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Delta airlines has announced a new surveillance pricing plan: they're going to feed an AI the nonconsensually harvested personal data that data-brokers and credit bureaux hold on you to predict the maximum you're willing to pay, and then price their tickets accordingly:
Data-brokers hold all kinds of data on you, from the "legitimate" information about everywhere your car has driven, to everywhere point in space that the Bluetooth radios on your phone and headphones have passed, to everything you've bought, to every website you've visited and every search you've performed. They also buy data that has been straight up stolen from you by spyware implanted on your phone:
All of this can be merged into a single file that you have no right to scrutinize, let alone redact. Biden's Consumer Finance Protection Bureau passed a rule banning all this shit, but Trump illegally killed off that rule:
Capitalism's highest form of creativity is finding ways to rip you off, and the business world's most creative minds have found a million ways to exploit this data, including surveillance pricing. For example, McDonald's has invested in a Kiwi startup called Plexure that offers to help restaurants jack up the price of your usual order on payday, when you can afford to pay more:
And then there's the Big Three "Uber for nurses" apps, who use surveillance data to calculate wages for nurses, offering lower hourly rates to nurses who are carrying a lot of credit-card debt, on the grounds that they are too desperate to turn down a lowball offer:
And just as these gigwork apps are deciding what your labor is worth, surveillance pricing systems decide what your money is worth, charging you more than another otherwise identical customer, for an identical product, meaning your dollar is worth less than that other customer's dollar:
Now we have Delta, which promises to do the same thing, but for plane tickets. Obviously, the aviation industry has long practiced a form of "price discrimination," charging radically different sums for the same seat, based on when you buy the ticket, or when you plan to return.
But this is different, and to explain why, here's a link to an article by the great Hubert Horan, who may be best known to my readers for his incredible breakdowns of Uber's finances, but whose life's work is as an aviation analyst:
Horan draws a distinction between surveillance pricing and "second degree price discrimination." Surveillance pricing targets you, personally, based on your personal information. "Second degree price discrimination" charges everyone like you the same price: like, everyone who buys a roundtrip ticket without a Saturday night stay is charged extra on the grounds that they are probably a price-insensitive business traveler whose fare is being paid by a corporation.
Surveillance pricing is first-degree price discrimination, with every customer seeing a different price. Horan argues that second-degree discrimination created efficiencies, for example, by offering cheap last-minute seats to people thinking about going away for the weekend, who fill seats that would otherwise go empty. Horan says these efficiencies have tapped out, thanks to the application of straightforward pricing algorithms to tickets.
Now, Delta wants to squeeze more profits out of price discrimination, but by employing first-degree discrimination, they're doing so without any benefit to fliers (unlike second-degree discrimination, which made many fliers better off because they were able to score cheaper tickets). This makes Delta's surveillance pricing a "pure transfer" – shifting wealth from fliers to shareholders with no benefit to those fliers.
Delta is doing this in partnership with an Israeli firm called Fetcherr, whose sales pitch denies that they are using surveillance data to price tickets, despite what Delta has claimed. Horan doesn't know what to make of this, but he speculates that because Fetcherr bills itself as an AI company, Delta thinks it can impress investors by claiming that it will goose prices by combining surveillance (well understood to be a way to benefit corporations at the expense of their customers) and AI, a hype-filled technology that is endlessly impressive to credulous investors.
A bigger mystery is how Fetcherr plans to do surveillance pricing without surveillance. Horan points out that the company's founders come from hedge funds, where automated high-speed AI trader-bots fed on tons of public market data are routinely used. He thinks it's possible that "Fletchrr doesn’t understand airline pricing very well." Also, being finance bros, they thought "airlines were 'outdated' 'undisrupted' and had seen few recent technological advances." But, Horan continues, the reason airlines aren't doing a lot with their algorithmic pricing is that they've already done it all, having pioneered the field.
Horan's favored explanation for the disconnection between what Fetcherr and Delta claim they're doing is that, on the one hand, they want to obscure the fact that they're doing surveillance pricing (to avoid regulatory scrutiny and consumer backlash), but on the other hand, they want to telegraph (to investors) that this is exactly what they're doing.
It's what Uber already does, repricing both the labor of its drivers based on their economic desperation, and the cost of your fare based on what its surveillance dossier suggests you're willing to pay. It's certainly increased Uber's margins – by effecting a pure transfer from riders and drivers to shareholders.
But Uber rides are last-minute, small dollar purchases, which decreases the likelihood that a rider will shop around before booking. By contrast, Horan says, most fliers buy well in advance, from online travel sites that show them lots of competing prices.
One thing Horan doesn't mention here is that British Airways has just done a top-to-bottom rejig of its frequent flier program to severely penalize anyone who buys tickets from one of these sites, effectively requiring its fliers to buy from BA.com. For example, I booked a $300 Alaska Airlines ticket on Alaska's website, using my BA frequent flier ID.
Under the old system, this would have been worth 10 tier points out of the 1500 needed to get Gold status (0.66%). Under the new system, I got 12 points out of the 20,000 needed to get Gold (0.05%) – a 93% reduction in the reward value of this flight.
Which is to say that if you don't book on BA's site, you effectively cannot make status. BA has also announced a surveillance pricing deal with an AI company – and this gambit will block its best fliers from getting a better price from an online travel agency.
One other key difference between Uber and Delta: Uber has gone to great lengths to hide the fact that it's doing surveillance pricing from both drivers and riders. Delta issued a press-release!
There's a certain kind of neoclassical economist who loves surveillance pricing and praises its "efficiencies." These apologists claim that by increasing the amount of "information" in the system, we encourage sellers to discount to customers who can't afford as much, making everyone better off:
This is nonsense. Sellers don't want to "increase the amount of information in the system." They want to spy on you. If you doubt it for an instant, just ask the firms that scrape airline websites for up-to-date pricing information:
Not only will airlines sue you for trying to find out what their fares are, they'll also sue you for figuring out how to get a better deal on their fares:
Companies that do surveillance pricing are violently allergic to sousveillance pricing. When they spy on you, that's progress. When you monitor their behavior, that's piracy.
As an aside, this reminds me of one of the AI industry's most egregious hoaxes-du-jour: the pretense that "agentic AI" is just around the corner, and soon we will be able to ask a chatbot to (e.g.) comparison shop across multiple website for the best airfare and book us a ticket:
This absolutely totally does not work. You should not give your credit-card number to a chatbot and ask it to go out an buy you anything, lest you end up paying $30 for a dozen eggs and buying tickets to a baseball stadium in the middle of the ocean:
AI agent demos are so dismal that AI companies are no longer claiming that "agentic AI" will involve chatbots that nagivate the web as is. Rather, they're claiming that every website will eventually re-tool so that it can be reliably and predictably addressed by an AI agent, with all of its user interface elements well-labeled and/or addressable programatically, via an API.
This is a remarkable sleight of hand! First of all, re-engineering every website to embrace a common set of labels and API fields is a gigantic engineering feat – formally called "the semantic web" – that has been attempted since 1999 without any meaningful progress:
https://en.wikipedia.org/wiki/Semantic_Web
In fact, the first viral article I ever published online was "Metacrap," a critique of semantic web efforts. That essay is now 24 years old:
In that essay, I suggest that there are multiple reasons that companies will not voluntarily retool their sites to make it easier to comparison shop. One important reason is that companies don't believe their products are comparable with competing products (or they don't want you to think so). Coach wants you to think that its $40,000 handbags can't be replaced with a well-made $100 bag or even a $0.10 plastic bag. They are not going to voluntarily categorize their handbag in a way that facilitates these comparisons.
Then there are companies that do want to be compared to rivals, for disingenuous reasons. That's why we saw such a proliferation of junk fees (stupid surcharges tacked on at checkout time): hotels, airlines and car rental agencies knew that the majority of their customers shopped for their offerings on comparison sites. By offering a low sticker price, a company could win on price comparison, even though it was substantially more expensive after its junk fees were factored in.
Finally, there's the fact that companies want to lie to you, and adding "semantics" to the web does nothing to prevent such lies, and indeed, makes them easier to tell. Think of all the Amazon sellers who use deceptive product photos to make you think you're getting (e.g.) a useful kitchen spatula, when they're selling a spatula so small that it appears to be engineered for a dollhouse; or companies that sell powerbanks that look like a useful portable battery but can't even recharge an LED flashlight, etc, etc. AI agents can't tell if metadata is correct or not!
Every complex ecosystem has parasites; that goes triple for the web. We won't fix agentic AI by asking people to accurately label their offerings, not when they stand to benefit by lying:
And if we could rejig the web to make it hospitable to agentic AI, we wouldn't need AI to make this happen. Fetching airfares for several routes and comparing them isn't something you need an AI-style inference engine for – it's a straightforward algorithmic problem that can be easily solved. The part that agentic AI purports to solve isn't figuring out which airfare out of a list is cheapest – it's compiling the list itself, from unstructured data retrieved from heterogeneous websites that are doing everything they can to prevent the compilation of such a list.
This is a well-known AI gambit. First, announce that agentic AI will be able to automate tasks that only humans can manage today; then insist that everything has to be changed to be amenable to the new technology. This is exactly what the self-driving car grifters (who were on the leading edge of the AI grift) did. First, they announced that AIs would be able to pilot cars in spaces filled with human drivers, walkers and cyclists. Then, when it became clear that this would result in slaughtersome robot-on-human violence, they demanded that humans curtail their behavior to avoid upsetting the robot.
They call this "the pogo-stick problem":
“I think many AV teams could handle a pogo stick user in pedestrian crosswalk,” Ng told me. “Having said that, bouncing on a pogo stick in the middle of a highway would be really dangerous.”
“Rather than building AI to solve the pogo stick problem, we should partner with the government to ask people to be lawful and considerate,” he said. “Safety isn’t just about the quality of the AI technology.”
Automation is real and can deliver real benefits to people. Sometimes, automation requires that other systems be adjusted to facilitate its functioning. But this is a gambit. It's a scam. AI agents aren't going to replace human labor. The only way we'll replace human labor with software agents is by redesigning all these heterogeneous, competing systems owned by people who benefit from the status quo and have every motivation to obstruct this project.
Good luck with that.
Support me this summer in the Clarion Write-A-Thon and help raise money for the Clarion Science Fiction and Fantasy Writers' Workshop! This summer, I'm writing The Reverse-Centaur's Guide to AI, a short book for Farrar, Straus and Giroux that explains how to be an effective AI critic.
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:
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[Turn to CAM 2, flip chair around backward] Meta employees, let me rap at you a minute. Sure, “You Can Always Quit,” as we like to say around here. But at this crucial juncture, you can both protect your own livelihood and do so much more good for the world by not quitting. That’s right! Don’t quit, just stop working. Show up every day, don’t complain, don’t draw attention to yourself. But don’t accomplish anything. If you are working on a project, commit in your heart to never finishing it. This will be your last project at Meta, and you will be “working on it” until they force you out. If others rely on you to get their work done, make sure they can’t. If your role involves reviewing pull requests, you and I both know you can find a reason to reject every one. In fact, wouldn’t it be fun to see how many other employees you can drive out first? If you work in an open office space, make sure you chew loudly at all times. Microwave fish in the break room every single day. Be creative! You’ll have plenty of time to think of ideas, with all the work you’re not getting done.
Transmitir um pensamento seja ele falado ou escrito não é uma tarefa fácil. Transformar uma série de pensamentos em algo tangível para transformá-lo em um programa é algo ainda mais complicado. Neste post, totalmente relacionado ao meu mestrado e ao meu projeto, resolvi falar um pouco da dificuldade na comunicação do entrevistador e do entrevistado objetivando um ponto comum no desenvolvimento de um "determinado" assunto.
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