#big store con

[mostlysignssomeportents]

Tiktok's enshittification

Here is how platforms die: first, they are good to their users; then they abuse their users to make things better for their business customers; finally, they abuse those business customers to claw back all the value for themselves. Then, they die.

If you’d like an essay-formatted version of this post to read or share, here’s a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/01/21/potemkin-ai/#hey-guys

I call this enshittification, and it is a seemingly inevitable consequence arising from the combination of the ease of changing how a platform allocates value, combined with the nature of a “two sided market,” where a platform sits between buyers and sellers, hold each hostage to the other, raking off an ever-larger share of the value that passes between them.

When a platform starts, it needs users, so it makes itself valuable to users. Think of Amazon: for many years, it operated at a loss, using its access to the capital markets to subsidize everything you bought. It sold goods below cost and shipped them below cost. It operated a clean and useful search. If you searched for a product, Amazon tried its damndest to put it at the top of the search results.

This was a hell of a good deal for Amazon’s customers. Lots of us piled in, and lots of brick-and-mortar retailers withered and died, making it hard to go elsewhere. Amazon sold us ebooks and audiobooks that were permanently locked to its platform with DRM, so that every dollar we spent on media was a dollar we’d have to give up if we deleted Amazon and its apps. And Amazon sold us Prime, getting us to pre-pay for a year’s worth of shipping. Prime customers start their shopping on Amazon, and 90% of the time, they don’t search anywhere else.

That tempted in lots of business customers — Marketplace sellers who turned Amazon into the “everything store” it had promised from the beginning. As these sellers piled in, Amazon shifted to subsidizing suppliers. Kindle and Audible creators got generous packages. Marketplace sellers reached huge audiences and Amazon took low commissions from them.

This strategy meant that it became progressively harder for shoppers to find things anywhere except Amazon, which meant that they only searched on Amazon, which meant that sellers had to sell on Amazon.

That’s when Amazon started to harvest the surplus from its business customers and send it to Amazon’s shareholders. Today, Marketplace sellers are handing 45%+ of the sale price to Amazon in junk fees. The company’s $31b “advertising” program is really a payola scheme that pits sellers against each other, forcing them to bid on the chance to be at the top of your search.

Searching Amazon doesn’t produce a list of the products that most closely match your search, it brings up a list of products whose sellers have paid the most to be at the top of that search. Those fees are built into the cost you pay for the product, and Amazon’s “Most Favored Nation” requirement sellers means that they can’t sell more cheaply elsewhere, so Amazon has driven prices at every retailer.

Search Amazon for “cat beds” and the entire first screen is ads, including ads for products Amazon cloned from its own sellers, putting them out of business (third parties have to pay 45% in junk fees to Amazon, but Amazon doesn’t charge itself these fees). All told, the first five screens of results for “cat bed” are 50% ads.

https://pluralistic.net/2022/11/28/enshittification/#relentless-payola

This is enshittification: surpluses are first directed to users; then, once they’re locked in, surpluses go to suppliers; then once they’re locked in, the surplus is handed to shareholders and the platform becomes a useless pile of shit. From mobile app stores to Steam, from Facebook to Twitter, this is the enshittification lifecycle.

This is why — as Cat Valente wrote in her magesterial pre-Christmas essay — platforms like Prodigy transformed themselves overnight, from a place where you went for social connection to a place where you were expected to “stop talking to each other and start buying things”:

https://catvalente.substack.com/p/stop-talking-to-each-other-and-start

This shell-game with surpluses is what happened to Facebook. First, Facebook was good to you: it showed you the things the people you loved and cared about had to say. This created a kind of mutual hostage-taking: once a critical mass of people you cared about were on Facebook, it became effectively impossible to leave, because you’d have to convince all of them to leave too, and agree on where to go. You may love your friends, but half the time you can’t agree on what movie to see and where to go for dinner. Forget it.

Then, it started to cram your feed full of posts from accounts you didn’t follow. At first, it was media companies, who Facebook preferentially crammed down its users’ throats so that they would click on articles and send traffic to newspapers, magazines and blogs.

Then, once those publications were dependent on Facebook for their traffic, it dialed down their traffic. First, it choked off traffic to publications that used Facebook to run excerpts with links to their own sites, as a way of driving publications into supplying fulltext feeds inside Facebook’s walled garden.

This made publications truly dependent on Facebook — their readers no longer visited the publications’ websites, they just tuned into them on Facebook. The publications were hostage to those readers, who were hostage to each other. Facebook stopped showing readers the articles publications ran, tuning The Algorithm to suppress posts from publications unless they paid to “boost” their articles to the readers who had explicitly subscribed to them and asked Facebook to put them in their feeds.

Now, Facebook started to cram more ads into the feed, mixing payola from people you wanted to hear from with payola from strangers who wanted to commandeer your eyeballs. It gave those advertisers a great deal, charging a pittance to target their ads based on the dossiers of nonconsensually harvested personal data they’d stolen from you.

Sellers became dependent on Facebook, too, unable to carry on business without access to those targeted pitches. That was Facebook’s cue to jack up ad prices, stop worrying so much about ad fraud, and to collude with Google to rig the ad market through an illegal program called Jedi Blue:

https://en.wikipedia.org/wiki/Jedi_Blue

Today, Facebook is terminally enshittified, a terrible place to be whether you’re a user, a media company, or an advertiser. It’s a company that deliberately demolished a huge fraction of the publishers it relied on, defrauding them into a “pivot to video” based on false claims of the popularity of video among Facebook users. Companies threw billions into the pivot, but the viewers never materialized, and media outlets folded in droves:

https://slate.com/technology/2018/10/facebook-online-video-pivot-metrics-false.html

But Facebook has a new pitch. It claims to be called Meta, and it has demanded that we live out the rest of our days as legless, sexless, heavily surveilled low-poly cartoon characters.

It has promised companies that make apps for this metaverse that it won’t rug them the way it did the publishers on the old Facebook. It remains to be seen whether they’ll get any takers. As Mark Zuckerberg once candidly confessed to a peer, marvelling at all of his fellow Harvard students who sent their personal information to his new website “TheFacebook”:

> I don’t know why.

> They “trust me”

> Dumb fucks.

https://doctorow.medium.com/metaverse-means-pivot-to-video-adbe09319038

Once you understand the enshittification pattern, a lot of the platform mysteries solve themselves. Think of the SEO market, or the whole energetic world of online creators who spend endless hours engaged in useless platform Kremlinology, hoping to locate the algorithmic tripwires, which, if crossed, doom the creative works they pour their money, time and energy into:

https://pluralistic.net/2022/04/11/coercion-v-cooperation/#the-machine-is-listening

Working for the platform can be like working for a boss who takes money out of every paycheck for all the rules you broke, but who won’t tell you what those rules are because if he told you that, then you’d figure out how to break those rules without him noticing and docking your pay. Content moderation is the only domain where security through obscurity is considered a best practice:

https://doctorow.medium.com/como-is-infosec-307f87004563

The situation is so dire that organizations like Tracking Exposed have enlisted an human army of volunteers and a robot army of headless browsers to try to unwind the logic behind the arbitrary machine judgments of The Algorithm, both to give users the option to tune the recommendations they receive, and to help creators avoid the wage theft that comes from being shadow banned:

https://www.eff.org/deeplinks/2022/05/tracking-exposed-demanding-gods-explain-themselves

But what if there is no underlying logic? Or, more to the point, what if the logic shifts based on the platform’s priorities? If you go down to the midway at your county fair, you’ll spot some poor sucker walking around all day with a giant teddy bear that they won by throwing three balls in a peach basket.

The peach-basket is a rigged game. The carny can use a hidden switch to force the balls to bounce out of the basket. No one wins a giant teddy bear unless the carny wants them to win it. Why did the carny let the sucker win the giant teddy bear? So that he’d carry it around all day, convincing other suckers to put down five bucks for their chance to win one:

https://boingboing.net/2006/08/27/rigged-carny-game.html

The carny allocated a giant teddy bear to that poor sucker the way that platforms allocate surpluses to key performers — as a convincer in a “Big Store” con, a way to rope in other suckers who’ll make content for the platform, anchoring themselves and their audiences to it.

Which brings me to Tiktok. Tiktok is many different things, including “a free Adobe Premiere for teenagers that live on their phones.”

https://www.garbageday.email/p/the-fragments-of-media-you-consume

But what made it such a success early on was the power of its recommendation system. From the start, Tiktok was really, really good at recommending things to its users. Eerily good:

https://www.npr.org/transcripts/1093882880

By making good-faith recommendations of things it thought its users would like, Tiktok built a mass audience, larger than many thought possible, given the death grip of its competitors, like Youtube and Instagram. Now that Tiktok has the audience, it is consolidating its gains and seeking to lure away the media companies and creators who are still stubbornly attached to Youtube and Insta.

Yesterday, Forbes’s Emily Baker-White broke a fantastic story about how that actually works inside of Bytedance, Tiktok’s parent company, citing multiple internal sources, revealing the existence of a “heating tool” that Tiktok employees use push videos from select accounts into millions of viewers’ feeds:

https://www.forbes.com/sites/emilybaker-white/2023/01/20/tiktoks-secret-heating-button-can-make-anyone-go-viral/

These videos go into Tiktok users’ ForYou feeds, which Tiktok misleadingly describes as being populated by videos “ranked by an algorithm that predicts your interests based on your behavior in the app.” In reality, For You is only sometimes composed of videos that Tiktok thinks will add value to your experience — the rest of the time, it’s full of videos that Tiktok has inserted in order to make creators think that Tiktok is a great place to reach an audience.

“Sources told Forbes that TikTok has often used heating to court influencers and brands, enticing them into partnerships by inflating their videos’ view count. This suggests that heating has potentially benefitted some influencers and brands — those with whom TikTok has sought business relationships — at the expense of others with whom it has not.”

In other words, Tiktok is handing out giant teddy bears.

But Tiktok is not in the business of giving away giant teddy bears. Tiktok, for all that its origins are in the quasi-capitalist Chinese economy, is just another paperclip-maximizing artificial colony organism that treats human beings as inconvenient gut flora. Tiktok is only going to funnel free attention to the people it wants to entrap until they are entrapped, then it will withdraw that attention and begin to monetize it.

“Monetize” is a terrible word that tacitly admits that there is no such thing as an “Attention Economy.” You can’t use attention as a medium of exchange. You can’t use it as a store of value. You can’t use it as a unit of account. Attention is like cryptocurrency: a worthless token that is only valuable to the extent that you can trick or coerce someone into parting with “fiat” currency in exchange for it. You have to “monetize” it — that is, you have to exchange the fake money for real money.

In the case of cryptos, the main monetization strategy was deception-based. Exchanges and “projects” handed out a bunch of giant teddy-bears, creating an army of true-believer Judas goats who convinced their peers to hand the carny their money and try to get some balls into the peach-basket themselves.

But deception only produces so much “liquidity provision.” Eventually, you run out of suckers. To get lots of people to try the ball-toss, you need coercion, not persuasion. Think of how US companies ended the defined benefits pension that guaranteed you a dignified retirement, replacing it with market-based 401(k) pensions that forced you to gamble your savings in a rigged casino, making you the sucker at the table, ripe for the picking:

https://pluralistic.net/2020/07/25/derechos-humanos/#are-there-no-poorhouses

Early crypto liquidity came from ransomware. The existence of a pool of desperate, panicked companies and individuals whose data had been stolen by criminals created a baseline of crypto liquidity because they could only get their data back by trading real money for fake crypto money.

The next phase of crypto coercion was Web3: converting the web into a series of tollbooths that you could only pass through by trading real money for fake crypto money. The internet is a must-have, not a nice-to-have, a prerequisite for full participation in employment, education, family life, health, politics, civics, even romance. By holding all those things to ransom behind crypto tollbooths, the hodlers hoped to convert their tokens to real money:

https://locusmag.com/2022/09/cory-doctorow-moneylike/

For Tiktok, handing out free teddy-bears by “heating” the videos posted by skeptical performers and media companies is a way to convert them to true believers, getting them to push all their chips into the middle of the table, abandoning their efforts to build audiences on other platforms (it helps that Tiktok’s format is distinctive, making it hard to repurpose videos for Tiktok to circulate on rival platforms).

Once those performers and media companies are hooked, the next phase will begin: Tiktok will withdraw the “heating” that sticks their videos in front of people who never heard of them and haven’t asked to see their videos. Tiktok is performing a delicate dance here: there’s only so much enshittification they can visit upon their users’ feeds, and Tiktok has lots of other performers they want to give giant teddy-bears to.

Tiktok won’t just starve performers of the “free” attention by depreferencing them in the algorithm, it will actively punish them by failing to deliver their videos to the users who subscribed to them. After all, every time Tiktok shows you a video you asked to see, it loses a chance to show you a video it wants you to see, because your attention is a giant teddy-bear it can give away to a performer it is wooing.

This is just what Twitter has done as part of its march to enshittification: thanks to its “monetization” changes, the majority of people who follow you will never see the things you post. I have ~500k followers on Twitter and my threads used to routinely get hundreds of thousands or even millions of reads. Today, it’s hundreds, perhaps thousands.

I just handed Twitter $8 for Twitter Blue, because the company has strongly implied that it will only show the things I post to the people who asked to see them if I pay ransom money. This is the latest battle in one of the internet’s longest-simmering wars: the fight over end-to-end:

https://pluralistic.net/2022/12/10/e2e/#the-censors-pen

In the beginning, there were Bellheads and Netheads. The Bellheads worked for big telcos, and they believed that all the value of the network rightly belonged to the carrier. If someone invented a new feature — say, Caller ID — it should only be rolled out in a way that allows the carrier to charge you every month for its use. This is Software-As-a-Service, Ma Bell style.

The Netheads, by contrast, believed that value should move to the edges of the network — spread out, pluralized. In theory, Compuserve could have “monetized” its own version of Caller ID by making you pay $2.99 extra to see the “From:” line on email before you opened the message — charging you to know who was speaking before you started listening — but they didn’t.

The Netheads wanted to build diverse networks with lots of offers, lots of competition, and easy, low-cost switching between competitors (thanks to interoperability). Some wanted this because they believed that the net would someday be woven into the world, and they didn’t want to live in a world of rent-seeking landlords. Others were true believers in market competition as a source of innovation. Some believed both things. Either way, they saw the risk of network capture, the drive to monetization through trickery and coercion, and they wanted to head it off.

They conceived of the end-to-end principle: the idea that networks should be designed so that willing speakers’ messages would be delivered to willing listeners’ end-points as quickly and reliably as they could be. That is, irrespective of whether a network operator could make money by sending you the data it wanted to receive, its duty would be to provide you with the data you wanted to see.

The end-to-end principle is dead at the service level today. Useful idiots on the right were tricked into thinking that the risk of Twitter mismanagement was “woke shadowbanning,” whereby the things you said wouldn’t reach the people who asked to hear them because Twitter’s deep state didn’t like your opinions. The real risk, of course, is that the things you say won’t reach the people who asked to hear them because Twitter can make more money by enshittifying their feeds and charging you ransom for the privilege to be included in them.

As I said at the start of this essay, enshittification exerts a nearly irresistible gravity on platform capitalism. It’s just too easy to turn the enshittification dial up to eleven. Twitter was able to fire the majority of its skilled staff and still crank the dial all the way over, even with a skeleton crew of desperate, demoralized H1B workers who are shackled to Twitter’s sinking ship by the threat of deportation.

The temptation to enshittify is magnified by the blocks on interoperability: when Twitter bans interoperable clients, nerfs its APIs, and periodically terrorizes its users by suspending them for including their Mastodon handles in their bios, it makes it harder to leave Twitter, and thus increases the amount of enshittification users can be force-fed without risking their departure.

Twitter is not going to be a “protocol.” I’ll bet you a testicle¹ that projects like Bluesky will find no meaningful purchase on the platform, because if Bluesky were implemented and Twitter users could order their feeds for minimal enshittification and leave the service without sacrificing their social networks, it would kill the majority of Twitter’s “monetization” strategies.

¹Not one of mine.

An enshittification strategy only succeeds if it is pursued in measured amounts. Even the most locked-in user eventually reaches a breaking-point and walks away, or gets pushed. The villagers of Anatevka in Fiddler on the Roof tolerated the cossacks' violent raids and pogroms for years, until they were finally forced to flee to Krakow, New York and Chicago:

https://doctorow.medium.com/how-to-leave-dying-social-media-platforms-9fc550fe5abf

For enshittification-addled companies, that balance is hard to strike. Individual product managers, executives, and activist shareholders all give preference to quick returns at the cost of sustainability, and are in a race to see who can eat their seed-corn first. Enshittification has only lasted for as long as it has because the internet has devolved into “five giant websites, each filled with screenshots of the other four”:

https://twitter.com/tveastman/status/1069674780826071040

With the market sewn up by a group of cozy monopolists, better alternatives don’t pop up and lure us away, and if they do, the monopolists just buy them out and integrate them into your enshittification strategies, like when Mark Zuckerberg noticed a mass exodus of Facebook users who were switching to Instagram, and so he bought Instagram. As Zuck says, “It is better to buy than to compete.”

This is the hidden dynamic behind the rise and fall of Amazon Smile, the program whereby Amazon gave a small amount of money to charities of your choice when you shopped there, but only if you used Amazon’s own search tool to locate the products you purchased. This provided an incentive for Amazon customers to use its own increasingly enshittified search, which it could cram full of products from sellers who coughed up payola, as well as its own lookalike products. The alternative was to use Google, whose search tool would send you directly to the product you were looking for, and then charge Amazon a commission for sending you to it:

https://www.reddit.com/r/technology/comments/10ft5iv/comment/j4znb8y/

The demise of Amazon Smile coincides with the increasing enshittification of Google Search, the only successful product the company managed to build in-house. All its other successes were bought from other companies: video, docs, cloud, ads, mobile; while its own products are either flops like Google Video, clones (Gmail is a Hotmail clone), or adapted from other companies’ products, like Chrome.

Google Search was based on principles set out in founder Larry Page and Sergey Brin’s landmark 1998 paper, “Anatomy of a Large-Scale Hypertextual Web Search Engine,” in which they wrote, “Advertising funded search engines will be inherently biased towards the advertisers and away from the needs of consumers.”

http://ilpubs.stanford.edu:8090/361/

Even with that foundational understanding of enshittification, Google has been unable to resist its siren song. Today’s Google results are an increasingly useless morass of self-preferencing links to its own products, ads for products that aren’t good enough to float to the top of the list on its own, and parasitic SEO junk piggybacking on the former.

Enshittification kills. Google just laid off 12,000 employees, and the company is in a full-blown “panic” over the rise of “AI” chatbots, and is making a full-court press for an AI-driven search tool — that is, a tool that won’t show you what you ask for, but rather, what it thinks you should see:

https://www.theverge.com/2023/1/20/23563851/google-search-ai-chatbot-demo-chatgpt

Now, it’s possible to imagine that such a tool will produce good recommendations, like Tiktok’s pre-enshittified algorithm did. But it’s hard to see how Google will be able to design a non-enshittified chatbot front-end to search, given the strong incentives for product managers, executives, and shareholders to enshittify results to the precise threshold at which users are nearly pissed off enough to leave, but not quite.

Even if it manages the trick, this-almost-but-not-quite-unusuable equilibrium is fragile. Any exogenous shock — a new competitor like Tiktok that penetrates the anticompetitive “moats and walls” of Big Tech, a privacy scandal, a worker uprising — can send it into wild oscillations:

https://pluralistic.net/2023/01/08/watch-the-surpluses/#exogenous-shocks

Enshittification truly is how platforms die. That’s fine, actually. We don’t need eternal rulers of the internet. It’s okay for new ideas and new ways of working to emerge. The emphasis of lawmakers and policymakers shouldn’t be preserving the crepuscular senescence of dying platforms. Rather, our policy focus should be on minimizing the cost to users when these firms reach their expiry date: enshrining rights like end-to-end would mean that no matter how autocannibalistic a zombie platform became, willing speakers and willing listeners would still connect with each other:

https://doctorow.medium.com/end-to-end-d6046dca366f

And policymakers should focus on freedom of exit — the right to leave a sinking platform while continuing to stay connected to the communities that you left behind, enjoying the media and apps you bought, and preserving the data you created:

https://www.eff.org/interoperablefacebook

The Netheads were right: technological self-determination is at odds with the natural imperatives of tech businesses. They make more money when they take away our freedom — our freedom to speak, to leave, to connect.

For many years, even Tiktok’s critics grudgingly admitted that no matter how surveillant and creepy it was, it was really good at guessing what you wanted to see. But Tiktok couldn’t resist the temptation to show you the things it wants you to see, rather than what you want to see. The enshittification has begun, and now it is unlikely to stop.

It's too late to save Tiktok. Now that it has been infected by enshittifcation, the only thing left is to kill it with fire.

[Image ID: Hansel and Gretel in front of the witch's candy house. Hansel and Gretel have been replaced with line-drawings of influencers, taking selfies of themselves with the candy house. In front of the candy house stands a portly man in a business suit; his head is a sack of money with a dollar-sign on it. He wears a crooked witch's hat. The cottage has the Tiktok logo on it.]

[armadillorollup]

la vie en rose

[autistic-shaiapouf]

Alright beginning work on moth outfit and:

1) fought to load the bobbin for 20 minutes

2) gave up on sleeves bc every piece of fabric is a different size

3) began shaping the wings with wire and found out I don't have anything to cut them with

[clannfearrunt]

Still no update on the fate of our store’s broken delivery car btw and it’s so fucking annoying bc while we’re waiting on that piece of junk another store is lending us their extra car which is. The same exact fucking piece of shit Hyundai Venue that we just crashed. I don’t even get to drive the Big Beautiful Van that apparently only I like to drive while we’re waiting. I miss the Big Beautiful Van. Where is she

[drfrogphd]

Reusable sticker books are in my shop now! (limited stock since I only got a few of each!)

✨ https://drfrogphd.etsy.com/

[leyyvi]

Have you ever seen any of you merch out in the wild? How would you feel if you did? (:

not really in the wild but i did have someone tell me they bought my hange charm at a thrift store and then they found me at a con gfjkdghjkdfgh

also some cons i come back to repeatedly there's a small group of aot fans that show me their aot ita bags and i see all my charms on it and it literally brings me to tears ;;; aot is very small at cons and usually im the only artist selling aot stuff so idjghsjkdghsd (at least all the ones I've tabled at)

it makes me very very happy when people come back to see if i added more aot stuff ahh

oops i got sidetracked LMAO if i saw it in the wild though id probably just internally freak out and be super giddy about it ;;;;

[monster-noises]

I love second hand book shops, I got to them frequently and always leave with Something and have a good time just peakin around

But i gotta say

It's one of the Worst spots for me in terms of imposter syndrome

I feel like everyone's uneasey with my presence as though i'm a stranger who just stumbled into their inner sanctum and they're.. they're gunna let me stay but they're gunna be weirded out the whole time and breath a sigh of relief when the Strange Unwelcome Freak Leaves

It also happens at record shops and sometimes at small antique shops or cons+festivals

Just this immediate foreboding of being Angrily Tolerated in a Space I Don't Belong

[kuromi-hoemie]

bleh i wish hearing was something u could turn off 100% at will (⁠´⁠-⁠﹏⁠-⁠`⁠；⁠) how am i overstimulated at 12:15am

[bibleofficial]

crazy how ‘lidl’ is ‘aldi’ spelled backwards

[hartxstarr]

my current favorite group of plushies.

[starlit-mansion]

i need to get my spending under control because i'm taking the entire first half of july off (unpaid) but also. i am a creature of wants.

[cat-eared-rose]

Back from my trip to Canada. Sad to leave all my cute partners, but so so so so happy I got to see them 🥺

[akiraofthefour]

uhhhhh I think my boyfriend suggested roleplay lol whuh dude??

[ikiprian]

Ghost Kitchen (brought to you by criminal entrepreneur, Red Hood)

Danny’s got the easiest job in Gotham.

He works as a fry cook at a shoddily-run, independent burger joint. Hardly anyone comes in, despite prices being criminally low, and portions insanely large, and while the manager looks like the average tough-as-nails ex-con, he lets Danny mess around in the kitchen whenever the place is empty. (Which is often. This place has to be the city’s hidden gem or something!)

Mr. Manager’s the only one ever there with Danny, except for sometimes when his buddies come over to smoke and play cards. Danny would find it shady, except part of his job is not to ask questions. Literally, he was told during the interview.

(It was a weird interview. Why would they need to hire someone who’s been in a gunfight before? Like, he has, but Gotham’s idea of “hirable qualities” is so bizarre.)

So instead he whips up some killer burgers with the frozen ingredients, and basks in the praise as the guys tell him he shouldn’t have, he does too much for this joint, ain’t that friendly!

Now, Danny’s a chef on the newer side. As a teen he’d preferred the look of Nasty Burger over anything with Michelin stars, and he only really took up cooking after Jazz moved out for college. But just like ecto-exposure used to turn the groceries sentient, Danny’s low-level ecto signature imbues all his food with something historically haunted Gothamites just love! And Danny’s never been one to half-ass a job when it makes people happy.

With fresher produce, real meat, Danny’s sure he can take his dishes to the next level. It takes a couple months of badgering, but his manager finally agrees to contact the mysterious store owner, who keeps the place going, despite profits Danny knows have to be in the red.

Danny spends the morning prepping. He pours his heart into his food, eager to impress. The big boss will be here soon, and he wants to prove that despite the dangerous location, this place has real potential!

It isn’t until the Red Hood shows up that Danny realizes he’s been working for a money laundering scheme.

[mostlysignssomeportents]

What kind of bubble is AI?

My latest column for Locus Magazine is "What Kind of Bubble is AI?" All economic bubbles are hugely destructive, but some of them leave behind wreckage that can be salvaged for useful purposes, while others leave nothing behind but ashes:

https://locusmag.com/2023/12/commentary-cory-doctorow-what-kind-of-bubble-is-ai/

Think about some 21st century bubbles. The dotcom bubble was a terrible tragedy, one that drained the coffers of pension funds and other institutional investors and wiped out retail investors who were gulled by Superbowl Ads. But there was a lot left behind after the dotcoms were wiped out: cheap servers, office furniture and space, but far more importantly, a generation of young people who'd been trained as web makers, leaving nontechnical degree programs to learn HTML, perl and python. This created a whole cohort of technologists from non-technical backgrounds, a first in technological history. Many of these people became the vanguard of a more inclusive and humane tech development movement, and they were able to make interesting and useful services and products in an environment where raw materials – compute, bandwidth, space and talent – were available at firesale prices.

Contrast this with the crypto bubble. It, too, destroyed the fortunes of institutional and individual investors through fraud and Superbowl Ads. It, too, lured in nontechnical people to learn esoteric disciplines at investor expense. But apart from a smattering of Rust programmers, the main residue of crypto is bad digital art and worse Austrian economics.

Or think of Worldcom vs Enron. Both bubbles were built on pure fraud, but Enron's fraud left nothing behind but a string of suspicious deaths. By contrast, Worldcom's fraud was a Big Store con that required laying a ton of fiber that is still in the ground to this day, and is being bought and used at pennies on the dollar.

AI is definitely a bubble. As I write in the column, if you fly into SFO and rent a car and drive north to San Francisco or south to Silicon Valley, every single billboard is advertising an "AI" startup, many of which are not even using anything that can be remotely characterized as AI. That's amazing, considering what a meaningless buzzword AI already is.

So which kind of bubble is AI? When it pops, will something useful be left behind, or will it go away altogether? To be sure, there's a legion of technologists who are learning Tensorflow and Pytorch. These nominally open source tools are bound, respectively, to Google and Facebook's AI environments:

https://pluralistic.net/2023/08/18/openwashing/#you-keep-using-that-word-i-do-not-think-it-means-what-you-think-it-means

But if those environments go away, those programming skills become a lot less useful. Live, large-scale Big Tech AI projects are shockingly expensive to run. Some of their costs are fixed – collecting, labeling and processing training data – but the running costs for each query are prodigious. There's a massive primary energy bill for the servers, a nearly as large energy bill for the chillers, and a titanic wage bill for the specialized technical staff involved.

Once investor subsidies dry up, will the real-world, non-hyperbolic applications for AI be enough to cover these running costs? AI applications can be plotted on a 2X2 grid whose axes are "value" (how much customers will pay for them) and "risk tolerance" (how perfect the product needs to be).

Charging teenaged D&D players $10 month for an image generator that creates epic illustrations of their characters fighting monsters is low value and very risk tolerant (teenagers aren't overly worried about six-fingered swordspeople with three pupils in each eye). Charging scammy spamfarms $500/month for a text generator that spits out dull, search-algorithm-pleasing narratives to appear over recipes is likewise low-value and highly risk tolerant (your customer doesn't care if the text is nonsense). Charging visually impaired people $100 month for an app that plays a text-to-speech description of anything they point their cameras at is low-value and moderately risk tolerant ("that's your blue shirt" when it's green is not a big deal, while "the street is safe to cross" when it's not is a much bigger one).

Morganstanley doesn't talk about the trillions the AI industry will be worth some day because of these applications. These are just spinoffs from the main event, a collection of extremely high-value applications. Think of self-driving cars or radiology bots that analyze chest x-rays and characterize masses as cancerous or noncancerous.

These are high value – but only if they are also risk-tolerant. The pitch for self-driving cars is "fire most drivers and replace them with 'humans in the loop' who intervene at critical junctures." That's the risk-tolerant version of self-driving cars, and it's a failure. More than $100b has been incinerated chasing self-driving cars, and cars are nowhere near driving themselves:

https://pluralistic.net/2022/10/09/herbies-revenge/#100-billion-here-100-billion-there-pretty-soon-youre-talking-real-money

Quite the reverse, in fact. Cruise was just forced to quit the field after one of their cars maimed a woman – a pedestrian who had not opted into being part of a high-risk AI experiment – and dragged her body 20 feet through the streets of San Francisco. Afterwards, it emerged that Cruise had replaced the single low-waged driver who would normally be paid to operate a taxi with 1.5 high-waged skilled technicians who remotely oversaw each of its vehicles:

https://www.nytimes.com/2023/11/03/technology/cruise-general-motors-self-driving-cars.html

The self-driving pitch isn't that your car will correct your own human errors (like an alarm that sounds when you activate your turn signal while someone is in your blind-spot). Self-driving isn't about using automation to augment human skill – it's about replacing humans. There's no business case for spending hundreds of billions on better safety systems for cars (there's a human case for it, though!). The only way the price-tag justifies itself is if paid drivers can be fired and replaced with software that costs less than their wages.

What about radiologists? Radiologists certainly make mistakes from time to time, and if there's a computer vision system that makes different mistakes than the sort that humans make, they could be a cheap way of generating second opinions that trigger re-examination by a human radiologist. But no AI investor thinks their return will come from selling hospitals that reduce the number of X-rays each radiologist processes every day, as a second-opinion-generating system would. Rather, the value of AI radiologists comes from firing most of your human radiologists and replacing them with software whose judgments are cursorily double-checked by a human whose "automation blindness" will turn them into an OK-button-mashing automaton:

https://pluralistic.net/2023/08/23/automation-blindness/#humans-in-the-loop

The profit-generating pitch for high-value AI applications lies in creating "reverse centaurs": humans who serve as appendages for automation that operates at a speed and scale that is unrelated to the capacity or needs of the worker:

https://pluralistic.net/2022/04/17/revenge-of-the-chickenized-reverse-centaurs/

But unless these high-value applications are intrinsically risk-tolerant, they are poor candidates for automation. Cruise was able to nonconsensually enlist the population of San Francisco in an experimental murderbot development program thanks to the vast sums of money sloshing around the industry. Some of this money funds the inevitabilist narrative that self-driving cars are coming, it's only a matter of when, not if, and so SF had better get in the autonomous vehicle or get run over by the forces of history.

Once the bubble pops (all bubbles pop), AI applications will have to rise or fall on their actual merits, not their promise. The odds are stacked against the long-term survival of high-value, risk-intolerant AI applications.

The problem for AI is that while there are a lot of risk-tolerant applications, they're almost all low-value; while nearly all the high-value applications are risk-intolerant. Once AI has to be profitable – once investors withdraw their subsidies from money-losing ventures – the risk-tolerant applications need to be sufficient to run those tremendously expensive servers in those brutally expensive data-centers tended by exceptionally expensive technical workers.

If they aren't, then the business case for running those servers goes away, and so do the servers – and so do all those risk-tolerant, low-value applications. It doesn't matter if helping blind people make sense of their surroundings is socially beneficial. It doesn't matter if teenaged gamers love their epic character art. It doesn't even matter how horny scammers are for generating AI nonsense SEO websites:

https://twitter.com/jakezward/status/1728032634037567509

These applications are all riding on the coattails of the big AI models that are being built and operated at a loss in order to be profitable. If they remain unprofitable long enough, the private sector will no longer pay to operate them.

Now, there are smaller models, models that stand alone and run on commodity hardware. These would persist even after the AI bubble bursts, because most of their costs are setup costs that have already been borne by the well-funded companies who created them. These models are limited, of course, though the communities that have formed around them have pushed those limits in surprising ways, far beyond their original manufacturers' beliefs about their capacity. These communities will continue to push those limits for as long as they find the models useful.

These standalone, "toy" models are derived from the big models, though. When the AI bubble bursts and the private sector no longer subsidizes mass-scale model creation, it will cease to spin out more sophisticated models that run on commodity hardware (it's possible that Federated learning and other techniques for spreading out the work of making large-scale models will fill the gap).

So what kind of bubble is the AI bubble? What will we salvage from its wreckage? Perhaps the communities who've invested in becoming experts in Pytorch and Tensorflow will wrestle them away from their corporate masters and make them generally useful. Certainly, a lot of people will have gained skills in applying statistical techniques.

But there will also be a lot of unsalvageable wreckage. As big AI models get integrated into the processes of the productive economy, AI becomes a source of systemic risk. The only thing worse than having an automated process that is rendered dangerous or erratic based on AI integration is to have that process fail entirely because the AI suddenly disappeared, a collapse that is too precipitous for former AI customers to engineer a soft landing for their systems.

This is a blind spot in our policymakers debates about AI. The smart policymakers are asking questions about fairness, algorithmic bias, and fraud. The foolish policymakers are ensnared in fantasies about "AI safety," AKA "Will the chatbot become a superintelligence that turns the whole human race into paperclips?"

https://pluralistic.net/2023/11/27/10-types-of-people/#taking-up-a-lot-of-space

But no one is asking, "What will we do if" – when ��� "the AI bubble pops and most of this stuff disappears overnight?"

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/12/19/bubblenomics/#pop

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

--

tom_bullock (modified) https://www.flickr.com/photos/tombullock/25173469495/

CC BY 2.0 https://creativecommons.org/licenses/by/2.0/

[iamred-iamyellow]

⋆ ˚｡⋆౨ৎ˚ Telepatía - [Part 1]

♥ next | masterlist

♥ pairing: platonic f1 grid x latina!fem!engineer!reader x lando norris

♥ smau + written (reader is lewis' ferrari race engineer)

♥ none of the pictures are mine, all were found on pinterest

♥ warnings: misogyny, swearing, and some suggestive language

♥ face claim: wolifecindy on insta & girls on pinterest

♥ a/n: I'm so sorry if my Spanish is incorrect, I'm a no sabo kid

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

liked by mercedesamgf1, lewishamilton, and 239,384 more

yourusername visiting lew at merc

view comments

mercedesamgf1 always happy to have you

*liked by original poster*

yourbestfriend THATS MY GIRL

yourusername love you <3

user60 you don't belong in f1

user73 shes lewis' new race engineer?!

user50 can't believe they're making the seven time champ work with her

user80 no one should be surprised when they loose

user1 lose*

user12 lose* 🤡

user6 that's rich coming from a man who can't spell lose properly.

user8 I'm so proud of her

fredrikvestiofficial I'm gonna miss you as my engineer

yourusername I'll see you in the paddock freddy dw xx

user40 shes probably just a fan of the hot guys

user7 maybe you should take a look in the mirror

user10 she's literally been working in motorsports since she was 19 ffs

user9 please let the rumors be true please please

user2 y/n at Ferrari is my dream

user14 you're so pretty

user6 unrelated but where'd you get those sunglasses

user15 our queen y/n

user56 they cant seriously be trusting her as Lewis' engineer?!

oscarpiastri happy to see you again

*liked by origional poster*

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

liked by scuderiaferrari, lewishamilton, and 946,853 more

yourusername I'm so incredibly honored to be where I am today. Ferrari has always been the dream for me. I can't wait to work with you @/lewishamilton. Forza Ferrari ❤️

view comments

lewishamilton Feliz de que estés aquí. Deseando trabajar con usted.

*liked by yourusername*

user6 LEWIS SPEAKING SPANISH 😭

user7 he's so sweet

user12 the only man ever

yourmom muy orgullosa de ti mija 💞

yourusername gracias mama te amo 💗💗

charlesleclerc welcome to the Ferrari family

yourusername can you adopt me so I'm a leclerc

alexandra.saint.mleux it would be our honor

mercedesamgf1 back off she's susie's daughter

user8 merceds' admin is amazing

fredrikvestiofficial I already miss you :(

*liked by origional poster*

premaracing congrats y/n 🎉

*liked by origional poster*

user80 I can't believe she's really their new engineer

susie_wolff so proud of you <3

*liked by origional poster*

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ ☾. ݁₊ ⊹ . ݁˖ . ݁˖°✧

-Australia 2025-

"It's the first race of the long awaited 2025 Formula 1 season. Welcome back everyone," Crofty said as he camera zoomed in on the track.

"It's definitely an exciting sight to see Hamilton in a Ferrari. Not to mention his new race engineer Y/n L/n who has just moved up from F2." Martin Brundle added.

"I'm really looking forward to what the two have in store today."

"Kravitz over to you."

Ted was walking around the track attempting to speak to Lewis before the race began. He caught a glimpse of Hamilton speaking to an interviewer beside his car.

"How are you feeling about today's race?" the interviewer said, holding the mic up to Lewis.

"I'm feeling pretty confident. The car was really good in testing, we had some good pace in quali, and I'm excited to work with Y/n this season."

"Speaking of Y/n L/n, do you think it will be a big mistake for Ferrari to bring her on the team? Especially as your engineer... knowing how much is on the line?"

"She's phenomenal at what she does and I trust no one more than her to get the job done."

"Don't you think there's some other people that have more experience than she does working in motorsports...?"

"Y/n has climbed up the ranks from f4, 3, 2, and now 1 just like the rest of us. If you're suggesting that she'll be a worse engineer because she's a woman, no. She won't be."

"That's- I wasn't saying she wasn't a good engineer because she's a woman. There's always risk when bringing on a new member. I was wondering if you think the risk is worth the potential reward."

"There's of course always the possibility that your race engineer is not a good fit for you as a driver, but there's not a larger risk due to the fact that she's not a man."

The interviewer continued to stumble over his words. Lewis' PR manager walked over to him, whispered something in his ear, and they both strolled away.

The camera panned to you in your seat in the garage with your headset on, carefully analyzing the data on the screen in front of you.

"You know I've worked with a fair share of awful male engineers in my day." Martin said on his mic and Crofty laughed softly.

~

Lewis had won the first race of the season which caused an eruption of applause from the crowd. The team let you stand on the podium to receive the constructors cup in their honor. It was definitely a day for the history books.

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

liked by lewishamilton, landonorris, and 853,430 more

yourusername first place, serving face

view comments

landonorris @/scuderiaferrari Voy a coger ella para ti

yourusername QUÉ?!?! 😧

user3 LANDO WHAT

user18 😭

schecoperez 🤣🤣

scuderiaferrari pardon?

user7 checo types like a dad 😭

user4 @/user7 that's caus he is one

yourusername @/landonorris DID CARLOS TEACH YOU THAT

landonorris @/yourusername yeah why?

fernandoalonso @/landonorris in latam you just said you'd fuck her for them

carlossainz55 I think what he was trying to say is he wants to steal you from ferrari

yourusername gave me a fucking heart attack omg

user3 I was gonna say ain't no way he's saying that on main

user17 LANDO STAND UP

user8 oh she ate I fear

user9 👑

francisca.gomes STUNNING

yourusername YOUR'E STUNNING

user2 beauty and brains

user10 not all the men bitching and moaning over y/n being an amazing race engineer

user8 she shut them up real quick

user3 women 🛐

user18 that's literally my wife

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

-F1 July Summer Break-

liked by landonorris, lewishamilton, and 429,320 more

yourusername you know I'm just a flight away

view comments

lilymhe gorgeous

yourusername you're gorgeous

landnonorris and you didn't invite me?

yourusername if you wanted you could take a private plane 🤷‍♀️

landonorris hola desde inglaterra

carlossainz55 how come you're trying harder to learn spanish for her but not me

carlossainz55 lando answer me

lewishamilton roscoe misses you

yourusername dile que yo también le echo de menos

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ ☾. ݁₊ ⊹ . ݁˖ . ݁˖°✧

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

liked by yourbestfriend, landonorris, and 652,383 more

yourusername mystery man

view comments

user90 half a season in and she's already dating a driver

yourbestfriend shut your bitch ass up

user5 @/user90 you're just jealous you cant bag a driver

user1 its totally possible the guy in the last pic is not even on the grid be so ffr

user2 literally the most beautiful woman I've ever seen

user8 I love women

user9 I don't watch f1 for hot guys I watch f1 for hot girls hdsjskd

✧˖ °. ݁₊ ⊹ . ݁˖ . ݁‧₊˚ . ݁₊ ⊹ . ݁˖ . ݁˖°✧

end notes: thank you for reading <3 part 2 coming soon