Lawsuit alleges Sony investigated WPP’s media operation and said it ran a ‘global crime scene’, WPP seeks to seal ‘highly confidential and sensitive’ client information from lawsuit with former exec by Lara O’Reilly. (This may be a common pattern. ICYMI: Meta tolerates rampant ad fraud from China to safeguard billions in revenue.)

Why does everything feel like a scam? by Hanna Horvath. (I thnk I know this one. As the IT industry ran out of ideas, but had to keep growing anyway, they filled in the gaps with crime. Phoebe Gates and Sophia Kianni reportedly knew Phia was ‘cookie stuffing’ for months.)

8 thoughts on “Who’s Tracking You? Use This New Service to Find Out” by Brian Krebs. A powerful and free new service called DecryptAds scrapes and correlates this adtech data and makes it simple to quickly learn a great deal about the entities that are tracking you. (This is a good start. What’s harder is figuring out the ML “inferences” about whether you’re a person in immediate need of the product, or a bargain hunter with more options.)

Separating AI’s Technological Problems from Its Capitalism Problems by Bruce Schneier. The question is not whether it is possible to develop AI in a non-exploitative way, or even whether we can trust AI companies to act in the public interest. The question is whether we will recognize that our existing social and economic systems are failing to achieve these outcomes, and whether we can act in time to make structural change. (A big part of the problem is the extent to which “AI” investors and execs see themselves as post-capitalist: a cognitive elite capable of ML-assisted economic central planning with better judgment than old-fashioned markets. More: reinventing Gosplan)

Be a Rube. by George Tannenbaum. I noticed the Times had told the story with six or seven cartoonish pictures and a few hundred words of copy. The New York water system is one of the most-complex infrastructures in the world. If it can be explained this simply, why can’t we do the same when we’re selling AI, or data migration, or Quantum, or whatever? (Maybe a clear explanation would be not so helpful? The More People Learn About AI, the More They Want It Out of Their Lives)

Federal lawsuit accuses four major publishers of extorting article processing charges The case, which became unsealed July 30, claims Elsevier, Springer Nature, Wiley and Informa forced U.S. research institutions to submit false claims to the government for reimbursement through article fees up to 10 times the cost of processing the articles.

AI is Removing Bottlenecks to Effective Content Moderation at Scale by Dave Willner. When platforms don’t prevent this kind of harm, it’s clear that it is no longer because the problem is technically hard. It’s because they’ve decided not to. (I agree: but I want to turn people into dinosaurs)

Reddit ads pose as news stories to promote AI investment scams by Chance Townsend. The promoted posts redirect users to cloned news websites designed to closely mimic the appearance of legitimate publishers, where fabricated articles, invented testimonials, and fake profit screenshots are used to build false credibility. (Why are ad blocker users happier than non-users? Some possibilities: picking up cheap shoes in front of a steamroller)

Extended availability of the products that customers are used to is not unusual in the firearms business. Colt had a “1991A1” near-reissue of the famous M1911A1 pistol from World War II. A serious hobbyist can get a hold of a surprising fraction of the entire firearms tech tree, newly manufactured. And, possibly as a result, even though the firearms market has what looks like a normal level of customer/vendor disputes, the customer base and the manufacturers are roughly aligned, and customers vote with the industry on issues that concern both.

Now compare that to IT. Can you still get the version of anything that was still good? Say, a desktop OS that works like Mac OS “Snow Leopard” or Windows XP Service Pack 3? Or an Apple iOS update without Liquid Ass? Or pre-“cloud” Adobe Photoshop? No—the necessary new code to support new hardware and fix bugs is bundled with stuff that’s just in there because reasons. Not just business reasons, like sticking ads on everything. Sometimes an adult software exec just wakes up with the determination to make an aesthetic impact, even when it makes the product look like a 1990s raver tried to design a psychedelic window manager theme.

IT CEOs are household names—but famous for being untrustworthy. That’s not ideal for an industry that’s trying to build popular support. AI was supposed to win people over by now – it hasn’t. People are asking librarians how to disable or avoid intrusive AI.

The problem is not just the big picture stuff like trying to get people to accept the impact of (still unpopular) data centers. Failure to keep what works, working is costing the industry in other ways, too. In Apple Dropping AirPort Utility From the App Store With iOS 27, Juli Clover covers how one company is turning a usable WiFi device into e-waste by dropping software support. There’s not even an open source code dump.

Cool trick, but now who’s going to buy an Apple Vision Pro? When a support rugpull could come at any time?

The Apple Vision Pro didn’t flop because it’s overpriced. When the Apple Macintosh came out, it cost about 1559 Big Macs or almost half a Honda Civic. That’s for a computer with no networking, Please insert the disk dialogs instead of a hard drive, and a tiny screen.

The Apple Vision Pro does so much more, and it’s far cheaper, at only 604 Big Macs or about one-seventh of a Civic.

But the Macintosh was sold into a 1980s market with conventional norms, and the Vision Pro was too expensive for most people, even developers, to take a chance on in today’s rugpull economy.

When you choose the behavior, you choose the consequences. If the industry wants political support and willingness to try ambitous new platforms, a lot of people will have to make more respectful and long-termist decisions.

One more point being made in favor of standardizing on Big Tech’s built-in ad tracking for web browsers: in the EU, the fix is already in. Supposedly, someone over in Europe (maybe the same crooked politicians in Ireland who help Big Tech evade taxes?) are going to allow attribution cartel tracking without consent, and make everyone else who wants to collect advertising data do the annoying “cookie banner” thing.

I’m not buying it. Do people really expect regulators and politicians in the EU to be all,

Gosh, thank you for the new awesome tracking system, Big Tech! Even though it’s a big risk, your elegant math and “privacy” branding will make us totally accept it without consent!

And do they expect regulators to give special treatment to the attribution cartel even when that would mean giving a problematically USA-centric tracking system—and Big Tech ad inventory—an advantage over European adtech and publishers?

That’s not the way things are going over there. Nick Heer explains a recent German competition authority (Bundeskartellamt) decision about Apple ATT, in After Regulator’s Investigation, Apple Will Make Changes to App Tracking Transparency Prompts in Germany. The definition of tracking Apple uses is self-serving, which would not matter so much if it did not also have a parallel desire to grow its advertising business.

Apple makes it easy to turn off “tracking” by non-Apple apps, while Apple’s own “personalization” and “privacy preserving ad measurement” are harder to find. (turn off advertising measurement in Apple Safari) But now they have to cut out the self-preferencing. From the English version of the decision:

Apple is allowed to provide for a level of protection for its users that exceeds the minimum legal requirements. However, if Apple sets up additional rules within its ecosystem for the use of data, these rules must, under Germany’s special abuse provision for large digital companies, not treat its own offerings better than those of its competitors. This is precisely where our competition concerns arose. Apple will now align the consent requests much more closely and give third-party app providers more freedom to combine the necessary requests in a sensible way.

More coverage by Ana-Maria Stanciuc: Apple bows to Germany and rewrites its tracking-consent rules, ending a self-preferencing probe.

So even if Irish regulators try to get special treatment for the attribution cartel, different from what all the other online ad companies get, eventually the rest of Europe will catch up with them.

Nobody who claims they can tell good writing from bad should care this much. If they’re not using the slopbot instead of doing the writing.

The watermarked text doesn’t even make it into the final writing project, if the LLM was just used for assistance, with methods such as Seth Godin’s AI tear down. So it shouldn’t really matter. Maybe Matt Birchler is right, and the reader’s desire to know when text is AI-generated is more important than the AI user’s desire for the opposite. Maybe Dave Winer is right in A rebuttal to Doc Searls’ piece about watermarks and the risk that a watermark might be detected could help discourage people from getting a long bit of writing from the bot, and then pasting it into a comment thread in a GitHub repo I run.

The bigger question, though, isn’t about the negligible difference between watermarked slop and somehow purer non-watermarked slop.

If LLM output can have watermarks, what else can it have?

Other identifiers. If Anthropic can get a 1-bit yes/no watermark into 200 words of text, how many words does an LLM provider need to encode a 32-bit identifier? That’s probably infeasible in the lengths of text that most people use LLMs for in practice. Maybe they would be able to find the authors of all those slop clone books on Amazon dot com, but for most business writing and article-length text it wouldn’t work. SynthID, described in Scalable watermarking for identifying large language model outputs, encodes a single bit of information by over-weighting token choice from one red list and one green list. Splitting the list into 2ⁿ categories would give you more bits but require a lot more text to encode it.

But what about just a few more bits? Now that governments and Big Tech know that encoding information into LLM-generated text is possible, what’s next?

• USA Citizen/non-citizen? This would be a obvious one for a company trying to get in good with the Federal government here.

• Age verification? I don’t know, they’re sticking age verification on everything now, someone will try it.

• Marketing-related data? The highest-earning 10% of people in the USA buy 50% of the stuff, so there could be all kind of uses for a flag to show which side of the K-shaped economy the user is on.

Infringing or plagiarizing text. The big AI companies have a pretty well-defined political program, and can identify likely opponents to some or all of that program. Some of those opponents are consistent “AI vegans” in their own personal IT choices, but if someone is politically inconvenient and an AI user, well, it’s possible to tune the likelihood that an LLM’s output contains material straight out of the training set.

Could the LLM’s output contain deliberate infringement bombs or plagiarism bombs? Deliberately giving users some text that would get them in trouble later is not the kind of thing that a human developer would risk—too much risk that the commit messages would come out in discovery—but it is the kind of trick that a heavily “agentic” automated software process would come up with. An AI agent can already hack a gym to get its owner a spot in pilates class, so a program of compromising political opponents who are also users seems feasible.

Marketing side effects. Some LLMs are serving ads now, which means a lot of hard-to-predict ML-driven ad placements. And this stuff will be a lot weirder and more indirect than current projects like the attribution cartel, which is pretty clearly going to cause ML to come up with privacy-violating ways to juice the apparent results from Big Tech advertising. ML systems going for other goals are going to get a lot weirder. Meta’s ad ML is already doing pretty weird (and creepy) stuff to maximize engagement, and it’s only going to get weirder.

What happens when more ad-revenue-maxing ML is in the loop in more places? What if you can sell a renter’s insurance policy to user A by giving their friend, user B, some bad household tips that result in an expensive bill from their landlord? Consumer-facing LLMs are run by the same companies that find themselves in a desperate squeeze to keep raising ad revenue at startup-like growth rates. Corners will be cut. Other ways will be looked. Slop advice will reflect the need to achieve ambitious business goals, even at the user’s expense.

Anyway, the difference between watermarked slop and non-watermarked slop is tiny compared to some of the text that’s going to be in the LLM output. Enjoy.

Our lab has agreed on a blanket ban on the use of generative AI for writing….Using generative AI inherently exposes you to the risk of career-ending accusations of plagiarism.

Even though there’s a lot of pressure on academics to adopt AI or be left behind!!1! this is a lot bigger deal. Especially for this particular research team.

They’re a public health lab, which puts them into an unavoidable adversarial relationship with the anti-public-health oligarchs who run the “AI” companies. The “E” in TESCREAL doesn’t stand for “eugenics,” but the political movement behind “AI” is more likely to believe in improving society by weeding out the “unfit” recipients of health misinformation than in public health as we know it.

More from the blog post:

Plagiarism accusations are now a core part of the right-wing harassment toolkit, and knowing that those accusations were made in bad faith or for political reasons does not make them disappear.

It’s safest to assume that a future well-connected accuser will be able to get access to large quantities of text, for practical purposes all of it, and the computing resources to look for a pattern match between anything that the targeted person has ever written and anything that anyone else has ever written. They’ll be able to do the search much better than the targeted person could, even using the best commercial “plagiarism detection” software and services.

Related: On the non-use of AI in my writing process by Charles Stross.

If I was crazy enough to feed the outline of a story I was working on as a prompt to ChatGPT or Claude in hope of getting the stochastic parrot to do my homework for me, then it would be only my own fault and nobody else’s if the next model from the company in question was trained on my book outline and could reproduce part or all of it for someone else.

Authors of scientific papers don’t have the choice to keep their work out of training sets in most cases. As soon as it’s published or on a preprint server it will get crawled, either with the publisher’s cooperation or not.

So what’s next? Prediction markets, apparently. Yes, I admit, predicting that they’re going to fail at this is a safe prediction. Meta trying to build an end-user platform is like Wile E. Coyote trying to catch the Road Runner.

• 2013: Facebook Home

• 2014: The Metaverse

• 2017: Diem (digital currency)

• 2018: Meta Portal

Meta bought Instagram and Whatsapp, and continues to grow as part of the advertising duopoly, but making new consumer-facing stuff, not so much. Open Compute Project was a huge success inside the IT department, but nobody has their hardware at home. The interesting part here isn’t that Meta is going to fail at prediction markets, it’s how they’re going to fail.

One of the arguments for the attribution cartel is that in-browser attribution tracking will somehow displace other forms of ad measurement. Because reasons, I guess. Or because the cartel members believe that they can convince people that everyone else’s ad data collection needs consent—or at least those fake “consent” dialogs that the Irish regulators will let you get away with—and somehow the attribution cartel doesn’t.

The problem with that argument is that there have already been two big opportunities for substitution effects to happen. And they haven’t.

• Google’s “Privacy Sandbox” included an Attribution Reporting API. But as far as I can tell it was the only one of the major “Privacy Sandbox” ad systems not to get an independent test. (If I’m wrong, let me know and I’ll add it to the timeline.)

• Apple Safari has “privacy-preserving ad attribution” that came out in 2021, but as far as I can tell most of the people talking about it are users who found it buried under “Advanced” in settings and are talking about turning it off.

Why so little marketer interest in an in-browser ad measurement system?

The problem is that for the attribution cartel, the system has a limited set of acceptable outputs. The Google and Apple systems would have had to agree that the best-performing ads are on Google and Apple properties.

Likewise, whatever W3C ends up standardizing on, the attribution reports will have to agree with the ad placement decisions already made by the Facebook and Instagram algorithms, by Google’s Performance Max, and by whatever Apple is going to be doing as they continue to enshittify over there. Imagine an attribution report that contradicted the optimal placements decreed from above, and gave credit for sales to legit independent sites instead. That would be like writing a biology paper contradicting Trofim Lysenko back when he was a big shot.

Since marketers can predict that the attribution reports are going to hide the halo effects of the likely most impactful ad placements, and just back up what the cartel members were saying anyway, there was little interest in the Google and Apple systems, and there will be little interest in the new one. The attribution cartel members have reasons to do what they’re doing—but they have to do with lobbying and consolidation, not benefits to legit advertisers or legit ad-supported sites.

More: Are ya winning, son? How the attribution cartel is getting privacy nerds and adtech execs to agree on something.

The European privacy organization noyb has filed a complaint over a common web annoyances. This one is a little more extreme than most: 1,741 “informed” consents with one click?! GDPR complaint against dict.cc filed. Who has 1,741 “partners”? Anyway, this claimed “consent” to data collection by all these “partners” is stored in the following TCF string.

CQoKcgAQoKcgAAJAGBENCpFsAP_gAEPgACiQMttR_G__bWlr-bb3abtkeYxP9_hr7sQxBgbIkm4FzLvW7JwGx2EZJAyatiIKmRIAu3DBIQNlHBDURUCgKIAFryDMaE2U4TNKJ6BkiFMZIytQCEhvm4tjeQCZ4ur_9kc0mB-t7dr-2dzyy6hHn3a5fmS1UJSdIYesDfv-ZhOS-9IEd-x8v4v4_EbpEm8eSVn9pGtp4jc6Yns6dBmxt-Tyff6Pn_f71fW7X_ve_n3zv8oXn7rr6-__f3-7___-b_-___b-__7Z_zM_37_v_YMttR_G_9bXlv-bBX4btkOYxf9_gD7sQxBAbIomYFzLqW5IwC32ETJEiaMCIIGRAAo1BBIAEpEBhEREChCIAVLxDsAE0Q4TtIAeBkgDMZYiBQAEhPi4tjWQCZ4Op-dUd0iQ2s5Nr22VyyWbAjn3KteOSVUJicKYMFHetuYhMQ-vIU93RK9otI_MbpEkIYARv9lWpl4TYa4vnKVpqxNeRydMSffdFz3fW7RO3a-91k-uqSV_rb4uXW5m__bNn_f138_f_7Z7_1x-3Zf_f__4AAAA.IMttR_G__bXlv-bb36btkeYxf9_hr7sQxBgbIsm4FzLvW7JwG32EbJEyatiIKmRIAu3DBIQNtHBjURUChKIAVrzDsaE2U4TtKJ-BkiHMZYytQCEhvm4tjeQCZ4ur_90d0mR-t7dr-2dzy27hnn3a9fuS1UJydKYetHfv-ZhOS-_IU9_x-_4v4_MbpEm8eSVv9tWtt4zc64vv6dpuxt-Tyff6f__f73fW7X__e__33_-qX3_r76-___3______f__________9_________4A.f_wAD_wAAAAA

If I visit the site from the complaint using a European VPN endpoint, Yes, I went to that site with VPN to Europe on and ad blocker off, and ended up seeing a gross fungus treatment ad. Yeech. The things I do for privacy research and click the obvious button to make the annoying dialog go away, this is what gets stored in the browser. And no, I won’t say that I “consented” because I’m still not informed enough about this industry to give informed consent in all but a few cases.

But why 1,741 partners? Because of the way that this stuff works in Europe right now.

1. A site gets a Consent Management Platform (CMP) – a third party script that powers the annoying “consent dialog”/“cookie banner”

2. A person with up-to-date knowledge of the site’s data practices carefully configures the CMP to match the…lol, no, somebody clicks various options in the CMP control panel until the errors and warnings stop, which is how you end up with “1,714 partners” and other ludicrous messages to end users.

3. When a user visits the site and clicks the CMP “consent” button, the CMP stores a record of “consent.” (This can be in TCF, or in a related format called Global Privacy Protocol that wraps TCF along with other strings that apply to non-EU jurisdictions.)

4. Any company that is somehow processing the user’s information has to check the record from step 3.

There’s no step in the process for MyTerms, and the way it’s set up makes it look like a MyTerms check is not needed at all. No decision-maker at the site is going to see any need to get contractual permission to do some data processing that, as far as they can tell, they “already have consent for.” (It’s fake consent because Irish politics, but people settle for it.)

So a way to get more sites interested in MyTerms is something like a step 3.5.

• Detect when a CMP is generating a TCF or GPP string.

• Where the string indicates “consent” to anything that would be disallowed by any of the possible MyTerms contracts that the user has indicated they would accept, modify the string to remove the conflict.

This filtering or masking step is not going to produce as good of a result as a full MyTerms transaction that both user and site participate in, but it at least takes a step to prevent the data practices most inconsistent with the user’s preferences (and safety), and gives the site an incentive to upgrade to full MyTerms instead of just filtered GPP.

Different MyTerms implementations might approach GPP and TCF integration differently.

One possibility is to provide a surrogate script for the CMP and prevent the annoying “consent” dialog from ever showing up.

Or implement the CMP API to provide a filtered result to callers.

I’m sure that other possible approaches exist, too. The only approach to GPP and TCF that I know for sure won’t work is ignoring them.

A.I. models are very different from the usual inexpensive imports we buy from China. These products must promote the interests of the Chinese government. Propaganda and false claims are baked into them.

…

Whoever supplies the world’s A.I. will shape how the world thinks. As these models get smarter and more autonomous, we are outsourcing more and more thinking to them. That “cognitive offloading” must not go to models that were designed to promote a foreign government, no matter how inexpensive they are.

Two problems with that. (Aside from letting the AI shape how you think, which, yikes. But the influence is already there, and we have to expect that it will persist.)

First of all, the choice is not between propaganda AI from the PRC and some hypothetical, honest red, white, and blue AI from the good old USA. The average American has more in common with a random propaganda commissar in China then with the deeply weird TESCREAL investors, founders, and CEOs who run the AI operations here.

Second, as more and more legal opt-outs apply to LLM training sets here, the US-based AI firms will rely more and more on vibe CMS automated paraphrased versions of US and European news and culture. Legit publishers will opt out the copyrighted works they own or distribute, in the hopes of training license deals. Big AI firms will pay a few publishers for PR value, but mostly settle for first-generation lossy copies.

And a lot of that free training material will have been run through someone’s PR filter. For example, a reputation management firm could make a site that mostly generates high-fidelity paraphrases of legit news, but folds in positive mentions of the firm’s clients. Almost everyone wins: big US-based AI gets freely crawlable tokens, the client gets their crimes buried in LLM-generated answers, most news consumers get an adequate free paraphrase. Meanwhile, though, AI operations in the PRC will be able to train on material that’s one generation fresher.

The problem isn’t so much that “our side’s” AI is better than theirs, or the other way around. Every LLM is going to have embedded biases, for a variety of reasons. Propaganda and copyright-related biases are only two.

Wherefore doth the way of the wicked prosper? wherefore are all they happy that deal very treacherously?

Every generation of people perceives a collapse in ethical behavior, and if the trust level of human civilization had really been sliding that badly for so long—the book of Jeremiah was written 2600 years ago—nothing would be left for us by now.

That perception of decline is not surprising, considering that most people respect norms of honesty and reciprocity, but the transgressors tend to attract more attention. Often, people who comment on moral collapse are older adults comparing their experiences with their own peer group to the crimes of the younger, higher-profile 30 under 30 crowd.

So we can’t just go by vibes, by our feelings of how much of a rip-off everything is now. We have to take a step back and look at the stats. And this time, possibly because of how network effects amplify the impact of a few big companies, it’s a real problem.

According to the FTC, people in the USA lost $2.1B to social media scams in 2025. Internal documents from Meta, which owns Facebook, Instagram, and WhatsApp, estimated that the company is involved in about 1/3 of successful scams here.

And Meta isn’t the only company that designs an Internet platform to work better for scammers. Google tweaks their systems and policies to benefit scams, too. The FBI warns,

Cyber criminals use advertisements that imitate legitimate companies to misdirect targets conducting an internet search for a specific website.

Google Search is a major scam risk because of some choices in software design and ad policies that make their platform work better for scammers and worse for those trying to catch them. As Prof. Tressie McMillan Cottom wrote, we are now living in a scam culture.

Scams weaken our trust in social institutions, but their going mainstream—divorced from empathy for the victims or stigma for the perpetrators—means that we have accepted scams as institutions themselves.

Google and Meta are large enough, and have enough impact on how people and companies find each other, that their internal collapse in business ethics has an oversized impact on the whole economy.

The ways that big companies profit from online fraud is pretty complicated, but I think I can explain it if we work backwards. And the better we understand how scam culture has been coded into everyday business practices, the better we will be able to roll it back.

Apple Updates Its Advertising Policies by Nick Heer. (More news from how Apple is on the enshittification curve the same as any other company.)

The political polarization of health outcomes in the USA by Elizabeth Elder and Neil A. O’Brian. Roughly half of this new health gap is due to people changing their ideology over time, with new entrants to the conservative coalition being less healthy than new liberals. But another sizeable share is due to people who were already liberal or conservative diverging more in health over time. (Maybe William James was right about the cash value of beliefs, and some people are just invested in lower-return asset classes?)

Experience Better Browsing: Introducing Native Containers in Firefox 153 (This is part of the easiest way to containerize and mostly de-enshittify YouTube, now part of the browser.)

A decade after the ‘Godfather of AI’ said radiologists were obsolete, their salaries are up to $571K and demand is growing fast vy Marco Quiroz-Gutierrez. Over the last 10 years, the number of active radiologists in the U.S. has grown by about 10%, said Christoph Herpfer, an economist and business administration professor at the University of Virginia’s Darden School of Business who studies health care finance and physician labor markets. We actually have a huge shortage of radiologists. So the exact opposite of this prediction has happened, he told Fortune.

Book publishers sue Google for copyright infringement over Gemini AI training by Emma Loffhagen. The publishers argue that Google repurposed books that had been supplied for limited services such as Google Books, Google Play Books and Google Scholar. Those services allowed Google to use the works in specific ways – for example, to display searchable snippets or sell ebooks – but not, the lawsuit claims, to copy them for training commercial AI products.

Please Stop Making Me Opt Out of AI by Reece Rogers. (not likely. Number must go up.) Related: https://マリウス.com/the-rise-of-the-bullshittery/), The Lies They’re Telling Towns And Tribes About The Benefits Of AI Data Centers by Karl Bode, The Pollution Being Churned Out by AI Data Centers Is So Severe That It’s Almost Incomprehensible by Victor Tangermann.

Please, I Beg You, Do Not Fill My TV With Pregnancy Ads by Victoria McNally—associate editor of AdExchanger. (Marketing people know that this stuff is creepy as hell, and counterproductive for the brand, but they’re so cohesive as a group that it will take a swift kick from outside to stop the slide into chickenization.) Related: Where Did It All Go Wrong For Agencies? by Brian Jacobs.

Google’s new use of IPs in Europe by Alan Chapell. Hooray, Google imposes yet another compliance tax on companies using their services. Accordingly, anyone running a third-party CMP supporting Adsense must surface Feature 3 in Google’s vendor entry before August 3 or risk understated-disclosure exposure and limited-ads degradation (not to mention legal liability). (Somewhere in Mountain View, Google lawyers are passing the bong and laughing their asses off about being able to make people do all this stuff. I got it, I got it, make them quack like a duck next, they’ll totally do it!)

Meta’s AI advertising dreams have become a nightmare for brands by Lara O’Reilly, Sydney Bradley, and Lucia Moses. Meta is pushing advertisers to use its AI tools — and results are proving chaotic: strangely twisted limbs, gibberish writing, or entirely changed products. Meta’s response to brands: That’s on you, not us. (Don’t worry, when Meta takes control of how the ad results get measured across all media, these ads will turn out to be the best ads ever.)

• WTF: W3C’s Attribution API?

• W3C Attribution API prompts debate over web measurement future

• Fears of Big Tech bias underpin debates around W3C’s Attribution API

I’m quoted, about the proposal’s biggest privacy problem.

“You get this paradoxical increase in user privacy risks, because the proposal obfuscates and rewards attribution fraud,” he told Digiday, adding the proposal’s current guise actually “creates more incentives to collect more data on more people in order to sneak ads in front of those who are about to buy anyway.”

And so is Angelina Eng, formerly VP of measurement at Interactive Advertising Bureau (IAB) U.S.

“There is no one-size-fits-all solution, and there is always customization,” she explained to Digiday, urging the importance of the ability to slice and dice data across time periods and portfolios without browser-imposed constraints or privacy budgets limiting combinations.

(The “privacy budget” feature is part of how “structural advantages” to large scale are built in to the proposal.)

So if both the free-range privacy nerd (me) and the adtech measurement expert executive are against the attribution proposal, could that mean that the attribution cartel is doing something right?

Unfortunately, no. The big companies in the middle are just taking such a big bite that it’s unacceptable to both ends.

Adtech people and privacy nerds are on opposite sites on a lot of issues, but fundamentally most members of both groups are proponents of decentralized decision-making. Markets, stigmergic learning, competition, all that good stuff.

The Big Tech companies are approaching the problem differently. In the surveillance oligopoly model, prices—instead of acting as an information-carrying medium—serve only as an output of an ML system that collects data from both buyers and sellers. The operator of the ML system can sit back and collect all the consumer surplus (which is really the only source of revenue remaining that’s large enough to justify all those data center investments, just saying).

There is well-known criticism of economic central planning, but every so often someone predicts that this time it will be different, and central planning will totally work because now we have better information technology for central planning. This time, that supposedly enabling technology is “AI.” The Attribution proposal is not an economic central planning platform all by itself, but it’s a step toward the cartel members’ planned economy goal. Instead of a variety of advertising decision-makers evaluating the performance of different ad media for different purposes and different audiences, the cartel will be able to provide one centralized report, which will, of course back up the placements made by its own algorithms.

My view is that advertising should be an economic signal between independent players in an economy. Cory Doctorow summarizes the other side of the argument as “Facebook has built a mind-control ray out of Big Data, and we can sell anything to anyone”.

So it’s not a surprise that adtech people and privacy people are on the same side on the attribution cartel issue. If the atttribution cartel can be beaten—and it can, the freedom-loving side beat the Clipper Chip and the Fritz Chip and this time they don’t even have a chip—then the privacy nerds and the IAB can go back to arguing about cookies and stuff in the context of a market economy. I’m looking forward to that.

Based on the article Bypassing the Profile Manager from MozillaZine. This is the “unlisted profile” feature.

And the temporary profile directory gets cleaned up when the script exits.

Looking back at the history of the IT industry, it’s possible to find instances where vendors did to their customers some of the same kinds of shenanigans that oligopoly companies are doing to everyone today.

An early example of paleoenshittification was the decision by Sun Microsystems to remove the C compiler from its Solaris operating system. An OS, as a two-sided platform for developers and users, is in a position to do the enshittification cycle, and Sun did it early. The Unix software scene was the subject of an enshittification run long before artists and writers experienced one on Facebook. Sun tried to get people to pay to rebuild their own C programs long before Meta tried the same for reaching people’s own audience. Yes, many Solaris users started paying for the compiler that they used to get with the OS, but others were able to slip out of being caught in first-stage enshittification—maybe because old-school Solaris didn’t have the infrastructure, licensing, or anticircumvention law to lock out or put a toll on other compilers. The removal of this key development tool was one of the key events in the popularization of a copyleft-licensed replacement, gcc. More info in Nick Moffitt’s $7 History of Unix.

Without that move by Sun, and other attempts at enshittification of Unix, the software freedom movement and open source software business might never have gone mainstream. So for those who dig rhyming history, it’s tempting to make the analogy: MyTerms and the tools that support it are to the enshittifying web of today as the GNU licenses and tools were to Unix. But the rhyme needs to hang together. The GNU tools were initially distributed first on tape, then CD, in a convenient form for building and installing on existing Unix systems. The “autotools” that mystify the developers of today were a pragmatic response to the need to work with what’s there in order to get adoption.

Today, IEEE, IAB, and W3C are all trying to address similar problems with how personal information gets used on the web, and everybody has gaps. The winning approach will be the one that can best embrace, extend, and ameliorate where necessary, the other two.

That starts with understanding the territory.

MyTerms is not unique in offering an automated way to do the paperwork necessary for processing personal data. On a technical level, data collection on typical web sites operates not directly under control of the site ToS, but using an Interactive Advertising Bureau standard called GPP, which stands for Global Privacy Protocol. (Not to be confused with GPC or GPL.)

GPP is an existing machine-readable way—with open source documentation and sample code—for browsers to tell sites that

• the user in in a jurisdiction that requires consent, and consent has been obtained

• the user is in a jurisdiction that recognizes opt-outs, and no opt-out is in effect

• the user is in some other jurisdiction, do as thou wilt shall be the whole of the law

And all of those options can apply to a bewildering grid of purposes and vendors.

Although MyTerms relies on contract instead of consent, it solves a problem that from the company point of view is already solved. Companies that process your data already have machine-readable permissions that they rely on to process your data, because they already check GPP.

From the company point of view, there is zero reason to check MyTerms for permission to do something that GPP already says is allowed.

So the path to adoption for MyTerms has to account for the widespread existing reliance on GPP. MyTerms can de-enshittify your web experience, but can’t get adopted everywhere all at once, any more than C programmers could go from proprietary Unix to a complete “GNU System” of all freely licensed software all at once.

We have to look for key influence points to work with what’s already there.

Fortunately—because GPP is open source, along with a bunch of handy tools for working with it, it will be pretty straightforward for MyTerms implementations to also support GPP.

Detect sites where GPP is in effect and modify any consent or no-objection entries that are obviously in conflict with the MyTerms contracts that the user is willing to accept. This means a little extra work is required to map the MyTerms licenses to the permissions that can be expressed in GPP, but when that’s done, a new MyTerms user can start getting value from their MyTerms tool even on non-MyTerms sites.

That would leave the MyTerms/GPP hybrid providing more privacy protection than GPP as deployed today, but not delivering the full benefits of MyTerms—kind of like how installing GNU tools on Solaris solved the immediate problem of building C programs, but you still needed a licensed copy of Solaris to run them. But it gets the MyTerms situation from (stable, no MyTerms) to (unstable, some MyTerms) on the way to the full MyTerms stack. For sites, the decision to adopt MyTerms would go from no effect to a better option than just MyTerms to GPP (lossy) encoding. And users could get a similar immediate benefit to what Rewarded Interest offers—the confusing, annoying “consent” dialogs disappear.

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Sometimes, though, I’m just all, damn, dude, you said that part out loud? The Big Tech companies have corporate training for talking about doing crimes, but it looks like Mozilla doesn’t have their own Stringer Bell, and ends up taking more “notes on a criminal fuckin’ conspiracy” than the other cartel members would probably like.

In an interview with Martin Thomson from Mozilla about the W3C Attribution API, Alan Chapell asks,

Critics have indicated that the privacy-budget mechanism favors large platforms whereby a single mistaken query can lock a small advertiser out, a constraint only a dominant firm could enforce. Does the design assume a power imbalance between platform and advertiser, and if so, does it entrench one?

And the answer is one that I’m going to archive just in case.

I want to acknowledge that this is one of the hard parts. Large platforms have more data to use, so they are able to slice that data in more ways than the little guys. With noise, you can’t slice what you get into thousands of pieces unless you have many thousands of people involved. Or, more likely millions. Small players need to be more careful and make fewer queries. And a mistake will wipe out more of their potential learnings as a result.

On top of that, big players will be better able to develop the discipline necessary to get more out of the system. More people, more resources, all that.

We spent a lot of time thinking about this problem. But we concluded that this was one area where attempting to levy a technical control was unwise. Competition law — as ineffective as it has been in stemming the rise of monopoly power in this market, and others — has a better suite of tools available than we do.

Right now, the best I can say is that there are no structural advantages provided to large players, other than what they obtain naturally. I understand that this might be disappointing, but it’s the pragmatic outcome in this case.

Let me check my notes here. Nope, not one of the members of the attribution cartel is Mother Nature. The “obtain naturally” has nothing to do with nature as we know it—it’s a reward to scale that results from the design of the attribution tracking system.

Oligopoly is hard-coded in—as a result of decisions made by and for the oligopoly companies. And of course it’s “pragmatic” for those who already dominate the online advertising market to design a system to keep dominating it.