“…reduces an entire mouse to a soup-like homogenate in 30 seconds.”

It’s like the “They laughed when I sat down at the piano” of laboratory advertising. There should be an awards show and a coffee table book about this ad.

The Polytron ad keeps getting shared. On Reddit, you can spot it on r/vintageads, r/WTF, and elsewhere. It popped up on science Twitter when that was a thing. The Polytron has entered popular (laboratory) culture in a big way. It’s Kevin Simler’s “cultural imprinting” effect in action, within a subculture. And it’s effective. Try finding a lab that processes samples and doesn’t have a Polytron, and look how many scientific papers include Polytron in their materials and methods.

But I have never seen a Polytron used on an entire mouse. Even mouse researchers generally instead [icky mouse processing redacted, you’re welcome]. The ad is terribly non-personalized. The cultural imprinting effect of an long-running campaign, and the attention-getting effect in the reader’s imagination, outweigh the effect that could have been achieved by dropping in an “AI” headline that personalizes a sample type and homogenization time for each reader based on their own research interests.

Cultural imprinting isn’t just a mass media thing, like the often-repeated beer jingles that George Tannenbaum (and many others) remember from baseball games on the radio. Cultural imprinting can work in a subculture or community of practice, if you meet the people where they are. And trying to do that with general-purpose surveillance advertising is less and less effective for more and more communities, where the most engaged people are getting the best privacy protections. Advertising to subcultures and communities of practice is hard, and it gets both harder and more interesting when the people being advertised to are making a point of blocking or even spoofing the conventional measurement tools. Higher-quality ad creative, coupled with high-reputation media buys or sponsorships, are going to be increasingly important for reaching low-surveillablity niche customer communities.

What reminded me of this was The Paradox Of Personalization: Billions Of AI-Tailored Ads Creates A Measurement Mess by Erez Levin. We must reject the fantasy of infinite creative variations – not just because it is technically impossible but because it fundamentally misunderstands how advertising works for the vast majority of brands. (IMHO, brands are a cognitive hack that uses our existing monkey reputation brain wiring, that we’re already equipped with at the hardware level, to help us participate in markets, where are too new on an evolutionary time scale to have built-in support.)

Brands are built on a collective understanding of what a brand stands for. When you fragment that message into infinite, hyper-personalized silos, you destroy the macro-cultural signal that gives a brand its authority and prestige. It dilutes a shared asset into statistical noise.

Anyway, read the whole thing.

Nobody needs AI to search the Internet, court says in ruling against Google by Ashley Belanger. Potentially impacting all AI search engines and chatbots known to poorly paraphrase source links, a German court has ruled that Google is liable for false statements in AI Overviews. (icymi: fix Google Search to remove the “AI” slop and other crap)

The rise of prediction markets is creating new ethical headaches for journalists by Kaleigh Rogers. (The big underlying problem, though, is prediction markets free-riding on “oracle” information from news sources in order to resolve big-money contracts. In order for prediction markets to stay sustainable and honest, oracle services need to be expensive. More: Pay the oracle.)

VICTORY: Meta Strips Facial Recognition Code From Smart Glasses App After Public Outcry by Cooper Quintin and Rindala Alajaji. (Don’t worry, these features will be back. Time to establish policies and norms for excluding surveillance glasses from any spaces you control or have influence over.)

Ukraine Is Not Losing. Russia Is Not Winning. by Anne Applebaum. The AI-powered drone interceptors are made possible by a complicated network of radar systems, acoustic sensors, and other tools that hundreds of large and small Ukrainian tech companies are creating and updating every day, using data they get directly from soldiers like the ones I met. Almost none of these companies existed four years ago. They have emerged from a tech-literate civil society whose members changed their professions or their focus to help defend their country.

Exclusive: Americans Now Overwhelmingly Oppose New Data Centers Near Them by Robinson Meyer. (But does this opposition translate into minimizing “AI” usage, or cutting back on “AI”-dependent products and services? I do notice that calling a feature “AI” makes people more likely to ask me how to turn it off.)

Advertising’s ‘most hated man’ is back with a new warning for CMOs by Lara O’Reilly. Mandel, who works as an advisor to marketing and tech companies, said his biggest bugbear about the industry now is principal media. The practice takes many forms, but at its essence, it’s when agencies purchase a large volume of media — spots where ads can run — at a discount, resell it to their clients, and make an undisclosed margin on top. (As a privacy nerd, I generally don’t have a beef with the actual advertisers—legit buyers and sellers have a shared interest in a win-win transaction. The problems are mostly with all the crooks in between those who are selling and those who are shopping.)

How Uber saved $35M a year on ads We did a holdout on Meta for 3 months. The results came back conclusively that there was no incrementality. With no ego, pride, budget manipulating, or any other crap I sometimes see, we made the decision to turn off spend on FB and return the money to the business.

It’s time to talk about my writerdeck on Veronica Explains. (Straightforward description of converting an old laptop to a text-only writing tool, with file sync to a more full featured system.)

This Blog Post is Your Sign to Start Self-Hosting You need datacenters to host GMail for everyone on earth, but you only need one small Linux box to run a very significant portion of your digital life.

Pirated Sports Streams Are Warping TV’s Most Important Ratings by James Hercher. To estimate the total missed audience that watched illegal streams of sporting events is practically impossible. Were the viewers hosting parties? Watching alone? Working at a bar or restaurant when they realized they didn’t have the right subscription and decided to pirate? With this in mind, the Super Bowl’s ratings were likely off by somewhere between one and two million total viewers, and that’s being conservative, Adalytics Founder and CEO Krzysztof Franaszek told AdExchanger.

Meat Industry Price Fixer Sentenced to Make Money by David Dayen. Most importantly, Agri Stats would still be able to issue its most critical reports, which ranked processors against their competitors on various metrics. These are the reports that tell processors when to cut supply or raise prices relative to others.

Not perfect—if a desktop RSS user switches clients or networks they get counted twice, but it does use the subscriber counts that services such as Feedbin and NewsBlur pass in the User-Agent header. And I think it fluctuates based on people trying different clients, scraper runs, and other trends. (When I get on “Hacker News” for something, there is always a bunch of weirdly configured bot traffic. A lot of it looks like requests for LLM-generated URLs that I might have used but never did.)

This is basically following the method in Easy SVG sparklines by Alex Plescan, except that in order to work as an img, the SVG file needs an XML namespace. See SVG Not Showing in Browser? Fix It in 30 Seconds on the SVG Genie blog.

These [Facebook] accounts – and there are hundreds, possibly thousands of them – present themselves as the work of British patriots. In one typical, AI-generated video, a middle-aged man claims his local cafe “has stopped serving pork, bacon and sausages just to avoid offending people”. Another post from the same account includes a sepia-tinted set of images of Victorian London, mourning a time when the city “was English, first-world and beautiful”. Alongside this type of reactionary nostalgia, it’s not unusual to see memes that call Islam a “cancer”, decry Muslims praying in public as an “invasion of the west” or promote the “great replacement theory” (which claims that white populations are being deliberately replaced by non-white immigrants).

For the past seven months, I have been investigating who is really behind pages like these. The answer, it turns out, is often young, entrepreneurial men from south Asia. They tend to have zero interest in UK politics, but the content they create often boosts far-right talking points in Britain and contributes to the increasingly hostile atmosphere for immigrants and British Muslims.

Read the whole thing: Who’s behind the Facebook page posting hateful AI slop about the UK? The answer might lie in south Asia.

The most important part about these “social media content creators,” from the point of view of Meta and the other Big Tech companies, is their material is cheap. Generative AI, low wages, zero research or news-gathering expenses—there is no way that a legit news site can compete in raw seconds of attention per currency unit. And they don’t just work in politics. There’s probably even more of this kind of slop about health-related topics.

Big Tech wins when they can move more ad money to support cheap slop and misinformation instead of more expensive content.

The problem for advertisers, of course, is the halo effect. Advertising just works better in a more trustworthy context. Content is not a commodity. Check that link for sources—I just added another one since I put that post up. Social science research and marketing research are notoriously hard to replicate, but the halo effect, along with a reverse halo effect for toxic content is one of those results that keeps replicating, no matter how inconvenient it is for the Big Tech companies that oligopolize the advertising market. Slop is just not a drop-in replacement for legit content as an advertising context.

Even though ad-supported content is not a commodity, the Big Tech companies of today are used to running a strategy that Joel Spolsky summed up as Commoditize your complements back in 2002, and that Bill Gurley wrote more about recently. For example, replace an expensive input like Sun servers with racks of generic PC servers, and replace expensive licensed software with open source. The biggest open source successes aren’t the acquisitions of Red Hat and other pure open source companies. The biggest impact has been internal. Google, and later Meta, answered the question “build or buy?” with neither, and chose to peer produce instead.

That peer production decision was, in many cases, a benign one. Big Tech “kernel teams” work on the Linux project, which regularly cranks out not a datacenter release and a mobile device OS release, but a general-purpose kernel release that even a low-budget developer can customize for almost anything you would need an OS for. The companies also support peer production of video codecs through the Alliance for Open Media. YouTube doesn’t have to pay for patent licenses—and as a side effect, neither does an independent filmmaker or the builder of a home media PC. Commoditizing the complement, when it works, causes a lot of the good stuff on the Internet. Imagine how dismal it would be to deploy even a basic database-backed CRUD application if open source databases such as if PostgreSQL hadn’t been supported by earlier developers. And the process continues in more adjacent IT markets. Today, RISC-V is a solid replacement for ARM for many uses.

The place where commoditization breaks down, though, is where there’s no commodity. Facebook Slop Guy is not a drop-in replacement for a legit site, even if you ignore the positive externalities of the latter. (For more on various theories on how advertising really works, or not, see The Anatomy of Humbug.)

The only way to fit Facebook slop (and crappy app store and search ads) into the same market niche as legit sites is, well,

Control the coinage and the courts—let the rabble have the rest. — The Padishah Emperor, in Dune by Frank Herbert

If the attribution cartel can control the standards for how advertising results are measured (and do the math in an obfuscated way, hidden from third-party checking) then all of a sudden Facebook Slop Guy isn’t just a commodity replacement for a legit site, he’s a better choice, with ROAS going up and to the right. That’s what I was on about in What Happens When The Attribution Cartel Meets Advertising’s Halo Effect?.

Commoditizing the complement is great when the commodity product is a viable replacement for the scarce, costly original. But the attribution cartel is trying to use the wrong tool for the job. There is some hope here, because commodification strategies don’t always work.

• Lindows, later Linspire, was a high-profile project to do a desktop operating system compatible with Microsoft Windows.

• Open Source Applications Foundation intended to produce an open-source, interoperable personal information management suite (like a replacement for Microsoft Outlook+Exchange)

Both of those went up against Microsoft, and there’s no Microsoft this time. Just a lot of companies of all sizes that are either in the ad-supported publishing business, or the advertising agency business. But the failures didn’t just fail just because of who the adversary was. A big part of their story arc was getting too much attention, too soon. Neither one was ready. The time for a commoditize the complement project to become a story is when it’s capable of successful niche projects, like Linux print servers. If it gets too much ink too early, it can flame out. Fortunately, the attribution cartel is not ready. By W3C’s own standards, they have a bunch of outstanding issues.

Instead of rushing to make a decision, W3C members should heed some wise advice: Don’t click. Count! Let’s count to 9 together.

1. Paradoxical increase in user privacy risks. See Methodological concerns regarding Attribution Level 1 and causal measurement. Although the system has some privacy properties when considered in isolation, in the context of the real web it increases incentives for “more first-party identity harvesting” and other problematic practices. So it creates more, not less, privacy risk for end users. Making an ad that actually sells a product or service is much harder than using surveillance data to identify someone about to buy and getting an ad in front of them. ML systems “learning” to optimize the attribution reports will tend to do better with more surveillance data to pursue the second option.

2. Structural bias toward channels positioned closest to observable conversion activity, including search, retail media, retargeting and click-oriented social advertising. The W3C Is Making A Mistake About Measuring Advertising Effectiveness. This proposal would tend to drive ad money toward “lower funnel” Big Tech placements such as search, social, and app store ads—depriving users of some positive externalities of legit ad-supported content and exposing them to more negative externalities from social media.

3. Incentives to suppress the “halo effect” of running ads on trusted sites. All of the attribution cartel companies are under pressure to shift ad spend from the “open web” to their own contexts. We might be able to trust the current developers working on the project to stay honest, but we have to consider who might be running this thing a couple rounds of layoffs from now. (The “pivot to video” saga shows what happens when marketing data meets pressure to produce the “right” results for some hot new strategy.)

4. Problematic USA centralization. In a world where tech sovereignty is trending, and A Handful of Companies Control the Web this proposal would hand control of a new information chokepoint to a few large companies here in the USA. A politician here could impose content-based punishments on sites worldwide, by requiring compliant Big Tech platforms to deny or filter the attribution reporting available to their advertisers, even advertisers outside the USA.

5. Sustainability. This proposal lacks a sustainability section. Even an estimate would provide some help to advertisers and agencies that want to report on emissions or general environmental impact.

6. Missing GPP support. Instead of handling the industry-standard Global Privacy Protocol, this proposal creates an extra, error-prone, compliance coding problem for every GPP-using site. This violates W3C’s Web Platform Design Principles: User needs come before the needs of web page authors, which come before the needs of user agent implementors, which come before the needs of specification writers, which come before theoretical purity. (Considered as a work of theoretical purity, this proposal might be just fine, but in practice it would offload the GPP detail work onto web sites, and extra risks onto users, when GPP support could have been handled by spec writers and user agent implementors.) (Issue #450)

7. A step backward on support for extensions. A similar system propsed as part of Google Chrome’s “Privacy Sandbox” implemented a chrome.privacy API, which helped users by letting extensions turn the ad features off. But this proposal omits the extension API, and makes extensions inject a script. (Issue #449)

8. No simulated data. Some of the companies behind this proposal already have conventional tracking data that they could have used to show how the attribution reports would have come out if the system had been in effect. If they had evidence to contradict items 1-3 they could have shown it already.

9. Public policy and lobbying considerations. Although the attribution reports are of limited use for professional marketers because of issues 1-3 above, the reports will be very useful for Big Tech companies making claims about how small businesses depend on them. Everyone who works on any privacy or competition issues is going to have to deal with papers based on this data popping up in any argument about restricting Big Tech in any way.

That’s about it. Anyway, please think before you click.

The attribution cartel companies haven’t released any data to back up a claim to the contrary. They claim benefits to legitimate sites, but so far, it’s all hypothetical.

The weird part is that several of the attribution cartel companies already have extensive tracking data. So where is the study showing how the attribution reporting would have come out, if the users in the history dataset had had attribution tracking turned on?

Absence of evidence is not always evidence of absence, but absence of a report that (1) could have been produced based on existing data and that (2) could make a strong case for the data holder’s position is at least sus.

A good example of the simulation approach is Inferring Users’ Demographics and Sensitive Interests Using the Topics API by Athicha Srivirote, Muhammad Abu Bakar Aziz, Jeffrey Gleason, Desheng Hu, and Christo Wilson. That study did not use the in-browser Topics API. Instead, the researchers calculated what the Topics API data would have shown based on a conventional browsing history data set—and got the results that many expected (but that Google somehow chose not to check at the time).

Personally, I would bet that the structural bias shows up in an unavoidably clear way, just because if it wasn’t there we would have heard by now. They have the data to get it through based on data—so why aren’t they using it? Why are they relying on the same kind of rush tactics that Craig Newmark and the Count warned us about? W3C doesn’t have to YOLO the Attribution proposal. An accurate simulated attribution report would help to “think before you click” and make an informed decision.

Such success stories are increasingly hard to find these days. One insidious, and perhaps unexpected, reason: the rise of online surveillance, enabled by the unrestricted mining and exploitation of consumer personal data.

Many technology companies track users’ every move through the digital world, amass detailed dossiers about consumer habits, hobbies and preferences, and repeatedly sell that data to the highest bidders. That means consumers are constantly served online ads based on information that was never intended to be shared with anyone.

These ads prompt many shoppers to turn away from local vendors, and buy instead from big corporations that utilize their leverage and wider supply chains to undercut local businesses on price.

And the beneficiaries of cross-context tracking aren’t just big retailers competing on scale or “partnerships.” Much of the benefit of cross-context tracking flows to obvious fraudulent advertisers.

The Big Tech companies don’t exactly “sell…data to the highest bidders.” What happens inside a big platform when a small business runs an ad is an auction: the legitimate ad must bid for impressions against other ads—and the Big Tech companies add extra bidders to drive up the price. And the price has to keep going up. Companies that already dominate a market that’s growing at single-digit rates have to keep taking a bigger piece of the action from every sale in order to sustain their own startup-like, double-digit growth rates. The result is an online scam crisis that benefits only Big Tech and the scammers.

It’s time to rethink state privacy laws in the context of scam culture. State laws can be win-win when they focus not on the “compliance” paperwork that Big Tech has already learned how to offload, but on reducing the real-world privacy harms that result in losses to scams and value extraction by Big Tech. (For example, state laws that focus on “data brokers” are effective against the “Lumascape” of legacy adtech firms, but not against the Big Tech platforms where data checks in but doesn’t check out.)

Most of the large-scale privacy harms to users are side effects of various schemes that Big Tech is running against either the creators of ad-supported resources or the buyers of advertising. Some of those schemes are run openly, like the bogus attribution reports thing, and some are behind the corporate firewalland hard to analyze. A kind of cheat code for privacy protection would be state laws that protect advertisers. Everyone else would win as an unavoidable side effect—customers are on the same side as legitimate businesses, because every win-win deal has two sides. It’s basic accounting: a positive outcome for a consumer means that some honest company made a sale, and a negative outcome means some money that won’t get spent or invested.

More: Suspicion and slop in the rugpull economy

Another very useful, though more limited, way of gaining familiarity with war in peacetime is to attract foreign officers who have seen active service. Peace does not often reign everywhere in Europe, and never throughout the whole world. A state that has been at peace for many years should try to attract some experienced officers—only those, of course, who have distinguished themselves. Alternatively, some of its own officers should be sent to observe operations, and learn what war is like.

However few such officers may be in proportion to an army, their influence can be very real. Their experience, their insights, and the maturity of their character will affect their subordmates and brother officers. Even when they cannot be given high command they should be considered as guides who know the country and can be consulted in specific eventualities. — Carl von Clausewitz (In On War, chapter 8, as translated by Michael Howard and Peter Paret) (PDF)

Platforms increasingly optimize ad delivery toward users already likely to convert. Consumers already in-market naturally generate more searches, retailer visits, social engagement, commerce activity and measurable lower-funnel signals. Attribution systems, therefore, risk confusing underlying purchase propensity with advertising persuasion. The result is a structural bias toward channels positioned closest to observable conversion activity, including search, retail media, retargeting and click-oriented social advertising.

The structural bias problem is related to, but not the same as, the problem I covered in What Happens When The Attribution Cartel Meets Advertising’s Halo Effect? Because of the way that big companies work, even if the attribution tracking did start to go in the direction of producing a right answer, it wouldn’t be allowed to. Either way:

If attribution systems systematically overcredit lower-funnel media environments already optimized around purchase intent, advertisers risk steering billions of dollars toward channels that harvest existing demand rather than create new demand.

Those big platform companies don’t just sit back and snipe unearned ad revenue. Extra ad money diverted to search, social, and app store advertising will fund risky data practices, fraud and extremism that harm everyone, while people are deprived of the positive externalities of other kinds of ad-supported media.

But none of these fine points of advertising data science are news to the attribution cartel companies. They can read the literature as well as anyone, and could even simulate attribution cartel results using their existing first-party data (like Google could have used in-house data to see the Inferring Users’ Demographics and Sensitive Interests Using the Topics API problem.)

But for the attribution cartel, getting the wrong answer is the point. That’s because marketing data science experts aren’t the most important audience for attribution reports—state legislators are.

Big Tech lobbyists already show up with voluminous research that doesn’t really hang together to back up their claims that legitimate businesses depend on Big Tech advertising. If the attribution cartel succeeds at W3C, they will be able to level up from existing misleading claims to extra-strength misleading claims, mathematically peer-reviewed and standardized. And—considering the lobbying coverage Big Tech can afford compared to the rest of us, they will have a lot of opportunities to use them.

Privacy concerns?

Fraud risks?

Noise and land use issues with data centers?

Too bad! This attribution data says that all businesses in the state depend on Big Tech advertising to sell anything.

Anyway, considered as a pure math project, the attribution proposal is probably fine. Give it a gold star. But whatever you do, don’t let it on the real web—take it out in the desert and bury the damn thing before the lobbyists start using it.

(Title borrowed from the Trix Rabbit, “who has been seeking the fruit flavor of Trix since 1959.”)

More: Think before you click

The three companies (along with Mozilla, which is on one of their “ad features in the browser” kicks again) are drawing up a built-in advertising measurement system, called Attribution Level 1, as a standard feature of web browsers. The system is intended to measure the effectiveness of advertising by enabling advertisers to correlate “impressions,” the occasions on which someone saw an ad, with “conversions,” when people bought something.

Don’t look for a section on permissions or consent in that document, by the way. There isn’t one. And nothing about nerd lawyer stuff like “opt out of sale” or “objections to processing” in there, either. The Big Tech companies want a two-track system, where other companies’ ad features are required to do all the privacy regulation hassles, but the browser’s own built-in tracking feature is something that people have to find the right setting for and turn off.

Unfortunately, this is not just a chapter in Big Tech’s ongoing antitrust saga. The attribution cartel is on track to perpetrate real harms to users, including:

• Built-in advantage for search, social, and app store advertising: More money for Big Tech, less for legit sites and other ad-supported resources.

• Added incentives for riskier tracking: Obfuscating the source of a sale makes it easier to get a payoff from tracking practices that would be seen as problematic on their own—which means that the attribution tracking feature, technically “privacy-preserving” in isolation, would cause more privacy violations as part of the whole online advertising system.

Those consequences are unavoidable because of the proposal’s narrow, mathematical privacy goals, which are a mismatch for the kinds of privacy harms that people experience in the real world. In the “Privacy Considerations” section, the proposal says,

The main privacy goal of this API is to ensure that providing sites with the ability to perform attribution does not improve their ability to perform cross-site recognition.

The system is supposed to produce aggregated measurements while making it prohibitively difficult for an advertiser to discover whether any one person who bought something is the same person who saw an ad. Technically, the way it works is that a script running on a site with ads asks the browser to record an ad impression. Then the browser keeps a record of ads seen from all the sites you visit. Later, when you buy something, the retail site can ask the browser to generate a “conversion report” that can be passed to a centralized aggregation service. The aggregation service can then give the site some aggregated results, in a way that does not reveal whether any individual who bought something ever saw a particular ad or visited a particular site.

So why are the same companies that are notorious for tracking people so fired up about it? The problem is that the attribution tracking won’t be functioning in isolation. It has to interact with other technologies and business models. Even if the browser developers can pull off their ambitious goal of preventing “cross-site recognition,” the proposal would make life worse on the real Internet.

Back before the whole economy-wide trust collapse really got going, I used to see NFL and NBA games on TV, and some of the most frequently advertised products were for home and yard care. Sherwin-Williams stains. Scotts Products to seed and fertilize your lawn. Replacement windows (I don’t remember the brands). Everything the diligent house and yard maintainer needs.

Today, though. the NFL and NBA are all about the gambling ads. Which is a decision that’s going to come back on them in a decade or so. Because gambling displaces savings. Many of today’s young sports fans, instead of getting on track to save up for a house, are getting into financial trouble that they won’t get out of in time to get a down payment together. The leagues are burning a future well-off audience, ready to be monetized with house-related advertising, in exchange for a quick cash hit from the gambling apps today.

• Even if the mathematical properties of the Attribution proposal make it infeasible to reidentify users using just the attribution data, in the real world this new form of tracking would add user privacy risks—by hiding the process of “stealing attribution” and creating more incentives to collect data in riskier ways.

• The attribution cartel can hide the halo effect of advertising on trusted sites, and drive more ad budgets to search, social, and app store ads.

One of the responses I got to the second one was, well, at least the Attribution proposal is something, and something is better than nothing. I doubted that, since in general you’re better off knowing what you don’t know, so I asked Rick Bruner from Central Control some questions.

Here’s what we came up with: Q&A: Marti & Bruner discuss the problematic W3C proposed measurement standard ‘Attribution Level 1’ — Central Control. And it turns out that the situtation is even worse than what I covered last month.

• Even if fraud operators are unable to exploit the complexity of the Attribution proposal to add more costs, risk and noise (which fraud hackers have been able to do every other time complexity increased)…

• Even if the Big Tech companies somehow decide not to unfairly favor their own products (for the first time ever)…

• Even if the extra processing and resource consumption required for the Attribution proposal’s mathematical goals turns out to be affordable and politically acceptable…

• And even if the design is bug-free and browsers implement it perfectly…

Then the reports that the attribution cartel can produce will still be actively misleading.

For what it’s worth, I don’t think the developers of the Attribution proposal are deliberately putting deception into the design of the system. I’m assuming that the developers are well-intentioned and that the design and code somehow achieve their goals perfectly. But it’s still important to consider the Attribution proposal as it would interact with the Web as it is in the real world, not in isolation.

And yes, I asked if it’s possible to tell (1) a pizza ad that actually sold someone a pizza apart from (2) a pizza ad placed using speech to text, targeting people who are already talking about pizza. Rick’s answer is informative—please read the whole thing.

Update: [attribution] Methodological concerns regarding Attribution Level 1 and causal measurement by Rick Bruner, on the public-patwg mailing list at W3C. (Also The Measurement Problem Inside the W3C Attribution Standard on LinkedIn)

There’s an insider group betting ‘almost exclusively’ on imminent U.S. military actions by Hunter Lazzaro. (Another reason why the best use of prediction markets is inside companies, but you should know that by now.)

I Feel For Those Laid Off by Meta, and Why More Must Go by Kelly Stonelake. I’d like to say this is offered without judgment, but that would not be true. What is true is that I offer it with the same judgment I’ve reserved for myself for staying as long as I did.

AT&T sues California in attempt to shut off old phone network by Jon Brodkin. (This is not just about POTS vs. wireless and fiber. The vintage phone lines have an older, more consumer friendly regulatory model, while the new services are under the most one-sided contracts that AT&T can come up with.)

‘How Deepfakes Tore a High School Apart’ by Nick Heer. (If the attribution cartel gets its way, more ad money gets redirected to the Big Tech app stores, that enable stuff like this, just saying.)

Google is replacing search results with only the AI by David Gerard. (Or not—my fix Google Search setup still works, for now.)

The EU Is Going Through a Trump-Fueled Breakup With Big Tech by Matt Burgess and Vittoria Elliott. Across Europe—as well as in Canada—politicians have been increasingly vocal about ditching US technology since the start of the second Trump administration. The Netherlands, Austria, Belgium, Denmark, and Finland all have ongoing sovereignty efforts, with German officials and regions also prominently pushing the movement. In December, eight countries, including France and Germany, announced they would partner on their efforts.

The ‘warrior ethos’ promises victory — history says it leads to defeat by John Broich. A fascist regime that treats democratic constraints as obstacles is likely to decide inconvenient information is an obstacle too. Because of this, in fascist governments, loyalists rank higher than experts. Fascist systems don’t remove people for being wrong; they remove them for insufficient loyalty. The man who tells the leader what he wants to hear rises.

Google is going to ruin the internet by Katie Notopoulos. (Going to? I had to check the date. The ad “safety” reports show that the ruination is already in progress.)

Massive Crypto ATM Company Bitcoin Depot Is Shutting Down as the Whole Industry Collapses by Bruce Gil. (That’s one end of the scam chain, but taking out the Meta end will probably be harder.)

Who’s behind the Facebook page posting hateful AI slop about the UK? The answer might lie in south Asia by Niamh McIntyre. (If the attribution cartel gets its way, more ad money gets redirected to the Big Tech social media platforms that enable stuff like this, just saying.)

Technoplasmosis: Big Tech Marketing Exposed by Adel Borky. These organizations are not merely participants in the advertising industry; they are its epistemic gatekeepers. By institutionalizing concepts like programmatic targeting, multi-touch attribution, and performance-based media as unquestioned “best practices” they have engineered a paradigm in which their own platform dynamics are mistaken for universal marketing truths.

r/uBlockOrigin handles an ad blocker blocker issue, in about a day. As many open-source projects suffer security and burnout problems it’s encouraging to see one that stays motivated and moves fast.

The Enshittification of History by Charlie Stross. With 20/20 hindsight, what I missed was the now-obvious wave of media ownership consolidation, including corporate social media such as X, Meta, and Google, in the hands of a narrow class of billionaire oligarchs. (Attribution cartel again, once you see them you can’t un-see them.)

The (Uncertain) Future of Media by Brian Jacobs. Money continues to flow out of more ‘traditional’ domestic media forms towards the giant US-based online platforms. Around two-thirds of all UK ad pounds currently make that journey. (And if the attribution cartel continues…all right, I’ll stop)

Advertising’s new ‘safety’ fight by Lara O’Reilly. Cross-industry efforts are taking shape to demand more transparency from tech giants like Google and Meta. Industry groups are pushing for more action around AI ad auction transparency and the responsible use of AI tools in marketing. (This smells like one of those “industry-wide problems” that people just agree not to solve. The problem for marketers, though, is that adding technical complexity to some great evil can dilute a participant’s understanding, but not culpability.)

• The capabilities of “AI agents” keep going up. Software projects will be able to do something like Tim Sehn’s A Week In Gas Town, but for more categories of software, including applications with featureful GUIs.

• Big AI wins copyright and related cases. On the AI-max timeline, politicians agree with Anna of Anna’s Archive that Copyright reform is necessary for national security, and while they’re at it, they nerf a bunch of content-related contracts including licenses, EULAs, and ToSs too. Maybe even patents. IP Maximalism continues to go out of fashion. So far it looks like Bright Data has some powerful friends, and is winning in court.

• Inference and other runtime costs stay reasonable or come down. The usage-based pricing problem turns out to be a nothingburger, the pricing Time Bomb detonation turns out to be just a blip, competition and technological advances drive prices down, all is well for vibe coding budgets. Maybe Ben Thompson’s Inference Shift happens, maybe something else?

All of those would need to happen, but what if they do? On that timeline, things would get interesting in a lot of ways. One of the biggest would be, let’s call it “Vibeshop,” the AI-built clone of Adobe Photoshop—or more like clones plural, since the project could make a variety of builds, each capturing the points in Photoshop’s history when some group of artists really liked it.

In Adobe Has Rid Itself of Its Allies, Nick Heer explains the Creative Cloud product direction, which helps explain why Photoshop is a good target for a vibe clone.

I think Adobe has actually shipped worse products as a result of this strategy — and, for once, I will avoid making it all about bugs, of which there are many. Adobe’s applications are more capable than they ever have been, but they are also often worse for professionals in actual use as a direct result of the company’s software-as-a-service model.

Users have to turn on Quiet Mode to avoid upsells. And Adobe’s ‘Modern’ User Interface Is Just Webpages.

Another reason Photoshop would be a good early target for an automated clone would be all the existing books and training videos that could be turned into test cases. (Remember, this is on the timeline where copyright and licenses get weakened because AI lobbying and/or competition with the PRC.) The Vibeshop “agents” could run a pre-ACC Photoshop in a VM, work through the tutorial, and keep tweaking their own code until results match. (Yes, this is also the timeline where LLM APIs get cheap.)

A company built around Vibeshop could offer the bleeding edge releases for free, plus supported releases of particular setups for artists who are used to having things one way and don’t want to change. And yes, the company that sells subscriptions might not be the same company that runs Photoshop in a VM in a license-violating way, but in a world where Google can make ad revenue from obvious infringing sites, we know that it’s possible to stand up enough insulating layers to make it work.

Of course, Adobe could always do Vibeshop to themselves, as Sun Microsystems could have done if they acted on Larry McVoy’s Sourceware Operating System Proposal instead of letting Linux eat their lunch. The existence of Vibeshop could turn into a long-term political asset for the company and the industry, too. One reason that firearms manufacturers have a loyal political constituency and IT companies don’t is that in the firearms business, management is smart enough not to periodically alienate the best customers. A customer can walk into a modern gun shop and buy a product that could have come from John M. Browning’s workbench more than a hundred years ago. What would happen if the same were true of software? (More: Learning from Second Amendment defenders)

The New Revolution in Military Affairs by Andriy Zagorodnyuk. Ukraine is championing a distributed, bottom-up innovation model with hundreds of firms and volunteer groups, close integration between frontline units and manufacturers, and research-and-development activity embedded directly in combat formations. Russia, by contrast, pursues a centralized approach…

Open and Closed: The Pursuit of Frontier Models by Stephen O’Grady. At a recent industry event, an AI executive likened the open models chasing their closed frontier counterparts to a pack of wolves…. Whether open will compete with closed, then, is not the interesting question. It always has, it always will. The question to ask is instead: how well? Put another way, will the “pack of wolves” ever catch their prey, and if so, how quickly?

A Speech to Europe 2026 »The European Moment« by Anne Applebaum. (also at What, actually, is European Civilization? but, you know, Substack.)

Influential study touting ChatGPT in education retracted over red flags by Jeremy Hsu. Since its publication, the study has been cited 262 times in other papers published by Springer Nature’s peer-reviewed journals and received a total of 504 citations from both peer-reviewed and non-peer-reviewed sources. It also attracted nearly half a million readers and received enough online attention to rank in the 99th percentile for journal articles in terms of attention score.

You can absolutely have an RSS dependent website in 2026 on matduggan.com. (fwiw, if you really want to get my feed as an email newsletter, use Feedrabbit - RSS and Atom web feed to email service. Just go to their site and paste in the URL of my site, welcome to my newsletter.

Newsmedia is the original everything app by Aram Zucker-Scharff. The model of American news organizations was always to be the home base for everything you did. Local events, business announcements, local news, national news, international wire service news. Ads made sense in that package because they were part of the service, they were also providing you with information about your community and things you wanted to know, just from a different angle.

The Hyperlocal Economics Nobody Wants to Admit by Yoni Greenbaum. (Only 17% of people in the USA have paid for any news product in the past year. What are these small-town news sites doing differently?)

No § 230 Immunity for Meta’s AI-Generated Ads by Eugene Volokh. These averments, taken as true, evidence a fact dispute over whether Meta contribute[d] materially to the alleged illegality of the advertisements. The alleged illegality stems from the advertisements’ content—i.e., the false statements made to Facebook and Instagram users that induced them to click on the ads. Plaintiffs have averred that Meta participated in the construction of the ads by literally generating, using artificial intelligence, the images and text in the advertisements. That degree of participation is not protected by section 230. (prediction: Google and Meta are going to set up the “AI” ad generation tools with a cut-out layer so they can claim the ad is the work of an “agency,” kind of like how Amazon.com uses “delivery partners” to be responsible for van crashes.)