century fiction, because how nice would it be if you could just go to the store and buy that robot from The Jetsons, free from any guilt? There’s a lot to unpack there, but that desire for a guilt-free servant class was, and is, persistant in fiction.
Somewhere along the lines, this changes, and robots stop being manual labor or the domestic staff, and start being secretaries, executive assistants. For example, by the time Star Trek: The Next Generation rolls around in the mid-80s, part of the fully automated luxury space communism of the Federation is that the Enterprise computer is basically the perfect secretary—making calls, taking dictation, and doing research. Even by the then it was clear that there was a whole lot of “stuff to know”, and so robots find themselves acting as research assistants. Partly, this is a narrative accelerant—having the Shakespearian actor able to ask thin air for the next plot point helps move things along pretty fast—but the anxiety about information overload was there, even then. Imagine if you could just ask somebody to look it up for you! (Star Trek as a whole is an endless Torment Nexus factory, but that’s a whole other story.)
I’ve been reading a book about the history of keyboards, and one of the more intersting side stories is the way “typing” has interacted with gender roles over the last century. For most of the 1900s, “typing” was a woman’s job, and men, who were of course the bosses, didn’t have time for that sort of tediousness. They’re Idea Guys, and the stuff that sucks is wrestling with an actual typewriter to write them down.
So, they would either handwrite things they needed typed and send it down to the “typing pool”, or dictate to a secretary, who would type it up. Typing becomes a viable job out of the house for younger or unmarried women, albeit one without an actual career path.
This arrangement lasted well into the 80s, and up until then the only men who typed themselves were either writers or nerds. Then computers happened, PCs landed on men’s desks, and it turns out the only thing more powerful than sexism was the desire to cut costs, so men found themselves typing their own emails. (Although, this transition spawns the most unwittingly enlightening quote in the whole book, where someone who was an executive at the time of the transition says it didn’t really matter, because “Feminism ruined everything fun about having a secretary”. pikachu shocked face dot gif)
But we have a pattern; work that would have been done by servants gets handed off to women, and then back to men, and then fiction starts showing up fantasizing about giving that work to a robot, who won’t complain, or have an opinion—or start a union.
Meanwhile, in parallel with all this “chat bots” have been cooking along for as long as there have been computers. Typing at a computer and getting a human-like response was an obvious interface, and spawned a whole set of thought similar but adjacent to all those physical robots. ELIZA emerged almost as soon as computers were able to support such a thing. The Turing test assumes a chat interface. “Software Agents” become a viable area of research. The Infocom text adventure parser came out of the MIT AI lab. What if your secretary was just a page of text on your screen?
One of the ways that thread evolved emerged as LLMs and “Generative AI”. And thanks to the amount of VC being poured in, we get the last couple of years of AI slop. And also a hype cycle that says that any tech company that doesn’t go all-in on “the AI” is going to be left in the dust. It’s the Next Big Thing!
Flash forward to Apple’s Worldwide Developer Conference earlier this summer. The Discourse going into WWDC was that Apple was “behind on AI” and needed to catch up to the industry, although does it really count as behind if all your competitors are up over their skis? And so far AI has been extremely unprofitable, and if anything, Apple is a company that only ships products it knows it can make money on.
The result was that they rolled out the most comprehensive vision of how a Gen AI–powered product suite looks here in 2024. In many ways, “Apple Intelligence” was Apple doing what they do best—namely, doing their market research via letting their erstwhile competitors skid into a ditch, and then slide in with a full Second Mover Advantage by saying “so, now do you want something that works?”
They’re very, very good at identifying The Stuff That Sucks, and announcing that they have a solution. So what stuff was it? Writing text, sending pictures, communicating with other people. All done by a faceless, neutral, “assistant,” who you didn’t have to engage with like they were a person, just a fancy piece of software. Computer! Tea, Earl Gray! Hot!
I’m writing about a marketing event from months ago because watching their giant infomercial was where something clicked for me. They spent an hour talking about speed, “look how much faster you can do stuff!” “You don’t have to write your own text, draw your own pictures, send your own emails, interact directly with anyone!”
Left unsaid was what you were saving all that time for. Critically, they didn’t annouce they were going to a 4-day work week or 6-hour days, all this AI was so people could do more “real work”. Except that the “stuff that sucks” was… that work? What’s the vision of what we’ll be doing when we’ve handed off all this stuff that sucks?
Who is building this stuff? What future do they expect to live in, with this bold AI-powered economy? What are we saving all this time for? What future do these people want? Why are these the things they have decided suck?
I was struck, not for the first time, by what a weird dystopia we find ourselves in: “we gutted public education and non-STEM subjects like writing and drawing, and everyone is so overworked they need a secretary but can’t afford one, so here’s a robot!”
To sharpen the point: why in the fuck am I here doing the dishes myself while a bunch of techbros raise billions of dollars to automate the art and poetry? What happened to Threepio up there? Why is this the AI that’s happening?
On Wednesday, we start kicking over rocks to find an answer...
There we go: Harris/Walz 24
Candidate swap complete. Okay, I’m convinced. Let’s go win this thing.
The party conventions are always a sales event—they’re the political versions of those big keynotes Apple does—but this one was remarkably well put-together, probably the best of my lifetime, which is especially insane considering they had to swap candidates only four weeks ago. I’m acting like Belle’s father from Beauty and the Beast, just staring at it asking “how is this accomplished?” I’m really looking forward to next summer’s deluge of tell-all behind-the-scenes books, explaining how in the heck they pulled any of this off.
This bit from Josh Marshall’s piece on the final night stuck with me:
What I took from this is a sense of focus and discipline from the people running Harris’ convention and campaign — not getting lost in glitz or stagecraft but defining a specific list of critical deliverables and then methodically checking them off the list. This was going on in the midst of what was unquestionably a high-powered and high-energy event. There was a mix of discipline and ability there that could not fail to have an impact but was also, in the intensity of the final day of a convention, easy to miss.
The other nights had some of this too. But it came through to me most clearly tonight.
I continue to think there’s more going on in this campaign than much of the political and commenting class has yet understood or reckoned with.
There’s a thing going on here that’s not just a “honeymoon phase” after a surprise switch-up. Personally, I think a big part is the Dem’s long overdue embrace of being the “regular people” party, but critically, without a self-destructive “pivot to the center.” In the US “The Center”, like “libertarian” is just a code word for a republican who smokes weed and doesn’t openly hate the gays. For ages now the Dems have surrendered so much American iconography—camo, flags, guns, the entire midwest—and it’s incredibly refreshing to see the Dems openly embrace all that “Real America” stuff, leaving the Repubs with nothing but looking like the creepy weirdo loosers they are.
I tend to think of the Democrats as, effectively, a British-style coalition, just without the framework the parliamentary system provides of actually having each member party having a public number of seats. Instead the factions are fluid and more obscure. Which makes intra-party negotiations hard even in better times, and even more so when the “other side” isn’t a coalition and is full of wannabe petty dictators. From the outside, and probably from the inside, it’s hard to tell how the various factions are doing versus each other.
There are, bluntly, a lot of issues that just aren’t on the ballot this year, which for whatever reason have fallen outside of the contextual Overton window of the ’24 election. The lack of formal coalition dynamics makes those so frustrating; there’s no way to know how close they were to being on the ballot. And, of course, the reason I keep calling this a “harm reduction” election is that for those about six things I’m subtweeting, the other side would be an absolute catastrophe. And that’s before we remember that the baseline of the opponents here really is “…or fascism.”
That said, it’s such a relief to see that the party seems to have finally shook off the Clinton/Blair era “Third Way” hangover and landed in a much more progressive place than I’d have ever hoped a few years ago. This feels like a group that would have held the banks accountable, for starters?
The first Bill Clinton campaign is the one this keeps making me think of, that explicit sense of “the old ways failed, here comes the new generation.” (Speaking of, can you imagine how hard Harris would kill on the old Arsenio show? For that matter, how hard Walz would?)
But more than any of that, this is a campaign and a candiate that’s here to play None of this gingerly hoping “we can finally talk about policy,” this a group that’s solidly on the offensive and staying there. The Dem’s traditional move has been to blow what should have been easy wins (looking at you 2000 and 2016) mostly by wrecking out the campaign to chase votes they were never going to get, or because actually trying to win power was beneath them somehow. Not this time. Non-MAGA America is deeply, profoundly sick of those assholes, and Harris has really captured the desire to move on as a country.
Finally!
In any case, we’re really though the looking glass now. No one has any idea what’s going to happen. Yeah, I saw that poll, and yes that one, and that one. We’re so far outside the lines I don’t think any of those mean anything we can interpret with the data we have. At this point, anybody who says what they think is going to happen without ending the sentence with a question mark is lying.
To quote Doctor Who: “Oh, knowing's easy. Everyone does that ad nauseam. I just sort of hope."
Further Exciting Consulting Opportunitues
I am expanding the offerings of my consulting company,we now offer a second service, which is this:
When someone is making, say, an eight season of a tv show for a streaming service, they can come to me and tell me what events will take place in those eight episodes. And then I will say,
“That is four episodes, max. What do ya got lying around that you’re saving for the second season? Let’s jam that in there too.”
“White Guy Tacos”
I just want to say that as a white guy with laughably-low spice tolerance, I never expected my demographic to be represented in a major national election, much less dominate a news cycle?
This is our time, fellow spice-phobes! You love to see it.
Feature Request: I Already Know That Part, Siri
I live pretty close to a major interstate highway. If you stand in the right place in my backyard, you can see the trucks! But, thanks to the turn-of-the-century suburb I live in, it’s at least 5 “turns” to get from my house to the freeway. I also live in one of those cities that’s a major freeway confluence, which means I’m another 2 or 3 “turns” away from at least 5 different numbered freeways?
So of course, when I need directions from Apple Maps (or any other nav system,) Siri very patiently explains how to get from my house to the freeway, which, yes Siri, I know that part.
I wish there was a way to mark an area on the the map as “look, I grew up here, I got this.” I wish, when I’m driving out to the mountains or whatever, Siri would start with “Get on I-5 south, I’ll be back with you in half an hour.” I want to be able to tell it “no, look, I know all these turns, I just want you to tell me when we’re at the destination so I don’t drive past the weird driveway again.” That’s an Apple Intelligence feature I’d be impressed by.
This Adam Savage Video
The YouTube algorithm has decided that what I really want to watch are Adam Savage videos, and it turns out the robots are occasionally right? So, I’d like to draw your attention to this vid where Adam answers some user questions: Were Any Myths Deemed Too Simple to Test on MythBusters?
It quickly veers moderately off-topic, and gets into a the weeds on what kinds of topics MythBusters tackled and why. You should go watch it, but the upshot is that MythBusters never wanted to invite someone on just to make them look bad or do a gotcha, so there was a whole class of “debunking” topics they didn’t have a way in on; the example Adam cites is dowsing, because there’s no way to do an episode busting dowsing without having a dowser on to debunk.
And this instantly made clear to me why I loved MythBusters but couldn’t stand Penn & Teller’s Bullshit!. The P&T Show was pretty much an extended exercise in “Look at this Asshole”, and was usually happy to stop there. MythBusters was never interested in looking at assholes.
And, speaking of Adam Savage, did I ever link to the new Bobby Fingers?
This is relevant because it’s a collaboration with Adam Savage, and the Slow Mo Guys, who also posted their own videos on the topic:
Shooting Ballistic Gel Birds at Silicone Fabio with @bobbyfingers and @theslowmoguys!
75mph Bird to the Face with Adam Savage (@tested) and @bobbyfingers - The Slow Mo Guys
It’s like a youtube channel Rashomon, it’s great.
On Enthusiasm
Remember Howard Dean? Ran for president in 2004. Had huge grassroots support, got “the kids” really excited, and then got too excited in public, and went home to let Kerry lose the election.
I always thought the media kerfluffle around the “Dean Scream” was bizarre. Years later I saw a documentary where he was interviewed, about the election and other things, and he came across as sane, thoughtful, charismatic. Afterwards, he was a tremendously successful head of the nation party apparatus. Towards the end, the interviewer asked him if he’d do “the scream”, and he refused. Seemed embarrassed by the idea, kinda pissed the interviewer would bring it up. Oh, I thought, this is why you lost the election. You have a brief moment of actual personality in public, it’s still the thing you’re the most known for, and even now you can’t bring yourself to embrace it.
The Dems, at least for the last 20–30 years, have had a strange aversion to “enthusiasm”, treating it as somehow low-class or embarrassing. I guess this partly their self-identity as the “adults in the room,” and partly a reaction to looking over at Reagan and saying “screaming crowds are the thing the other guys do”.
So the guy in ’04 who has the kids all excited allows the media to shame him out of the race for being excited. And clearly he was actually embarrassed, based on that interview. He should have leaned into it, made that his thing. Opened every event with that yell, get a call and response going. Instead, nope, we’re gonna let the most boring man in the world lose the election to the war criminal running on ending social security.
And of course, the really maddeningly weird thing is that the Dem base is much more purpose-driven, more emotionally-connected to outcomes. They’re the ones who will stay home unless you fire them up! The main opponent has always been apathy!
So the Dems that win are (mostly) charismatic outsiders, whereas the party wants to run “grownups.” So you have Gore, who runs basically as a robot, and then as soon as he loses shows up on Futurama and is incredibly funny. Remember how scandalized the other Dems were by Clinton playing the sax on Arsenio? I think this was one of the dynamics that fueled the Bernie-Clinton feud too; somehow the Dems though people yelling “Bernie or bust” meant he wasn’t electable?
I suspect this is mostly a generational thing. The batch of boomer-age Dems that have been running the show the last 30 years have always treated “people being excited” as not grown up enough. And fair enough, if you grew up in the 50s & 60s, there was a very, very limited number of things you were allowed to “like” or express feeling about; maybe sports? Otherwise, stoicism was the goal. Maybe because an entire generation grew up with parents who had undiagnosed PTSD?
The younger generations aren’t like that? Or at the very least, have a different set of “things you’re allowed to be excited about” and aren’t fundamentally embarrassed by the concept of “excitement” or “emoting”. So those people start being in charge, and they’re like, no actually, stoicism isn’t the goal, let’s get the base fired up. Which turns out to be really valuable when the opponent isn’t “the other guy” but “staying home”?
Anyway, my Hot Take is that Harris/Walz is what you get when the Dems stop treating “enthusiasm” as something low class and embarrassing.
More than anything, Biden had a vibes problem; I see that Harris is now polling ahead of the convicted felon/ failed businessperson on “the economy”, as opposed to Biden who was well behind. It’s the same economy! Same administration! Same failed casinos! Vibes issue.
Being “the grown ups” meant being reactive, trying to stick to “serious topics”, with the result being that the other side gets to dictate the terms of the fight and then ground you down over a year(s)-long campaign.
But now we’ve got a team actually trying to fire up the base, setting the terms, taking the initiative. Part of why “mind you own damn business” has popped so hard as a campaign theme is that this is the kind of topic everyone actually cares about and has wanted a Dem to run on since forever, instead of the finer points of NATO funding or whatever.
This really does feel like a campaign run by people who at a critical age, instead of watching Mr Smith goes to Washington, watched Heathers. As they say, let’s not go back.
Apple vs Games
Apple Arcade is in the news again, for not great reasons; as always, Tsai has the roundup, the but the short, short version is that Arcade is going exactly as well as all of Apple’s other video game–related efforts have gone for the last “since forever.”
My first take was that games might be the most notable place Apple’s “one guy at the top” structure falls down. Apple’s greatest strength and greatest weakness has always been that the whole company is laser focused on whatever the guy in charge cares about, and not much of anything else. Currently, that means that Apple’s priorities are, in no particular order, privacy, health, thin devices, operational efficiency, and, I guess, becoming “the new HBO.” Games aren’t anywhere near that list, and never have been. I understand the desire to keep everything flowing through one central point, and not to have siloed-off business units or what have you. On the other hand Bill Gates wasn’t a gamer either, but he knew to hire someone to be in charge of X-everything and leave them alone.
But then I remembered AppleTV+. Somehow, in a very short amount of time, Apple figured out how to be a production company, and made Ted Lasso, a new Fraggle Rock, some new Peanuts, and knocked out a Werner Herzog documentary for good measure. I refuse to believe that happened because Tim Apple was signing off on every production decision or script; they found the right people and enabled them correctly.
At this point, there’s just no excuse why AppleTV has something like Ted Lasso, and Apple Arcade doesn’t. There’s obvious questions like “why did I play Untitled Goose Game on my Switch instead of my Mac” and “why did they blow acquiring Bungie twice”. Why isn’t the Mac the premier game platform? Why? What’s the malfunction?
Meet the Veep
And there we go, it’s Walz. Personally, I was hoping for Mayor Pete, but as Elizabeth Sandifer says: “…when you create the campaign's new messaging strategy you get to be the VP nom.". I love that he’s a regular guy in the way that’s the exact opposite of what we use the word “weird” as a shorthand for.
The Dems claiming the title of the party of regular, normal, non-crazy people is long overdue; this is a note they should have been playing since at least the Tea Party, and probably since Gingrich. But, like planting a tree, the second best time is now, and Walz’s midwestern cool dad energy is the perfect counterpoint to the Couch Experience.
“Both sides are the same” is right-wing propganda designed to reduce voter turnout, but the Dems don’t always run a ticket that makes it easy to dispute. What I like about the Harris/Walz vs Trump/Vance race is that the differences are clear, even at a distance. What future do you want, America?
As I keep saying, this is a “turn out the base” election; everyone already knows which side they’d vote for, and the trick is to get them to think it’s worth it to bother to vote. Each candidate is running against apathy, not each other. Fairly or not, over the summer the Democrats found themselves with a substantial enthusiasm gap. The Repubs didn’t have a huge amount of enthusiasm either, but the reality is the members of the Republican coalition are more likely to show up and vote for someone they don’t like than the Dems, so structurally thats the sort of thing that hurts Team Blue more.
Literally no one wanted to do the 2020 election over again, and in one of those bizarre unfair moments America decided to blame Biden for it, instead of blaming the guy who lost for not staying down. But more than that, complaining about how “old” everyone was also a shorthand for something else—all the actors here are people who’ve been around since the 80s. We just keep re-litigating the ghosts of the 20th century. Obama felt like the moment we were finally done having elections rooted in how the Boomers felt about Nixon, but then, no, another three cycles made up entirely of people who’ve been household names since Cheers was on the air.
And then Harris crashes into the race at the last second with an “oh yeaaahhhh!” Suddenly, we’ve got something new. This finally feels like not just a properly post-Obama ticket, but actually post “The Third Way”; both in terms of policy and attitude this is the campaign the Dems should have been running every election in the 21st century. And for once, the Dems aren’t just trying to score points with some hypothetical ref and win on technicals, they’re here to actually win. Finally.
I’m as surprised as anyone at the amount of excitement that’s built up over the last two weeks; I was sure swapping candidates was an own-goal for the ages, but now I’m sure I was wrong.
Rooting for the winning team is fun, and the team with the initiative and hustle is usually the one that wins. It’s self-perpetuating, in both directions. (This is a big part of how Trump managed to stumble into a win in ’16, it was a weird feedback loop of him doing something insane and then everyone else going “hahaha what” and all that kept building on itself until he was suddenly the President.)
Accurately or not, the Dems had talked themselves into believing they were going to lose, and were acting like it. Now, not so much! The feedback loops are building the other way, and as Harris keeps picking up more support, you can see the air bleeding out of Trump’s tires as his support drifts away because he’s only fun when he’s winning.
I have a conceptual model that I use for US Presidential elections that has very rarely let me down. It goes like this: every cycle the Republicans run someone who reads as a Boss, and the Democrats run someone who reads as a college Professor. And so most elections turn into a contest between the worst boss you’ve ever had against your least favorite teacher; with the final decision boiling down to, basically, “would you rather work for this guy or take a class from that guy”. (Often leading to a frustrated “bleah, neither!”)
And elections pretty consistently go to the team that wins that comparison. As a historical example, I liked Gore a lot, but he really had the quality that he’d grade you down on a paper because he thought you used an em dash wrong when you didn’t, whereas W (war crimes notwithstanding) seemed like the kind of boss that wouldn’t hassle you too bad and would throw a great summer BBQ. And occasionally one side or the other pops a good one—Obama seemed like he’d be your favorite law professor of all time.
Viewing this ticket via that lens? This one I like. We have the worst boss you can imagine running with the worst coworker you’ve ever had, against literally the cool geography teacher/football coach and the lady that seems like she’d be your new favorite professor? Hell yeah. I’m sold. Let’s do this.