Article

When All You Have Is a Robots.txt Hammer

Last year, Robb Knight figured out how Perplexity, an artificial intelligence search engine, was evading instructions not to crawl particular sites. Knight learned that Perplexity’s engine would use an unlisted user agent to scrape summaries of pages on websites where Perplexity was blocked. In my testing, I found the summaries were outdated by hours-to-days, indicating to me the pages were not being actively visited as though guided by a user. Aravind Srinivas, CEO of Perplexity, told Mark Sullivan, of Fast Company, it was the fault of a third-party crawler and denied wrongdoing.

This dispute was, I think, a clear marker in a debate concerning what control website owners have — or ought to have — over access to and interpretation of their websites, an issue that was recently re-raised in an article by Mike Masnick of Techdirt. Masnick explores scraper gating services offered by Cloudflare and Reddit’s blocking of the Internet Archive, and concludes the web is being cleaved in two:

There are plenty of reasons to be concerned about LLM/AI tools these days, in terms of how they can be overhyped, how they can be misused, and certainly over who has power and control over the systems. But it’s deeply concerning to me how many people who supported an open internet and the fundamental principles that underlie that have now given up on those principles because they see that some AI companies might benefit from an open internet.

The problem isn’t just ideological — it’s practical. We’re watching the construction of a fundamentally different internet, one where access is controlled by gatekeepers and paywalls rather than governed by open protocols and user choice. And we’re doing it in the name of stopping AI companies, even though the real result will be to concentrate even more power in the hands of those same large tech companies while making the internet less useful for everyone else.

This is a passionately argued article about a thorny issue. I, too, am saddened by an increasingly walled-off web, whether through payment gates or the softer barriers of login or email subscriptions. Yet Masnick misses the mark in ways I think he is usually more careful about.

In the second quoted paragraph above, for example, Masnick laments an internet “governed [less] by open protocols and user choice” than “controlled by gatekeepers”. These are presented as opposing qualities, but they are in fact complementary. Open protocols frequently contain specifications for authentication, allowing users and administrators to limit access. Robots.txt is an open standard that is specifically intended to communicate access rules. Thus, while an open web is averse to centralization and proprietary technologies, it does not necessarily mean a porous web. The open web does not necessarily come without financial cost to human users. I see no reason the same principle should not be applied to robots, too.

Masnick:

This illustrates the core problem: we’re not just blocking bulk AI training anymore. We’re blocking legitimate individual use of AI tools to access and analyze web content. That’s not protecting creator rights — that’s breaking the fundamental promise of the web that if you publish something publicly, people should be able to access and use it.

Masnick is entirely correct: people should be able to access and use it. They should be able to use any web browser they like, with whatever browser extensions and user scripts they desire. That does not necessarily extend to machines. The specific use case Masnick is concerned with is that he uses Lex as a kind of editorial verification step. When he references some news sites, however, Lex is blocked from reading them and therefore cannot provide notes on whether Masnick’s interpretation of a particular article is accurate. “I’m not trying to train an A.I. on those articles”, Masnick writes. “I’m just asking it to read over the article, read over what I’ve written, and give me a sense” if they jibe.

That may well be the case, but the blame for mistrust lies squarely with artificial intelligence companies. The original sin of representatives of this industry was to believe they did not require permission to ingest a subset of the corpus of human knowledge and expression, nor did they need to offer compensation. They did not seem to draw hard ethical lines around what they would consume for training, either — if it was publicly available, it could become part of their model. Anthropic and Meta both relied on materials available at LibGen, many of which are hosted without permission. A training data set included fan-made subtitles, which can be treated as illicit derivative works. I cannot blame any publisher for treating these automated visitors as untrustworthy or even hostile because A.I. companies have sabotaged attempts at building trust. Some seem to treat the restrictions of a robots.txt file as mere suggestions to be worked around. How can a publisher be confident the user-initiated retrieval of their articles, as Masnick is doing, is not used for training in any way?

Masnick is right, however, to be worried about how this is bifurcating the web. Websites like 404 Media have explicitly cited A.I. scraping as the reason for imposing a login wall. A cynical person might view this as a convenient excuse to collect ever-important email addresses and, while I cannot disprove that, it is still a barrier to entry. Then there are the unintended consequences of trying to impose limits on scraping. After Reddit announced it would block the Internet Archive, probably to comply with some kind of exclusivity expectations in its agreements with Google and OpenAI, it implied the Archive does not pass along the robots.txt rules of the sites in its collection. If a website administrator truly does not want the material on their site to be used for A.I. training, they would need to prevent the Internet Archive from scraping as well — and that would be horrible consequence.

Of course, Reddit does not block A.I. scraping on principle. It appears to be a contractual matter, where third-parties pay the company some massive amount of money for access. Anthropic’s recent proposed settlement supposed a price of a billion-and-a-half dollars would sufficiently compensate authors of the books it pirated. M.G. Siegler called this “pulling up a drawbridge” by setting a high cost floor that will lock out insufficiently funded competitors. Masnick worries about the same thing, predicting the ultimate winners of this will be “the same large tech companies that can afford licensing deals and that have the resources to navigate an increasingly complex web of access restrictions”.

To be sure, intellectual property law is a mess, and encouraging copyright maximalism will have negative consequences. The U.S. already has some of the longest copyright protections in the world, and which have unfortunately spilled into Canada thanks to trade agreements. But A.I. organizations have not created a bottom-up rebellious exploration of the limits of intellectual property law. They are big businesses with deep pockets exploiting decades of news, blogging, photography, video, and art. Nobody, as near as makes no difference, expected something they published online would one day feed the machines that now produce personalized Facebook slop.

Masnick acknowledges faults like these in his conclusion, but I do not think his proposed solutions are very strong:

None of this means we should ignore legitimate concerns about AI training or creator compensation. But we should address those concerns through mechanisms that preserve internet openness rather than destroy it. That might mean new business models, better attribution systems, or novel approaches to creator compensation. What it shouldn’t mean is abandoning the fundamental architecture of the web.

The “new business models” and “better attribution systems” are not elucidated here, but the compensation pitch seems like a disaster in the making to me. It is also from Masnick; here is the nut of his explanation:

But… that doesn’t mean there isn’t a better solution. If the tech companies need good, well-written content to fill their training systems, and the world needs good, high-quality journalism, why don’t the big AI companies agree to start funding journalists and solve both problems in one move?

What Masnick proposes is that A.I. companies could pay journalists to produce new articles for their training data. Respectfully, this would be so insubstantial as to be worthless. To train their models, A.I. companies are ingesting the millions of websites, tens of millions of YouTube videos, hundreds of thousands of books, and probably far more — the training data is opaque. It is almost like a perverse version of fair use. Instead of a small amount of an existing work becoming the basis of a larger body of work — like the quotes I am using and attributing in this article — this is a massive library of fully captured information. Any single piece is of little consequence to the whole, but the whole does not work as well without all those tiny pieces.

The output of a single journalist is inconsequential, an argument Masnick also makes: “[a]ny individual piece of content (or even 80k pieces of content) is actually not worth that much” in the scope of training a large language model. This is near the beginning of the same piece he concludes by arguing we need “novel approaches to creator compensation”. Why would A.I. companies pay journalists to produce the microscopic portion of words training their systems when they have historically used billions — perhaps trillions — of freebies? There are other ways I can think of why this would not work, but this is the most obvious.

One thing that might help, not suggested by Masnick, is improving the controls available to publishers. Today marked the launch of the Really Simple Licensing standard offering publishers a way to define machine-readable licenses. These can be applied site-wide, sure, but also at a per-page level. It is up to A.I. companies to adhere to the terms but with an exception — there are ways to permit access to encrypted material. This raises concerns about a growing proliferation of digital rights management, bringing me back to Masnick’s reasonable concern about a web increasingly walled-off and accessible only to authorized visitors.

I am not saying I have better ideas; I appreciate that Masnick at least brought something to the table in that regard, as I have nothing to add. I, too, am concerned about dividing the web. However, I think publishers are coming at this from a reasonable place. This is not, as Masnick puts it, a “knee-jerk, anti-A.I. stance” to which publishers have responded with restrictions because “[i]f it hurts A.I. companies, it must be good”. A.I. companies largely did this to themselves by raising billions of dollars in funding to strip-mine the public web without permission and, ultimately, with scant acknowledgement. I believe information should be freer than it is, that intellectual property hoarding is wrong, and that we are better when we build on top of each other. That is a fine stance for information reuse by fellow human beings. However, the massive scale of artificial intelligence training comes with different standards.

In writing this article, I am acutely aware it will become part of a training data set. I could block those crawlers — I have blocked a few — but that is only partly the point. I simply do not know how much control I reclaim now will be relevant in the future, and I am sure the same is true of any real media organization. I write here for you, not for the benefit of building the machines producing a firehose of spam, scams, and slop. The artificial intelligence companies have already violated the expectations of even a public web. Regardless of the benefits they have created — and I do believe there are benefits to these technologies — they have behaved unethically. Defensive action is the only control a publisher can assume right now.

The U.S.’ Increasing State Involvement in the Tech Industry

The United States government has long had an interest in boosting its high technology sector, with manifold objectives: for soft power, espionage, and financial dominance, at least. It has accomplished this through tax incentives, funding some of the best universities in the world, lax antitrust and privacy enforcement, and — in some cases — direct involvement. The internet began as a Department of Defense project, and the government invests in businesses through firms like In-Q-Tel.

All of this has worked splendidly for them. The world’s technology stack is overwhelmingly U.S.-dependent across the board, from consumers through large businesses and up to governments, even those which are not allies. Apparently, though, it is not enough and the country’s leaders are desperately worried about regulation in Europe and competition from Eastern Asia.

The U.S. Federal Trade Commission:

Federal Trade Commission Chairman Andrew N. Ferguson sent letters today to more than a dozen prominent technology companies reminding them of their obligations to protect the privacy and data security of American consumers despite pressure from foreign governments to weaken such protections. He also warned them that censoring Americans at the behest of foreign powers might violate the law.

[…]

“I am concerned that these actions by foreign powers to impose censorship and weaken end-to-end encryption will erode Americans’ freedoms and subject them to myriad harms, such as surveillance by foreign governments and an increased risk of identity theft and fraud,” Chairman [Andrew] Ferguson wrote.

These letters (PDF) serve as a reminder to, in effect, enforce U.S. digital supremacy around the world. Many of the most popular social networks are U.S.-based and export the country’s interpretation of permissive expression laws around the world, even to countries with different expectations. Occasionally, there will be conflicting policies which may mean country-specific moderation. What Ferguson’s letter appears to be asking is for U.S. companies to be sovereign places for U.S. citizens regardless of where their speech may appear.

The U.S. government is certainly correct to protect the interests of its citizens. But let us not pretend this is not also re-emphasizing the importance to the U.S. government of exporting its speech policy internationally, especially when it fails to adhere to it on its home territory. It is not just the hypocrisy that rankles, it is also the audacity requiring posts by U.S. users to be treated as a special class, to the extent that E.U. officials enforcing their own laws in their own territory could be subjected to sanctions.

As far as encryption, I have yet to see sufficient evidence of a radical departure from previous statements made by this president. When he was running the first time around, he called for an Apple boycott over the company’s refusal to build a special version of iOS to decrypt an iPhone used by a mass shooter. During his first term, Trump demanded Apple decrypt another iPhone in a different mass shooting. After two attempted assassinations last year, Trump once again said Apple should forcibly decrypt the iPhones of those allegedly responsible. It was under his first administration in which Apple was dissuaded from launching Advanced Data Protection in the first place. U.S. companies with European divisions recently confirmed they cannot comply with E.U. privacy and security guarantees as they are subject to the provisions of the CLOUD Act enacted during the first Trump administration.

The closest Trump has gotten to changing his stance is in a February interview with the Spectator’s Ben Domenech:

BD: But the problem is he [the British Prime Minister] runs, your vice president obviously eloquently pointed this out in Munich, he runs a nation now that is removing the security helmets on Apple phones so that they can—

DJT: We told them you can’t do this.

BD: Yeah, Tulsi, I saw—

DJT: We actually told him… that’s incredible. That’s something, you know, that you hear about with China.

The red line, it seems, is not at a principled opposition to “removing the security helmet” of encryption, but in the U.K.’s specific legislation. It is a distinction with little difference. The president and U.S. law enforcement want on-demand decryption just as much as their U.K. counterparts and have attempted to legislate similar requirements.

While the U.S. has been reinforcing the supremacy of its tech companies in Europe, it has also been propping them up at home:

Intel Corporation today announced an agreement with the Trump Administration to support the continued expansion of American technology and manufacturing leadership. Under terms of the agreement, the United States government will make an $8.9 billion investment in Intel common stock, reflecting the confidence the Administration has in Intel to advance key national priorities and the critically important role the company plays in expanding the domestic semiconductor industry.

The government’s equity stake will be funded by the remaining $5.7 billion in grants previously awarded, but not yet paid, to Intel under the U.S. CHIPS and Science Act and $3.2 billion awarded to the company as part of the Secure Enclave program. Intel will continue to deliver on its Secure Enclave obligations and reaffirmed its commitment to delivering trusted and secure semiconductors to the U.S. Department of Defense. The $8.9 billion investment is in addition to the $2.2 billion in CHIPS grants Intel has received to date, making for a total investment of $11.1 billion.

Despite its size — 10% of the company, making it the single largest shareholder — this press release says this investment is “a passive ownership, with no Board representation or other governance or information rights”. Even so, this is the U.S. attempting to reassert the once-vaunted position of Intel.

This deal is not as absurd as it seems. It is entirely antithetical to the claimed free market capitalist principles common to both major U.S. political parties but, in particular, espoused by Republicans. It is probably going to be wielded in terrible ways. But I can see at least one defensible reason for the U.S. to treat the integrity of Intel as an urgent issue: geology.

Near the end of Patrick McGee’s “Apple in China” sits a section that will haunt the corners of my brain for a long time. McGee writes that a huge amount of microprocessors — “at least 80 percent of the world’s most advanced chips” — are made by TSMC in Taiwan. There are political concerns with the way China has threatened Taiwan, which can be contained and controlled by humans, and frequent earthquakes, which cannot. Even setting aside questions about control, competition, and China, it makes a lot of sense for there to be more manufacturers of high-performance chips in places with less earthquake potential. (Silicon Valley is also sitting in a geologically risky place. Why do we do this to ourselves?)

At least Intel gets the shine of a Trump co-sign, and when has that ever gone wrong?

Then there are the deals struck with Nvidia and AMD, whereby the U.S. government gets a kickback in exchange for trade. Lauren Hirsch and Maureen Farrell, New York Times:

But some of Mr. Trump’s recent moves appear to be a strong break with historical precedent. In the cases of Nvidia and AMD, the Trump administration has proposed dictating the global market that these chipmakers can have access to. The two companies have promised to give 15 percent of their revenue from China to the U.S. government in order to have the right to sell chips in that country and bypass any future U.S. restrictions.

These moves add up and are, apparently, just the beginning. The U.S. has been a dominant force in high technology in part because of a flywheel effect created by early investments, some of which came from government sources and public institutions. This additional context does not undermine the entrepreneurship that came after, and which has been a proud industry trait. In fact, it demonstrates a benefit of strong institutions.

The rest of the world should see these massive investments as an instruction to build up our own high technology industries. We should not be too proud in Canada to set up Crown corporations that can take this on, and we ought to work with governments elsewhere. We should also not lose sight of the increasing hostility of the U.S. government making these moves to reassert its dominance in the space. We can stop getting steamrolled if we want to, but we really need to want to. We can start small.

‘Apple in China’

When I watched Tim Cook, in the White House, carefully assemble a glass-and-gold trophy fit for a king, it felt to me like a natural outcome of the events and actions exhaustively documented by Patrick McGee in “Apple in China”. It was a reflection of the arc of Cook’s career, and of Apple’s turnaround from dire straits to a kind of supranational superpower. It was a consequence of two of the world’s most powerful nations sliding toward the (even more) authoritarian, and a product of appeasement to strongmen on both sides of the Pacific.

Photo: Daniel Torok/White House.
Apple CEO Tim Cook sets up an engraved glass Apple disc on the Resolute Desk before President Donald Trump announces a $100 billion investment in the U.S., Wednesday, August 6, 2025, in the Oval Office. (Official White House Photo by Daniel Torok)

At the heart of that media spectacle was an announcement by Apple of $100 billion in domestic manufacturing investment over four years, in addition to its existing $500 billion promise. This is an extraordinary amount of money to spend in the country from which Apple has extricated its manufacturing over the past twenty years. The message from Cook was “we’re going to keep building technologies at the heart of our products right here in America because we’re a proud American company and we believe deeply in the promise of this great nation”. But what becomes clear after digesting McGee’s book is that core Apple manufacturing is assuredly not returning to the United States.

Do not get me wrong: there is much to be admired in the complementary goals of reducing China-based manufacturing and an increasing U.S. role. Strip away for a minute the context of this president and his corrupt priorities. Rich nations have become dependent on people in poorer nations to make our stuff, and no nation is as critical to our global stuff supply than China. One of the benefits of global trade is that it can smooth local rockiness; a bad harvest season no longer has to mean a shortage of food. Yet even if we ignore their unique political environment and their detestable treatment of Uyghur peoples — among many domestic human rights abuses — it makes little sense for us to be so dependent on this one country. This is basically an antitrust problem.

At the same time, it sure would be nice if we made more of the stuff we buy closer to where we live. We have grown accustomed to externalizing the negative consequences of making all this stuff. Factories exist somewhere else, so the resources they consume and the pollution they create is of little concern to us. They are usually not staffed by a brand we know, and tasks may be subcontracted, so there is often sufficient plausible deniability vis a vis working conditions and labour standards. As McGee documents, activist campaigns had a brief period of limited success in pressuring Apple to reform its standards and crack down on misbehaviour before the pressure of product delivery caught up with the company and it stopped reporting its regressing numbers. Also, it is not as though Apple could truly avoid knowing the conditions at these factories when there are so many of its own employees working side-by-side with Foxconn.

All the work done by people in factories far away from where I live is, frankly, astonishing. Some people still erroneously believe the country of origin is an indicator of whether a product is made with any degree of finesse or care. This is simply untrue, and it has been for decades, as McGee emphasizes. This book is worth reading for this perspective alone. The goods made in China today are among the most precise and well-crafted anywhere, on a simply unbelievable scale. In fact, it is this very ability to produce so much great stuff so quickly that has tied Apple ever tighter to China, argues McGee:

Whereas smartphone rivals like Samsung could bolt a bunch of off-the-shelf components together and make a handset, Apple’s strategy required it to become ever more wedded to the industrial clusters forming around its production. As more of that work took place in China, with no other nation developing the same skills, Apple was growing dependent on the very capabilities it had created. (page 176)

Cook’s White House announcement, for all its patriotic fervour, only underscores this dependency. In the book’s introduction, McGee reports “Apple’s investments in China reached $55 billion per year by 2015, an astronomical figure that doesn’t include the costs of components in Apple hardware” (page 7). That sum built out a complete, nimble, and precise supply chain at vast scale. By contrast, Apple says it is contributing a total of $600 billion over four years, or $150 billion per year. In other words, it is investing about three times as much in the U.S. compared to China and getting far less. Important stuff, to be sure, but less. And, yes, Apple is moving some iPhone production out of China, but not to the U.S. — something like 18% of iPhones are now made in India. McGee’s sources are skeptical of the company’s ability to do so at scale given the organization of the supply chain and the political positioning of its contract manufacturers, but nobody involved thinks Apple is going to have a U.S. iPhone factory.

So much of this story is about the iPhone, and it can be difficult to remember Apple makes a lot of other products. To McGee’s credit, he spends the first two-and-a-half sections of this six-part book exploring Apple’s history, the complex production of the G3 and G4 iMacs, and the making of the iPod which laid the groundwork for the iPhone. But a majority of the rest of the book is about the iPhone. That is unsurprising.

First, the iPhone is the product of a staggering amount of manufacturing knowledge. It is also, of course, a sales bonanza.

In fact, among the most riveting stories in the book do not concern manufacturing at all. McGee writes of grey market iPhone sales — a side effect of which was the implementation of parts pairing and activation — and the early frenzy over the iPad. Most notably, McGee spends a couple of chapters — particularly “5 Alarm Fire” — dissecting the sub-par launch sales of the iPhone XR as revealed through executive emails and depositions after Apple was sued for allegedly misleading shareholders. The case was settled last year for $490 million without Apple admitting wrongdoing. Despite some of these documents becoming public in 2022, it seems nobody before McGee took the time to read through them. I am glad he did because it is revealing. Even pointing to the existence of these documents offers a fascinating glimpse of what Apple does when a product is selling poorly.

Frustratingly, McGee does not attribute specific claims or quotations to individual documents in this chapter. Virtually everything in “5 Alarm Fire” is cited simply to the case number, so you have to go poking around yourself if you wish to validate his claims or learn more about the story.1 It may be worthwhile, however, since it underscores the unique risk Apple takes by releasing just a few new iPhones each year. If a model is not particularly successful, Apple is not going to quietly drop it and replace it with a different SKU. With the 2018 iPhones, Apple was rocked by a bunch of different problems, most notably the decent but uninteresting iPhone XR — 79% fewer preorders (PDF) when compared to the same sales channels as the iPhone 8 and 8 Plus — and the more exciting new phones from Huawei and Xiaomi released around the same time. Apple had hoped the 2018 iPhones would be more interesting to the Chinese market since they supported dual SIMs (PDF) and the iPhone XS came in gold. Apple responded to weak initial demand with targeted promotions, increasing production of the year-old iPhone X, and more marketing, but this was not enough and the company had to lower its revenue expectations for the quarter.

That Cook called this “obviously a disaster” is, of course, a relative term, as is the way I framed this as a “risk” of Apple’s smartphone release strategy. Apple still sold millions of iPhones — even the XR — and it still made a massive amount of money. It is a unique story, however, as it is one of the few times in the book where Apple has a problem of making too many products rather than too few. It is also illustrative of increasing competition from Chinese brands and, as emails reveal (PDF), trade tensions between the U.S. and China.

The fundamental heart of the story of this book is of the tension of a “proud American company” attempting to appease two increasingly nationalist and hostile governments. McGee examines Apple’s billion-dollar investment in Didi Chuxing, and mentions Cook’s appointment to the board of Tsinghua University School of Economics and Management. This is all part of the politicking the company realized it would need to do to appease President Xi. Similarly, its massive spending in China needed to be framed correctly. For example, in 2016, it said it was investing $275 billion in China over the following five years:

As mind-bogglingly large as its $275 billion investment was, it was not really a quid pro quo. The number didn’t represent any concession on Apple’s part. It was just the $55 billion the company estimated it’d invested for 2015, multiplied by five years. […] What was new, in other words, wasn’t Apple’s investment, but its marketing of the investment. China was accumulating reams of specialized knowledge from Apple, but Beijing didn’t know this because Apple had been so secretive. From this meeting forward, the days in which Apple failed to score any political points from its investments in the country were over. It was learning to speak the local language.

One can see a similar dynamic in the press releases for U.S. investments it began publishing one year later, after Donald Trump first took office. Like Xi, Trump was eager to bend Apple to his administration’s priorities. Some of the company’s actions and investments are probably the same as those it would have made anyhow, but it is important to these autocrat types that they believe they are calling the shots.

Among the reasons the U.S. has given for taking a more hostile trade position on China is its alleged and, in some cases, proven theft of intellectual property. McGee spends less time on this — in part, I imagine, because it is a hackneyed theme frequently used only to treat innovation by Chinese companies with suspicion and contempt. This book is a more levelheaded piece of analysis. Instead of having the de rigueur chapter or two dedicated to intellectual property leaving through the back door, McGee examines the less-reported front-door access points. Companies are pressured to participate in “joint ventures” with Chinese businesses to retain access to markets, for example; this is why iCloud in China is operated not by Apple, but by AIPO Cloud (Guizhou) Technology Co. Ltd.

Even though patent and design disputes are not an area of focus for McGee, it is part of the two countries’ disagreements over trade, and one area where Apple is again stuck in the middle. A concluding anecdote in the book references the launch of the Huawei Mate XT, a phone that folds in three which, to McGee, “appears to be a marvel of industrial engineering”:2

It was only in 2014 that Jony Ive complained of cheap Chinese phones and their brazen “theft” of his designs; it was 2018 when Cupertino expressed shock at Chinese brands’ ability to match the newest features; now, a Chinese brand is designing, manufacturing, and shipping more expensive phones with alluring features that, according to analysts, Apple isn’t expected to match until 2027. No wonder the most liked comment on a YouTube unboxing video of the Mate XT is, “Now you know why USA banned Huawei.” (pages 377–378)

The Mate XT was introduced the same day as the iPhone 16 line, and the differences could not have been more stark. The iPhone was a modest evolution of the company’s industrial design language, yet would be familiar to someone who had been asleep for the preceding fifteen years. The Mate XT was anything but. The phones also had something in common: displays made by BOE. The company is one of several suppliers for the iPhone, and it enables the radical design of Huawei’s phone. But according to Samsung, BOE’s ability to make OLED and flexible displays depends on technology stolen from them. The U.S. International Trade Commission agreed and will issue a final ruling in November which is likely to prohibit U.S. imports of BOE-made displays. It seems like this will be yet another point of tension between the U.S. and China, and another thing Cook can mention during his next White House visit.

“Apple in China” is, as you can imagine, dense. I have barely made a dent in exploring it here. It is about four hundred pages and not a single one is wasted. This is not one of those typical books about Apple; there is little in here you have read before. It answers a bunch of questions I have had and serves as a way to decode Apple’s actions for the past ten years and, I think, during this second Trump presidency.

At the same time, it leaves me asking questions I did not fully consider before. I have long assumed Apple’s willingness to comply with the demands of the Chinese government are due to its supply chain and manufacturing role. That is certainly true, but I also imagine the country’s sizeable purchasing power is playing an increasing role. That is, even if Apple decentralizes its supply chain — unlikely, if McGee’s sources are to be believed — it is perhaps too large and too alluring a market for Apple to ignore. Then again, it arguably created this problem itself. Its investments in China have been so large and, McGee argues, so impactful they can be considered in the same context as the U.S.’ post-World War II European recovery efforts. Also, the design of Apple’s ecosystem is such that it can be so deferential. If the Chinese government does not want people in its country using an app, the centralized App Store means it can be yanked away.3

Cook has previously advocated for expressing social values as a corporate principle. In 2017, he said, perhaps paraphrasing his heroes Martin Luther King Jr. and John Lewis, “if you see something going on that’s not right, the most powerful form of consent is to say nothing”. But how does Cook stand firmly for those values while depending on an authoritarian country for Apple’s hardware, and trying to appease a wanna-be dictator for the good standing of his business? In short, he does not. In long, well, it is this book.

It is this tension — ably shown by McGee in specific actions and stories rather than merely written about — that elevates “Apple in China” above the typical books about Apple and its executives. It is part of the story of how Apple became massive, how an operations team became so influential, and how the seemingly dowdy business of supply chains in China applied increasingly brilliant skills and became such a valuable asset in worldwide manufacturing. And it all leads directly to Tim Cook standing between Donald Trump and J.D. Vance in the White House, using the same autocrat handling skills he has practiced for years. Few people or businesses come out of this story looking good. Some look worse than others.

  1. The most relevant documents I found under the “415” filings from December 2023. ↥︎

  2. I think it is really weird to cite a YouTube comment in a serious book. ↥︎

  3. I could not find a spot for this story in this review, but it forecasts Apple’s current position:

    But Jobs resented third-party developers as freeloaders. In early 1980, he had a conversation with Mike Markkula, Apple’s chairman, where the two expressed their frustration at the rise of hardware and software groups building businesses around the Apple II. They asked each other: “Why should we allow people to make money off of us? Off of our innovations?” (page 23)

    Sure seems like the position Jobs was able to revisit when Apple created its rules for developing apps for the iPhone and subsequent devices. McGee sources this to Michael Malone’s 1999 book “Infinite Loop”, which I now feel I must read. ↥︎

‘Mood Machine’

The goals of art and commerce are basically opposite. Art fills our soul; it gives us emotional life. I have rarely heard anyone describe commerce similarly.

At its most ideal, the business of art enables more of it in greater variety, while allowing those who create it a reasonable living. This has rarely been the case. There are hundreds of years of unbelievably wealthy patrons building their cultural cachet by supporting artists of their particular taste and at their behest. More recently, recording contracts are routinely described as “brutal”, “a raw deal”, “predatory”, and “exploitative”. That has been generally true for all artists, but has been particularly pronounced for marginalized — and, to be more even specific, black — artists since the recording industry’s origins.

In “Mood Machine”, released earlier this year, Liz Pelly adds an additional complicating question: what is the relationship between art and commerce when massive data collection becomes routine?

The origins of streaming music may be found first in piracy and later in Rhapsody, but Spotify is where modern streaming platforms truly began. While Spotify’s founders tend to describe a noble birth, Perry points to a 2015 interview with co-founder Martin Lorentzon in which he describes the idea to build a targeted advertising platform first. How it would acquire users was an open question — “[s]hould it be product search? Should it be movies, [or ‘Godfather’], or audiobooks? And then we ended up with music”. That is not necessarily a bad thing. What is bad, though, is that Spotify reportedly began with an unlicensed library and made money on the back of it. That combination does not sound to me like the result of a love of music.

Sadly, the interesting storytelling does not reliably continue. Admittedly, part of the reason for this is my personal distaste for Pelly’s style of writing, something which I would not normally mention — surely not everyone is a fan of my writing style, either — but feel compelled to do so for how intrusive I found it. Far too many sections and chapters in this book end in a tedious turn of phrase: “Under the gaze of streaming surveillance, the exchange is never truly one-to-one;”; “It makes sense that as the digital world has grown to feel more like a shopping mall, it is also sometimes the very companies making music for shopping malls that are flooding its soundtrack”. Another part of the problem is the way this book is organized. Each chapter reads like an individual essay dedicated to a specific problem with Spotify — algorithmic suggestions, vibe-based playlists, and changing business terms, to name a few. What that looks like in practice is a great deal of repetition. I count at least seven chapters, of eighteen, dedicated to background and unfocused listening.

Part of the problem, however, is that Pelly has been documenting these phenomena for years in articles published at the Baffler. I am familiar with the extraordinary amount of “chill” music, trendy sound palettes, the relationship between mood-based music and targeted advertising, and the comparisons to Uber because these articles were all published a minimum of six years ago. That I remember these articles is sometimes a testament to Pelly’s reporting; at other times, it reminds me of things I previously found questionable but could not quite articulate why.

One thing I remember from one article, for example, is its attempt to define a “Spotify sound”. This was revisited in the book in the “Streambait Pop” chapter (page 82):

By the time of Spotify’s IPO in 2018, it seemed that the peak playlist era had produced an aesthetic of its own. That year, one pop songwriter and producer told me that [Billie] Eilish had become a type of poster child for what was being called a “Spotify sound,” a deluge of platform-optimized pop that was muted, mid-tempo, and melancholy. He told me it had become normal for him to go into a session and hear someone say they wanted to write a “Spotify song” to pitch around to artists: “I’ve definitely been in circumstances where people are saying, ‘Let’s make one of those sad girl Spotify songs.’ You give yourself a target,” he said. It was a formula. “It has this soft, emo-y, cutesy thing to it. These days it’s often really minimal and based around just a few simple elements in verses. Often a snap in the verses. And then the choruses sometimes employ vocal samples. It’s usually kind of emo in lyrical nature.”

Pelly’s argument is built primarily around the works of Charlotte Lawrence, Sasha Sloan, and Nina Nesbitt, none of which I am familiar with. But their music — “Normal” and “Psychopath” are both named in the article — sound like a lot of pop music trends of the time: a blend of genres that emerges kind of beach-clubby, pretty breathy, and electronics-heavy but not particularly danceable. Pelly quotes an indie rock label owner calling it “emotional wallpaper”.

In re-reading Pelly’s “streambait” article for this piece, I found this paragraph a good distillation of many arguments made throughout the book:

Musical trends produced in the streaming era are inherently connected to attention, whether it’s hard-and-fast attention-grabbing hooks, pop drops and chorus-loops engineered for the pleasure centers of our brains, or music that strategically requires no attention at all—the background music, the emotional wallpaper, the chill-pop-sad-vibe playlist fodder. These sounds and strategies all have streambait tricks embedded within them, whether they aim to wedge bits of a song into our skulls or just angle toward the inoffensive and mood-specific-enough to prevent users from clicking away. All of this caters to an economy of clicks and completions, where the most precious commodity is polarized human attention — either amped up or zoned out—and where success is determined, almost in advance, by data.

Much like the similar essays in “Mood Machine”, very little of this feels like it is directly traceable to Spotify or streaming generally. There has long been pop music that is earwormy, and pop music that is kind of a silence-filler. When radio was more influential, the former could be found on the contemporary hit radio station and the latter on any number of adult contemporary variants.

Coalescing around a particular sound is also not a Spotify phenomenon. The early 1990s brought an onslaught of Nirvana imitators, and the late 1990s polished the sound so hard it removed any trace of edge and intrigue it once held. The early-2000s dominance of Coldplay made way for the mid-2000s Timbaland production craze, which led to a wave of late-2000s dance and club pop, which was followed in the early-2010s by Americana revival. This is the power of radio. Or, it was the power of radio, at least. You could describe any of the chart-topping songs in similar terms as Pelly uses for “streambait”: “attention-grabbing hooks”, “chorus-loops engineered for the pleasure centers of our brains”, and “chill-pop-sad-vibe playlist fodder”. Should this be blamed on the precise listener analytics dashboard available to artists on Spotify? I am not sufficiently convinced.

Pelly describes a discussion she had with two teenagers outside an all-ages venue as they struggled to describe the “aesthetic rap” show they were attending, a genre which seems to be a slower and spacier take on rage (page 118):

The kids I spoke to outside Market seemed genuinely enthused. But as I headed home, I was struck by how palpably it seemed that most of those conversations were more concerned with a niche vibe fandom — which no one could even really explain — than the artists themselves.

I cannot imagine this is a new phenomenon. Some people develop a deep fascination with music and seek releases from specific artists. But plenty are only looking for a sound and a vibe. It is why retailers and magazines gave away sampler CDs in the mid-2000s scratching a generic indie rock itch.

What Pelly keeps describing in these chapters is a kind of commodification of cool, none of which is new or unique to Spotify. It is the story of popular culture writ large: things begin as cool for a small group, are absorbed into broader society, and are sold back to us by industry. This most often happens to marginalized communities who find community in vocabulary, music, visual art, and dance, and then it gets diluted as it becomes mainstreamed.

As noted, Pelly dedicates considerable space in the book to chill playlists — “‘Chilled Dance Hits,’ ‘Chilled R&B,’ and ‘Chilled Reggae’ were all among Spotify’s official playlist offerings, alongside collections like ‘Chillin’ on a Dirt Road,’ ‘lofi chill,’ and ‘Calm.'” (page 45). This is partly not the fault of Spotify; YouTube expanded the availability of live streams in 2013 and it resulted in plenty of samey chill hop stations. In a 2018 New York Times article about these nonstop live-streams, Jonah E. Bromwich writes:

Channels like College Music, ChilledCow, Chillhop Music and others are unlikely to have a broad impact on the music industry. But they represent an underground alternative to the streaming hegemony of Spotify and Apple Music. The industry commentator Bob Lefsetz said that while the stations were not likely to become a lucrative endeavor, they were a way for members of the public to seize power back from cultural gatekeepers.

Instead of being predominantly inspired or encouraged by Spotify, it is possible the growth of the background music genre is something the company is instead taking advantage of — and take advantage it did.

Whether on YouTube or Spotify, the beat-makers behind these tracks are loosely inspired by artists like J Dilla, but they have coalesced around a distinctly hazy and slowed-down instrumental palette. That these tracks are deliberately indistinct has led to Spotify commissioning low-royalty generic tracks and, as Pelly writes, this passivity is an area “where the imminent A.I. infiltration of music was most feasible: the replacement of lean-back mood music” (page 132).

All told, it sure sounds like Spotify aligned its recommendations to compel users into filling silence with music featureless enough it could be replicated by what are, in effect, stock tracks. If this was a deliberate strategy to allow Spotify to have lower royalty expenses, it has had a mixed effect. Setting aside the ongoing popularity of big pop stars like Taylor Swift and Justin Bieber — I would love to know how much of Spotify’s revenue is sent to those two artists alone — the rise of streaming also coincided with the explosion of in-your-face K-pop groups, renewed interest in rock music, and revivals of funk and disco. These are not the kinds of passive listening genres Pelly seems so concerned with.

That is not to say Spotify plays no influence in what is popular. Just as what was made popular on the radio brought a wave of imitators, so too is the case for an era where streaming is where most people listen to music. None of this is new. A streaming listener’s context is often quite similar to a radio listener’s, too. Pelly’s exploration of the chilled-out Spotify playlist and lean-back listener reads, to me, with considerable disdain. But that kind of passive listening was common in the radio days. People put music on in the car and at work all the time. My parents used to put a C.D. on when they were cooking dinner. I do not think they were captivated in that moment by the sounds of Genesis or the Police. I was listening to music while reading this book and writing this article. Sometimes, an album will get played as a background to other tasks; any musician is surely aware of this.

Perhaps you, too, are now seeing what I began to understand. What Pelly keeps gesturing at throughout this book — but never quite reaches — is that the problems Spotify faces are similar to that of any massive two-sided platform. Pick your case study of any of the large tech companies and you can find parallels in Spotify. It has hundreds of millions of subscribers; everything it does is at vast scale.

It has privacy problems. Pelly dedicates a chapter to “Streaming as Surveillance”, pointing to Spotify’s participation in the data broker and ad tech economy. Spotify suggests its ads can be targeted based on users’ moods correlated with playlist and song data. This, like so many other ad tech sales pitches, is likely an inflated claim with only limited success. Yet it is also a little creepy to consider it is what Spotify aspires its ad product to be.

Spotify, like many others, faces moderation problems. Spotify does not want to put too many limits on what music is accepted. In the best of circumstances, this makes it possible for a nascent artist to rise from obscurity and start a career. But there are financial incentives to gaming the system. There are people who will follow trends, and even commit outright fraud manually or with A.I.-generated material. This is true for other broadly available revenue machines — Google Ads and YouTube are two that immediately spring to mind. In an attempt to disincentivize these behaviours and reduce Spotify’s costs, the company announced in November 2023 it would stop paying royalties for tracks with fewer than one thousand annual streams. Pelly writes this “was part of a campaign waged by Universal Music Group to revamp streaming in its favor” (page 155). When Spotify rolled out this new royalty structure, UMG CEO Lucian Grainge bade good riddance to “merchants of garbage […] no one actually wants to listen to” (page 157). How much it actually hurts low-effort spammers is a good question, but it impacts legitimate indie artists — what Grainge calls “garbage” — for whom Spotify now presents no advantage over piracy.

I would not be so presumptuous as to say that is what this book ought to have been but, as a longtime reader of Pelly’s articles about the subject, I was frustrated by “Mood Machine”. It is the kind of book I wish would be taken apart and reassembled for better flow and a more coherent structure. Spotify and the streaming model have problems. “Mood Machine” identifies many of them. But the money quote — the one that cut through everything for me — is from an anonymous former Spotify employee (page 167):

“If Spotify is guilty of something, they had the opportunity at one point to change the way value was exhanged in the music industry, and they decided not to,” the former employee told me. “So it’s just upholding the way that things have always been.”

We treat art terribly. It is glamorous and alluring, but it is ultimately a plaything of the rich. The people who make money in art, no matter the discipline, are those responsible for its distribution, management, and sale. Those creating the actual work that enriches our lives too often get the scraps, unless they have enough cachet to dictate the terms in their favour.

Spotify is just another layer in the chain; another place that makes far more money than artists ever will. An artist understands they are signing up for a job with unpredictable pay, but Spotify’s particular structure makes it even more opaque.

The four biggest audio streaming platforms — Spotify, YouTube, Tencent, and Apple Music are the top-down force pushing culture in a particular direction, a level of influence Clear Channel’s executives could have only hoped for in its heyday. Streaming can help people learn about music they have never heard before. But it is not very effective as an artistic conduit. It is an ad-supported platform operating at global scale, much like a handful of other large tech companies, and it faces similar problems.

Yet none of them are as essentially tied to the distribution of art as is Spotify. It is a shame it did not create something to upend the status quo and made more artists more money. I guess part of the reason for that could be because its co-founders saw music as one of several interchangeable user acquisition strategies to sell advertisements — you know, for the love of art and music.

The Vagueness and Vagaries of ‘Personal Superintelligence’

Mark Zuckerberg is not much of a visionary. He is ambitious, sure, and he has big ideas. He occasionally pops into the public consciousness to share some new direction in which he is taking his company — a new area of focus that promises to assert his company’s leadership in technology and society. But very little of it seems to bear fruit or be based on a coherent set of principles.

For example, due to Meta’s scale, it is running into limitations on its total addressable market based on global internet connectivity. It has therefore participated in several related projects, like measuring the availability of internet connectivity worldwide with the Economist, which has not been updated since 2022. In 2014, it acquired a company building a solar-powered drone to beam service to people in more remote locations; the project was cancelled in 2018. It made a robot to wrap fibre optic cable around existing power lines, which it licensed to Hibot in 2023; Hibot has nothing on its website about the robot.

It is not just Meta’s globe-spanning ambitions that have faltered. In 2019, Zuckerberg outlined a “privacy-focused vision for social networking” for what was then Facebook, the core tenets of which in no way conflict with the company’s targeted advertising business. Aside from the things I hope Facebook was already doing — data should be stored securely, private interactions should remain private, and so on — there were some lofty goals. Zuckerberg said the company should roll out end-to-end encrypted messaging across its product line; that it should add controls to automatically delete or hide posts after some amount of time; that its products should be extremely interoperable with those from third-parties. As of writing, Meta added end-to-end encryption to Facebook Messenger and Instagram, but it is only on by default for Facebook. (WhatsApp was end-to-end encrypted by default already.) It has not added an automatic post deletion feature to Facebook or Instagram. Its apps remain stubbornly walled-off. You cannot even sign into a third-party Mastodon app with a Threads account, even though it is amongst the newest and most interoperable offerings from Meta.

Zuckerberg published that when it was advantageous for the company to be seen as doing its part for user privacy. Similarly, when it was smart to advocate for platform safety, Zuckerberg was contrite:

But it’s clear now that we didn’t do enough. We didn’t focus enough on preventing abuse and thinking through how people could use these tools to do harm as well. That goes for fake news, foreign interference in elections, hate speech, in addition to developers and data privacy. We didn’t take a broad enough view of what our responsibility is, and that was a huge mistake. It was my mistake.

Then, when it became a good move to be brash and arrogant, Zuckerberg put on a gold chain and a million-dollar watch to explain how platform moderation had gone too far.

To be clear, Meta has not entirely failed with these initiatives. As mentioned, Threads is relatively interoperable, and the company defaulted to end-to-end encryption in Facebook Messenger in 2023. It said earlier this year it is spending $10 billion on a massive sub-sea cable, which is a proven technology to expand connectivity more than a solar-powered drone could.

But I have so far not mentioned the metaverse. According to Zuckerberg, this is “an embodied internet where you’re in the experience, not just looking at it”, and it was worth pivoting the entire company to be “metaverse-first”. The company renamed itself “Meta”. Zuckerberg forecasted an “Altria moment” a few years prior and the press noticed. In announcing this new direction in 2021, Zuckerberg acknowledged it would be a long-term goal, though predicted it would be “mainstream in the next five to ten years”:

Our hope is that within the next decade, the metaverse will reach a billion people, host hundreds of billions of dollars of digital commerce, and support jobs for millions of creators and developers.

Granted, it has not been even four years since Zuckerberg made these announcements, but are we any closer to his company’s vision becoming mainstream? If you broaden the definition of “metaverse” to include all augmented and virtual reality products then, yes, it appears to be a growing industry. But the vision shown at Connect 2021 is scarcely anywhere to be found. We are not attending virtual concerts or buying virtual merch at virtual after-parties. I am aching to know how the metaverse real estate market is doing as I am unaware of anyone I know living in a virtual house.

As part of this effort, Meta announced in May 2022 it would support NFTs on Instagram. These would be important building blocks for the metaverse, the company said, “critical for how people will buy, use and share virtual objects and experiences” in the virtual environment it was building. Meta quickly expanded availability to Facebook and rolled it out worldwide. Then, in March 2023, it ended support for NFTs altogether, saying “[a]ny collectibles you’ve already shared will remain as posts, but no blockchain info will be displayed”.

Zuckerberg has repeatedly changed direction on what his company is supposed to stand for. He has plenty of ideas, sure, and they are often the kinds of things requiring resources in an amount only possible for a giant corporation like the one he runs. And he has done it again by dedicating Meta’s efforts to what he is calling — in a new manifesto, open letter, mission statement, or whatever this is — “personal superintelligence”.

I do have to take a moment to acknowledge the bizarre quality of this page. It is ostensibly a minimalist and unstyled document of near-black Times New Roman on a white background — very hacker, very serious. It contains about 3,800 characters, which should mean a document barely above four or five kilobytes, accounting for HTML tags and a touch of CSS. Yet it is over 400 kilobytes. Also, I love that keywords are defined:

<meta name="keywords" content="Personal 
Superintelligence, AI systems improvement, 
Superintelligence vision, Mark Zuckerberg 
Meta, Human empowerment AI, Future of 
technology, AI safety and risks, Personal
AI devices, Creativity and culture with 
AI, Meta AI initiatives">

Very retro.

Anyway, what is “superintelligence”? is a reasonable question you may ask, and a term which Zuckerberg does not define. I guess it is supposed to be something more than or different from artificial intelligence, which is yesterday’s news:

As profound as the abundance produced by AI may one day be, an even more meaningful impact on our lives will likely come from everyone having a personal superintelligence that helps you achieve your goals, create what you want to see in the world, experience any adventure, be a better friend to those you care about, and grow to become the person you aspire to be.

He decries competitors’ ambitions:

This is distinct from others in the industry who believe superintelligence should be directed centrally towards automating all valuable work, and then humanity will live on a dole of its output. At Meta, we believe that people pursuing their individual aspirations is how we have always made progress expanding prosperity, science, health, and culture. This will be increasingly important in the future as well.

I am unsure what to make of this. It is sorely tempting to dismiss the whole endeavour as little more than words on a page for a company deriving 98% of its revenue (PDF) from advertising.1 If we consider it more seriously, however, we are left with an ugly impression for what “valuable work” may consist of. Meta is very proud of its technology to “generate photorealistic images”, thereby taking the work of artists and photographers. Examples of its technology also include generating blog posts and building study plans, so it seems writing and tutoring are not entirely “valuable work” either.

I am being a bit cheeky but, with Zuckerberg’s statement entirely devoid of specifics, I am also giving it the gravitas it has earned.

While I was taking way too long to write this, Om Malik examined it from the perspective of someone who has followed Zuckerberg’s career trajectory since it began. It is a really good piece. Though Malik starts by saying “Zuck is one of the best ‘chief executives’ to come out of Silicon Valley”, he concludes by acknowledging he is “skeptical of his ability to invent a new future for his company”:

Zuck has competitive anxiety. By repeatedly talking about being “distinct from others in the industry” he is tipping his hand. He is worried that Meta is being seen as a follower rather than leader. Young people are flocking to ChatGPT. Programmers are flocking to Claude Code.

What does Meta AI do? Bupkiss. And Zuck knows that very well. You don’t do a company makeover if things are working well.

If you are solely looking at Meta’s earnings, things seem to be working just fine for the company. Meta beat revenue expectations in its most recent quarter while saying the current quarter will also be better than analysts thought. Meta might not be meeting already-low analyst expectations for revenue in its Reality Labs metaverse segment, but the stock jumped by 10% anyhow. Even Wall Street is not taking Zuckerberg seriously as an innovator. Meta is great at selling ads. It is not very exciting, but it works.

Back to the superintelligence memo, emphasis mine:

We believe the benefits of superintelligence should be shared with the world as broadly as possible. That said, superintelligence will raise novel safety concerns. We’ll need to be rigorous about mitigating these risks and careful about what we choose to open source. Still, we believe that building a free society requires that we aim to empower people as much as possible.

And here is what Zuckerberg wrote just one year ago:

Meta is committed to open source AI. I’ll outline why I believe open source is the best development stack for you, why open sourcing Llama is good for Meta, and why open source AI is good for the world and therefore a platform that will be around for the long term.

[…]

There is an ongoing debate about the safety of open source AI models, and my view is that open source AI will be safer than the alternatives. I think governments will conclude it’s in their interest to support open source because it will make the world more prosperous and safer.

No mention of being careful, no mention of choosing what to open source. Zuckerberg took an ostensibly strong, principled view supportive of open source A.I. when it benefitted the company, and is now taking an ostensibly strong, principled view that it requires more nuance.

Zuckerberg concludes:

Meta believes strongly in building personal superintelligence that empowers everyone. We have the resources and the expertise to build the massive infrastructure required, and the capability and will to deliver new technology to billions of people across our products. I’m excited to focus Meta’s efforts towards building this future.

On this, I kind of believe him. I believe the company has the resources and reach to make “personal superintelligence” — whatever it is — a central part of Meta’s raison d’être, just as Malik says in his article he has “learned not to underestimate Zuckerberg”. The language in Zuckerberg’s post is flexible, vague, and optimistic enough to provide cover for whatever the company does next. It could be a unique virtual assistant, or it could be animated stickers in chats. Whatever it is, this technology will also assuredly be directed toward the company’s advertising machine, as its current A.I. efforts are providing “greater efficiency and gains across our ad system”. Zuckerberg is telling investors imagine what we could do with superintelligence.

In December 2023, Simon Willison wrote about the trust crisis in artificial intelligence, comparing it to the conspiracy theory that advertisers use audio from real-world conversations for targeting:

The key issue here is the same as the OpenAI training issue: people don’t believe these companies when they say that they aren’t doing something.

One interesting difference here is that in the Facebook example people have personal evidence that makes them believe they understand what’s going on.

With AI we have almost the complete opposite: AI models are weird black boxes, built in secret and with no way of understanding what the training data was or how it influences the model.

Meta has pulled off a remarkable feat. It has ground down users’ view of their own privacy into irrelevance, yet its services remain ubiquitous to the point of being essential. Maybe Meta does not need trust for its A.I. or “superintelligence” ambitions, either. It is unfathomably rich, has a huge volume of proprietary user data, and a CEO who keeps pushing forward despite failing at basically every quasi-visionary project. Maybe that is enough.

  1. Do note two slides later the company’s effective tax rate dropping from 17% in Q3 and Q4 2023 to just 9% in Q1 2025, and 11% in the most recent quarter. Nine percent on over $18 billion in income. ↥︎

The Unknown Effect of Google A.I. Overviews on Search Traffic

Pew Research Centre made headlines this week when it released a report on the effects of Google’s A.I. Overviews on user behaviour. It provided apparent evidence searchers do not explore much beyond the summary when presented with one. This caused understandable alarm among journalists who focused on two stats in particular: a reduction from 15% of searches which resulted in a result being clicked to just 8% when an A.I. Overview was shown, and finding that just 1% of searches with an Overview resulted in a click on a citation in that summary.

Beatrice Nolan, of Fortune, said this was evidence A.I. was “eating search”. Thomas Claburn, of the Register, said they were “killing the web”, and Emanuel Maiberg, of 404 Media, says Google’s push to boost A.I. “will end the flow of all that traffic almost completely and destroy the business of countless blogs and news sites in the process”. In addition to the aforementioned stats, Ryan Whitwam, of Ars Technica, also noted Pew found “Google users are more likely to end their browsing session after seeing an A.I. Overview” than if they do not. It is, indeed, worrisome.

Pew’s is not the only research finding a negative impact on search traffic to publishers thanks to Google’s A.I. search efforts. Ryan Law and Xibeijia Guan of Ahrefs published, earlier this year, the results of anonymized and aggregated Google Search Console data finding a 34.5% drop in click-through rate when A.I. Overviews were present. This is lower than the 47% drop found by Pew, but still a massive amount.

Ahrefs gives two main explanations for this decline in click-through traffic. First, and most obviously, these Overviews present as though they answer a query without needing to visit any other pages. Second, they push results further down the page. On a phone, an Overview may occupy the whole height of the display, as shown in Google’s many examples. Either one of these could be affecting whether users are clicking through to more stuff.

So we have two different reports showing, rather predictably, that Google’s A.I. Overviews kneecap click rates on search listings. But these findings are complicated by the various other boxes Google might show on a results page, none of which are what Google calls an “A.I.” feature. There are a slew of Rich Result types — event information, business listings, videos, and plenty more. There are Rich Answers for when you ask a general knowledge question. There are Featured Snippets that extract and highlight information from a specific page. These “zero-click” features all look and behave similarly to A.I. Overviews. They all try to answer a user’s question immediately. They all push organic results further down the page. So what is different about results with an A.I. twist?

Part of the problem is with methodology. That deja vu you are experiencing is because I wrote about this earlier this week, but I wanted to reiterate and expand upon that. The way Pew and Ahrefs collected the data for measuring click-through rates differs considerably. Pew, via Ipsos KnowledgePanel, collected browsing data from 900 U.S. adults. Researchers then used a selection of keywords to identify search result pages with A.I. Overviews. Ahrefs, on the other hand, relied on data directly from Google Search Console automatically provided by users who connected it to the company’s search optimization software. Ahrefs compared data collected in March 2024, pre-A.I. rollout, against that from March 2025 after Google made A.I. Overviews more present in search results.

In both reports, there is no effort made to distinguish between searches with A.I. Overviews present and those with the older search features mentioned above, and that would impact average click-through rates. Since Featured Snippets rolled out, for example, they have been considered the new first position in results and, unlike A.I. Overviews in the findings of Pew and Ahref, they can drive a lot of traffic. Search optimization studies are pretty inconsistent, finding Featured Snippets on between 11%, according to Stat, and up to 80% according to Ahrefs.

But the difference is even harder to research than it seems because A.I. Overviews do not necessarily replace Featured Snippets, nor are they independent of each other. There are queries for which Overviews are displayed that had no such additional features before, there are queries where Featured Snippets are being replaced. Sometimes, the results page will show an A.I. Overview and a Featured Snippet. There does not seem to be a lot of good data to disentangle what effect each of these features has in this era. A study from Amisive from earlier this year found the combined display of Overviews and Snippets reduced click-through rates by 37%, but Amisive did not publish a full data set to permit further exploration.

But publishers do seem to be feeling the effects of A.I. on traffic from Google’s search engine. The Wall Street Journal, relying on data from Similarweb, reported a precipitous drop in search traffic to mainstream news sources like Business Insider and the Washington Post from 2022 to 2025. Similarweb said the New York Times’ share of traffic coming from search fell from 44% to 36.5% in that time. Interestingly, Similarweb’s data did not show a similar effect for the Journal itself, reporting a five-point increase in the share of traffic derived from search over the same period.

The quality of Similarweb’s data is, I think, questionable. It would be better if we had access to a large-scale first-party source. Luckily, the United States Government operates proprietary analytics software with open access. Though it is not used on all U.S. federal government websites, its data set is both general-purpose — albeit U.S.-focused — and huge: 1.55 billion sessions in the last thirty days. As of writing, 44.1% of traffic in the current calendar year is from organic Google searches, down from 46.4% in the previous calendar year. That is not the steep decline found by Similarweb, but it is a decline nevertheless — enough to drop organic Google search traffic behind direct traffic. I also imagine Google’s A.I. Overviews impact different types of websites differently; the research from Ahrefs and Amisive seems to back this up.

Google has, naturally, disputed the results of Pew’s research. In an extended comment to Search Engine Journal, the company said Pew “use[d] a flawed methodology and skewed queryset that is not representative of Search traffic”, adding “[we] have not observed significant drops in aggregate web traffic”. What Google sees as flaws in Pew’s methodology is not disclosed, nor does the company provide any numbers to support its side of the story. Sundar Pichai, Google’s CEO, has even claimed A.I. Overviews are better for referral traffic than links outside Overviews — but, again, has never provided evidence.

Intuitively, it makes sense to me that A.I. Overviews are going to have a negative impact on click-through rates, because that is kind of the whole point. The amount of information being provided to users on the results page increases while the source of that information is minimized. It also seems like the popular data sources for A.I. Overviews are of mixed quality; according to a Semrush study, Quora is the most popular citation, while Reddit is the second-most popular.

I find all of these studies frustrating and it is not necessarily the fault of the firms conducting them. Try as hard as the search optimization industry has, we still do not have terrifically reliable ways of measuring the impact each new Google feature has on organic search traffic. The party in the best possible position to demystify this — Google — tends to be extremely secretive on the grounds it does not want people gaming its systems. Also, given the vast disconnect between the limited amount Google is saying and the findings of researchers, I am not sure how much I trust its word.

It is possible we cannot know exactly how much of an effect A.I. Overviews will have on search trafic, let alone that of “answer engines” like Perplexity. The best thing any publisher can do at this point is to assume the mutual benefits are going away — and not just in search. Between Google’s legal problems and it fundamentally reshaping how people discover things in search, one has to wonder how it will evolve its advertising business. Publishers have already been prioritizing direct relationships with readers. What about advertisers, too? Even with the unknown future of A.I. technologies, it seems like it would be advantageous to stop relying so heavily on Google.

A Tedious Explanation of Paying for YouTube, Tediously

Well, they got me. I am now paying for YouTube.

For years, I have used an ad blocker only infrequently on YouTube partly because the ads used to be short and not too disruptive, but mostly because I feel bad for people who make videos for a living. There is basically no alternative to YouTube.

Text is small; I can take this website anywhere I want. I can make my writing as discoverable or as paywalled as I deem makes sense. The same is true, to varying degrees, for images and audio. If someone does not like how their podcast host is behaving, they can move their show. It is not easy but it is doable.

That is not the case for video — at least, not for independent makers in the safe-for-work realm. You might use any number of streaming apps for video from large studios, and perhaps smaller ones too, like Dropout and Nebula. But there is no second YouTube. Even though TikTok and Instagram provide sufficient competition in the mobile short-form format, there is simply nothing else for longer formats in landscape. Sites like Dailymotion are doing so poorly they are deleting videos if they have no activity for about a year. Video makers on alternative sites like Rumble still post clips or copies of their show to YouTube; despite their persistent whining about alleged censorship, their videos are not removed from YouTube, and they know it remains the best platform for discovery.

I began considering a YouTube Premium subscription a couple of years ago when the great Alec Watson mentioned that creators like him get a cut. Which, in hindsight, seems obvious: instead of ad revenue, they get a portion of subscription revenue. But this was and remains unmentioned in YouTube’s marketing. Call it parasocial, non-derogatory, but this is the most compelling argument for why I should pay for YouTube. I support several indies through Patreon, too, but this means I get to be even more supportive without making specific monthly commitments, and I get a better experience.

The experience, by the way, is what pushed me over the edge. Remember how I mentioned “ads used to be short and not too disruptive”? Over the past few years, YouTube has increased the default ad load and duration. Before I had Premium, I was seeing ads every one or two minutes in many videos where the uploader had not changed the ad settings. Being that intrusive is something only YouTube can do because, again, it has no competition.

The process for actually paying for YouTube was bizarrely difficult. Since I already have a music streaming subscription, the Premium Lite option was a good fit for me. However, Google simply would not geolocate me or my personal Google account to Canada, where the Lite option is available. There was no way to correct Google’s assumption about where I was located; it simply did not let me see the Lite registration page, even though the currency was displayed in Canadian dollars.

So I made a new account in my Google Workspace dashboard just for YouTube. It turns out this was a little complicated, too, as I now needed to enable various Google services to make this work: YouTube and Google Pay, at first, and more later.

Then I used Safari’s autocomplete to enter my credit card details, which is where things got real weird. My card’s expiration date and CSC were entered correctly. The number itself was, too, until the last digit, at which point it abruptly changed to something completely different in nearly the same format — instead of four groups of four numbers, it became three groups of four, followed by one group of three. A test card number also encountered the same issue. Today, about a week later, I cannot reproduce it, so it seems like it has been fixed — but, still, strange.

One unfortunate side effect of having a YouTube Premium membership is that I now need to sign into YouTube, which means I am also signed into all Google services. Because I am using a Workspace-type Google account, I have also needed to enabled additional services on the account, like Google Maps. I can work around this by using YouTube in a separate browser and configuring Safari to open all YouTube links in that other browser — but that is not a great experience. I have as much tracking turned off as I am able through Google’s settings, plus Safari has generally better tracking protection. And I really do use frequent site sponsor Magic Lasso Adblock, which truly helps me avoid a bunch of tracking I see in the wild; the difference is obvious in Web Inspector if I refresh a page without having Magic Lasso enabled.

I am still seeing the occasional ad on YouTube on videos where they should not be present. In general, however, this is a night-and-day experience. YouTube has successfully degraded its free experience to the point where it feels like the trial version of paid software. A single meaningful competitor would be a corrective force. Alas, only YouTube is YouTube, and that makes things worse for audiences and video makers alike.

Roundrect Dictator

I have many thoughts about the redesigned elements common across most of Apple’s platforms but they are still brewing, much as I hope the same is true for the visual interface itself. There is one thing, though, which is a downright shame: Apple’s guidance for the shape of Mac app icons:

An app icon’s shape varies based on a platform’s visual language. In iOS, iPadOS, and macOS, icons are square, and the system applies masking to produce rounded corners that precisely match the curvature of other rounded interface elements throughout the system and the bezel of the physical device itself. In tvOS, icons are rectangular, also with concentric edges. In visionOS and watchOS, icons are square and the system applies circular masking.

This is no longer optional, but mandated by the system. App icons across Apple’s three most popular operating systems share a similar rounded square mask, and it is a downgrade. Simon B. Støvring correctly calls out the “expressive, varied app icons, a case of character over conformity” as a highlight of past versions of MacOS. I miss detailed and artistic app icons plenty. Indulging in realistic textures and thoughtful rendering was not only a differentiator for the Mac; it also conveyed the sense an app was built with a high degree of care.

Perhaps that is largely a product of nostalgia. Change can be uncomfortable, but it could be for good reasons. Stripping icons of their detail might not be bad, just different. But wrapping everything in a uniform shape? That is, dare I say, an objective degradation.

Since MacOS Big Sur debuted the precursor to this format, I have found it harder to differentiate between applications which, as I understand it, is the very function and purpose of an icon. I know this has been a long-running gripe for those of us of a certain age, but it remains true, and a walk through the history of Apple’s Human Interface Guidelines indicates the company also understands it to be true.

The uniform rounded rectangular icons in MacOS Tahoe are the product of a slow but steady series of changes Apple has made to its guidance beginning with OS X Yosemite. At its introduction at WWDC 2014, Craig Federighi said those icons were “beautifully crafted”, “so clean and yet so fundamentally still Mac”. While Apple has long provided recommendations for icon shapes and the angle at which objects should sit, its Yosemite guidelines tended to converge around specific shapes. However, Apple still advised “giving your app icon a realistic, unique shape”, since a “unique outline focuses attention on the depicted object and makes it easier for users to recognize the icon at a glance”. It also said developers should not use the same icon as a companion iOS app, since “you don’t want to imply that your app isn’t tailored for the OS X environment”.

By the next major redesign in MacOS Big Sur, Apple was extolling the “harmonious user experience” of “a common set of visual attributes, including the rounded-rectangle shape, front-facing perspective, level position, and uniform drop shadow”. Still, it emphasized the delight of including a “familiar tool” and “realistic objects” in an icon, in a manner that “float[s] just above the background and extend[s] slightly past the icon boundaries”. This is one of the reasons the MarsEdit icon remains so distinctive to me — not only does the rocket ship have enough contrast with the background, its silhouette is not the same as the icons for Mimestream above it or Fantastical below it. This is not a knock against either of those two apps; they are understandably following the documentation Apple provides and follows with all the first-party app icons I also keep in my dock.

MacOS Tahoe overrides all this previous guidance in both written policy and technical implementation. Apple, as quoted above, now says icons should be square, and the system will take care of rounding the corners — just like on iOS. Since iOS apps can run on MacOS, a lack of being “tailored for the [MacOS] environment” is no longer seen by Apple as something to caution against. But it goes further. Designers should, in its words, “embrace simplicity”:

An icon with fine visual features might look busy when rendered with system-provided shadows and highlights, and details may be hard to discern at smaller sizes. […]

Designers no longer get to decide highlights and shadows, the system does. It defines the shape, too, and non-updated icons that do not conform are doomed to live out their days in a little grey jail cell.

Apple used to guide designers on how to make smaller icons by removing details and simplifying. Something you will often hear from designers is the fun and challenge of very small icons; how does one convey the same impression of fidelity when you have exactly 256 pixels to use? It is a delicate feat. Now, Apple simply says no icon — no matter how large — is deserving of detail. This, to me, betrays a lack of trust in the third-party designers it apparently celebrates.

Moreover, it fundamentally contradicts longstanding icon design principles. Reducing each application’s visual identity to a simple glyph — albeit with the potential for a few layers — on a coloured background necessarily leads to this perverse revision of Figure 5–15 from the 2004 Human Interface Guidelines:

A comparison of four icons in the first row each set in rounded squares of blue, orange, red, and green, each with a different white glyph. In the second row are four black rounded squares.

Though this description and figure is specifically regarding toolbar icons, Apple’s rationale for using different shapes remains clear-eyed and simply expressed:

Each toolbar icon should be easily and quickly distinguishable from the other items in the toolbar. Toolbar icons emphasize their outline form, rather than subtler visual details.

Perhaps this reasoning is incorrect. If so, the current guidelines make no effort to explain how or why users are not guided by outline in addition to colour and enclosed shape. Apple simply says icons should be constructed “in a simple, unique way with a minimal number of shapes” on “a simple background, such as a solid colour or gradient”. Not only are there no longer any “subtler visual details”, there is also no distinct outline for each icon. I believe limitations spur creativity, but imposed uniformity sure makes that difficult. This is, however, apparently required because of new icon formats available to users, including a clear version that makes it look as though the glyph and base are an ice sculpture: cool, but entirely indistinguishable from others surrounding it. Again, this wrests control away from designers to give a little bit to users, but only at the behest of and within the boundaries of Apple’s mandates.

The technical and feature improvements in MacOS Tahoe are intriguing. I sure hope the Spotlight improvements are as excellent as they seem to be since I expect I will be increasingly dependent upon it as an application launcher. I am also excited to try Liquid Glass on a Mac. Though I remain skeptical, it is at least interesting. That is something I find difficult to see in the new direction of MacOS icons.

Cycling Directions Have Expanded Across Canada in Apple Maps

Apple has made no announcement that can find about a significant expansion in the availability of cycling directions across Canada, but I thought it was worth noting here because it impacts me personally. I need no other excuse.

As of yesterday, Apple’s iOS feature page indicated Canadian cycling directions were only available in Montreal, Toronto, and Vancouver. The list has grown substantially today, adding:

  • Austria

  • Belgium

  • Denmark

  • Finland

  • Greece

  • Ireland

  • Italy

  • Monaco, because I guess even tax-dodging billionaires sometimes hop on their bikes, too

  • Netherlands

  • New Zealand

  • Norway

  • Portugal

  • San Marino

  • Singapore

  • Sweden

  • Switzerland

  • Thailand

  • Vatican City

In addition, three places were upgraded from availability in specific cities to, apparently, whole-country directions:

  • Canada

  • Spain

  • United Kingdom

Some of this expansion may truly be new, but it seems to me this page is merely catching up. For example, it only now includes the Netherlands, where cycling directions have been available for a year. The expansion to Calgary was noticed on 4 April by Reddit user drinkyourwaterbitch. I cannot recall receiving an in-app notification of this change which arrives just in time for cycling season here.

I cannot speak to anywhere else but, in my testing, Canadian availability is broad. Coverage includes not only larger cities like Calgary, Edmonton, Halifax, Ottawa, Victoria, and Winnipeg, but also smaller towns, and even Northern Canada. It also includes rural routes. I was able to get cycling directions within Iqaluit, and between Inuvik and Squamish. Eight-and-a-half days straight, if you are wondering, with a total climb of 70,200 metres.

More practically, the cycling directions within Calgary seem, overall, pretty good. Without changing any settings, Maps sometimes chooses different routes than I would take. On a ride I am familiar with, Maps auto-selected a 51-minute, 13-kilometre path instead of one it says takes 42 minutes over 11 kilometres, the main difference being a 100 metre climb compared to 150 metres. Yet, with a different destination, Maps selected a ride that takes three minutes longer and requires a greater amount of climbing, but is shorter. Both appear to have a similar mix of roads and bike lanes, so I am not sure what to make of this.

I also tried putting in a route to a pharmacy with a particularly excellent selection of coffee beans and other dry goods. Instead of putting me on the protected bike lane on Edmonton Trail, visible from the Look Around imagery, it suggests a route on Fourth Street — which is a one-way road in the opposite direction. The step-by-step directions suggest there is a cycle lane along Fourth Street but I can assure you there is not — I checked. Google Maps gets it right.

Canadian cyclists like myself can rejoice at having much greater coverage that takes into account our unique needs. At last, we can make an informed decision about how we can get to a store that, upon arrival, we find is closed because the listed hours are wrong. It is still Apple Maps, after all.

I am truly happy to have cycling directions here.

Apple ‘Fandom’ in 2025

Dan Moren ended his “Stay Foolish” column at Macworld with a tremendous essay about what it means to be a “fan” of Apple or its products in 2025:

Over the years, those in the Apple community have long been called everything from the liturgical “Apple faithful” to the insipid “iSheep”, dating back to the days when the prevailing wisdom was that to hitch your fortunes to this weird company must imply a cult-like devotion. The simple truth was that most customers were simply fans of the products themselves: they liked the way they worked and looked.

That hasn’t changed for me: I continue to be a fan of Apple’s products. But as Apple started becoming more and more successful, I’ve become increasingly skeptical that one should ever really consider oneself a “fan” of a company.

On the eve of WWDC and, with it, the kicking-off of Apple’s coming year, I found myself thinking about this column published in April.

There was a time when rooting for Apple and calling oneself a “fan” seemed to make sense. The things it designed and sold had a clear ethos that gave me an impression of the kind of effortless confidence that only comes from a massive amount of effort. The business model felt like a simple exchange — as Steve Jobs said at D8, “we want to make the best products in the world for our customers. If we succeed they’ll buy them, and if we don’t they won’t”.

That era — the Jobs era, the simplistic worldview era, and the clear ethos era — is behind us. I am not saying Apple now takes everything for granted; I am sure it has teams of people working hard all day long to make improvements. But it is a corporate behemoth that cannot move quickly. Regardless of how cool its rumoured “Liquid Glass” visual refresh may be, I have a difficult time believing it will radically alter the way we use our devices. There are 2.35 billion devices on users’ wrists, in their hands and bags, and on their desks. At least a billion of them are iPhones. So, even though it is a bit exciting to be on the verge of something new and different, I do not think it will be that new and different, lest Apple alienate a huge number of people. It will look different enough, and that looks like progress — and maybe it will actually represent progress, too.

Visual interface changes aside, the expectations for this year’s WWDC do not seem to be high. We are still waiting on last year’s most impressive Apple Intelligence features, and the Vision Pro is a nascent device in the hands of few. The ideas factory is sputtering a little. But the money factory remains strong.

I am enmeshed in the Apple ecosystem so, in some ways, it should be exciting the company has to try a little harder. I am not. I do not think anyone expects Apple will sell dramatically fewer iPhones this year, nor will it lose subscribers to services, its increasingly important recurring revenue printer. Apple was a more interesting company when it could not be certain its customers would buy more stuff. I hope, after the Vision Pro’s release, it is also understanding it cannot take its developer base for granted, either.

Every time I use the Windows 11 computer on my desk at work, I am reminded of why I use MacOS. I still prefer it. But the post-P.C. device era has encouraged some nasty habits at Apple that have, consequently, made it one of the world’s most valuable businesses.

Apple has all the money it could ever want. It sells some very good products. But its size has smothered the fire it seemed to have, and dulled its edge. There are still risky bets it could make, but all of them are necessarily softened by its critical position in the world’s economy and in retirement plans. I see no reason to be a fan of that kind of company, even if you — as I — still appreciate many of the products and services it delivers. I am, as ever, looking forward to seeing what is being announced tomorrow, albeit with the understanding I will be watching a slick infomercial possibly containing concept videos. It is hard to see how one could be a fan of a multi-trillion-dollar company. I am just a customer, like a billion-plus others.

‘Nimble Fingers’ Racism and iPhone Manufacturing

Tripp Mickle, of the New York Times, wrote another one of those articles exploring the feasibility of iPhone manufacturing in the United States. There is basically nothing new here; the only reason it seems to have been published is because the U.S. president farted out yet another tariff idea, this time one targeted specifically at the iPhone at a rate of 25%.1

Anyway, there is one thing in this article — bizarrely arranged in a question-and-answer format — that is notable:

What does China offer that the United States doesn’t?

Small hands, a massive, seasonal work force and millions of engineers.

Young Chinese women have small fingers, and that has made them a valuable contributor to iPhone production because they are more nimble at installing screws and other miniature parts in the small device, supply chain experts said. In a recent analysis the company did to explore the feasibility of moving production to the United States, the company determined that it couldn’t find people with those skills in the United States, said two people familiar with the analysis who spoke on the condition of anonymity.

I will get to the racial component of this in a moment, but this answer has no internal logic. There are two sentences in that larger paragraph. The second posits that people in the U.S. do not have the “skills” needed to carefully assemble iPhones, but the skills as defined in the first sentence are small fingers — which is not a skill. I need someone from the Times to please explain to me how someone can be trained to shrink their fingers.

Anyway, this is racist trash. In response to a question from Julia Carrie Wong of the Guardian, Times communications director Charlie Stadtlander disputed the story was furthering “racial or genetic generalizations”, and linked to a podcast segment clipped by Mickle. In it, Patrick McGee, author of “Apple in China”, says:

The tasks that are often being done to make iPhones require little fingers. So the fact that it’s young Chinese women with little fingers — that actually matters. Like, Apple engineers will talk about this.

The podcast in question is, unsurprisingly, Bari Weiss’; McGee did not mention any of this when he appeared on, for example, the Daily Show.

Maybe some Apple engineers actually believe this, and maybe some supply chain experts do, too. But it is a longstanding sexist stereotype. (Thanks to Kat for the Feminist Review link.) It is ridiculous to see this published in a paper of record as though it is just one fact among many, instead of something which ought to be debunked.

The Times has previously reported why iPhones cannot really be made in the U.S. in any significant quantity. It has nothing to do with finger size, and everything to do with a supply chain the company has helped build for decades, as McGee talks about extensively in that Daily Show interview and, presumably, writes about in his book. (I do not yet have a copy.) Wages play a role, but it is the sheer concentration of manufacturing capability that explains why iPhones are made in China, and why it has been so difficult for Apple to extricate itself from the country.

  1. About which the funniest comment comes from Anuj Ahooja on Threads. ↥︎

Meta’s A.I. Television

If you were listening out of context to something Mark Zuckerberg said in a recent interview with Dwarkesh Patel, you might think he is deeply concerned about meaningful personal friendships:

There’s this stat that I always think is crazy: the average American, I think, has I think it’s fewer than three friends. Three people that they’d consider friends. And the average person has demand for meaningfully more — I think it’s like fifteen friends, or something. […] The average person wants more connectivity — uh, connection — than they have.

For what it is worth, I tried to find the source for these numbers. The “three friends” figure correlates with the findings and phrasing of a 2021 American Enterprise Institute survey (PDF), though other surveys have found broadly similar numbers. In 2023, Pew Research found 39% of Americans say they have one to three close friends, while 38% say they have five or more. Recent YouGov polling finds over 52% saying they have one to three, while 22% say they have four or five.

The second appears to come from the work of Robin Dunbar. The accuracy of this number is disputed.

Still, it sounds like Zuckerberg simply cares about the number of friends people say they have compared to the number they want. And, so, you would think the CEO of the world’s biggest social networks would be concerned about making sure we maintain the real-life connections we already have, and perhaps finding new ones. Alas, the technological solutions along those lines sound pretty boring unless they are marketed based on their quaint vintage appeal.

That is not what Zuckerberg is being interviewed to promote. This line of questioning is bookended by questions about artificial general intelligence and DeepSeek. And, in fairness, I did not quote Patel’s question which prompted this response:

On this point of A.I.-generated content or A.I. interactions, already people have meaningful relationships with A.I. therapists, A.I. friends, you know, maybe more. And this is just gonna get more intense as these A.I.s get more unique and more personable — more intelligent, more spontaneous, and funny, and so forth. […] People are going to have relationships with A.I.s. How do we make sure these are healthy relationships?

Zuckerberg barely answers this. Instead, he pivots to more comfortable territory about how Meta’s vision of A.I. will increase the number of entirely generated “friends” people can have. Or, in the words of Paul Fairie:

The average American has 3 eggs, but has demand for 15. So here are 12 photographs of eggs. I am a business man.

Zuckerberg acknowledges “I think there are all these things that are better about physical connections when you can have them,” but his primary complaints with A.I. relationships are how technologically primitive they are.

My goal is not to dump on anyone except Henry Blodget who may have found some kind of personal fulfilment in some A.I. program. That is not my place and I have no idea where to begin. What is notable to me is the role Meta plays in manipulating the experience of real-world friendships.

Kyle Chayka, the New Yorker:

[…] The people we follow and the messages they post increasingly feel like needles in a digital haystack. Social media has become less social.

Facebook’s founder, Mark Zuckerberg, admitted as much during more than ten hours of testimony, over three days last week, in the opening phase of the Federal Trade Commission’s antitrust trial against Facebook’s parent company, Meta. The company, Zuckerberg said, has lately been involved in “the general idea of entertainment and learning about the world and discovering what’s going on.” This under-recognized shift away from interpersonal communication has been measured by the company itself. During the defense’s opening statement, Meta displayed a chart showing that the “percent of time spent viewing content posted by ‘friends’” has declined in the past two years, from twenty-two per cent to seventeen per cent on Facebook, and from eleven per cent to seven per cent on Instagram.

What “friends” mean in this context is different from how it is used by Zuckerberg and in the surveys above. Also, the rest of this material is not necessarily A.I.-generated. Even so, 7–17% of users’ time is spent viewing stuff they say they want to see, and that is not necessarily because they have elected to view it less. That is driven to a considerable degree by the posts Meta has selected for you to see first, and the order in which your friends’ Stories are displayed.

If Meta had an institutional responsibility to help users maintain their real-world friendships, it is failing to do so based on these numbers. But that is not the role it seems to want to play.

John Herrman, of New York magazine, nails it:

Meta’s AI strategy less resembles a bet on an unrecognizable future than a belief, or a wish, that it can simply be Meta, but more so. (It’s also a bet that large-language-model-based AI will present more opportunities for entertainment than for work.) Zuckerberg isn’t just envisioning a Meta staffed by AI engineers and AI moderators, but platforms that stock themselves with content, allow users to request whatever types of interactions they want, and are even more effective at holding attention, keeping people engaged, and, of course, serving and targeting advertising.

Perhaps what people ultimately want — in general and on average — is entertainment brought to them. That is not a denigration of society or anything; it makes sense. We once turned on the radio and enjoy audio-only plays and discussions. Then we had podcasts. We once turned on the television and scrolled through channels until we settled on something we liked. Then we had Netflix and YouTube. Both provide suggestions on what to watch, and some podcast apps have their own recommendations, but there is still a manual quality to discovery.

Then TikTok came around and did away with two expectations: that you should have to work to figure out what you want to be entertained by, and that your best source of entertainment is your friend group. Meta is taking it a step further: what if the best source of entertainment is generated entirely for them? I find that thought revolting. The magic of art and entertainment is in the humanity of it. Thousands of years of culture is built on storytelling and it is not as though this model has been financially unsuccessful. That is not the lens through which I view art, but it is obviously relevant to Meta’s goals.

This is not enough. Meta, institutionally, sees its world through quantities — of friends, of posts made, of ads served, of engagement, of time spent, of interactions — and envisions abundance delivered through A.I. means. Its efforts so far have been sloppy. Maybe they will, as Patel appears to believe, get better: “more unique and more personable” and so forth. Regardless, they will still be fake. I am not the biggest A.I. downer, but this worldview sucks. Human-created art is as irreplaceable by A.I. as is a human friendship. Not every problem is one which can be solved through technological development, and not every problem is real — who is to say that three close friends is too few for most people, or that the amount of entertainment produced by human beings is insufficient?

It would seem an empire can be built only so far on what is real.

MacDailyNews’ Sexist Response to Yesterday’s Epic Games Ruling

Following yesterday’s ruling finding Apple has disregarded a U.S. court’s instructions to permit links to external purchases from within iOS apps under reasonable terms, the publisher of MacDailyNews responded with the site’s take. In case you are not already familiar, MacDailyNews has a consistently right-libertarian editorial slant. It is not one I agree with, but that has only the tiniest bit of relevance to this commentary.

Also, while the site was founded by Steve Jack, it attaches no byline to its articles and so I am uncertain who specifically wrote this tripe:

It’s too bad Gonzalez Rogers expected Apple to provide a service that she ordered for free, because it makes no sense for Apple to do such a thing. Gonzales ordered Apple to allow developers to advertise lower prices elsewhere within Apple’s App Store. It is Apple’s App Store. Despite what Epic Games wishes and misrepresents, the App Store is not a public utility. Apple built it. Apple maintains it. Apple owns it, not Epic Games or some ditzy U.S. District Judge. Advertising within Apple’s App Store has value, a fee for which its owner has every right to charge, regardless of whatever the blank-eyed Gonzalez Rogers, bless her heart, expected.

I am sure there are plenty of people out there who believe Apple is entitled to run the iOS App Store as it sees fit. It is an argument with which I have sympathies outweighed by disagreements, but I get it.

What I do not get is describing a U.S. district court judge as “ditzy”.

It is an adjective invoked by MacDailyNews to describe just two people: Gonzalez Rogers and former European Commissioner for Competition Margrethe Vestager. It is an inherently sexist term — a cheap shot thrown at women who happen to have legally restricted the world’s most valuable corporation. Agree or disagree with their work, this kind of response is pathetic.

If, however, one is desperate to be a misogynist, they had better be certain the rest of their argument is airtight. And MacDailyNews falls on its face.

Gonzalez Rogers has not demanded an entirely free ride. In fact, she gave Apple substantial opportunity to explain how it arrived at (PDF) a hefty 27% commission rate for external purchases. Apple did not do so. It took hearings this year to learn it went so far as to get the Analysis Group to produce a report which happened to find (PDF) Apple was responsible for “up to 30% of a developer’s revenue”. But, Gonzalez Rogers writes, this study was not the basis for Apple’s justification for a 27% cut for external purchases, nor could it have been, because it was produced after records show Apple had already decided on that rate. It was reverse-engineered to maintain Apple’s entirely unjustified high commission rate.

To quote Gonzalez Rogers:

This is an injunction, not a negotiation. There are no do-overs once a party willfully disregards a court order. […]

And again:

Apple was afforded ample opportunity to respond to the Injunction. It chose to defy this Court’s order and manufacture post hoc justifications for maintaining an anticompetitive revenue stream. Apple’s actions to misconstrue the Injunction continue to impede competition. This Court will not play “whack-a-mole,” nor will it tolerate further delay.

Apple could have taken this up in a legally justifiable way that, plausibly, could have given it some reasonable commission on some sales. It did not do that, so now the court says no commission whatsoever is permissible. Simple. Besides, developers pay for hardware, a developer membership, and plenty of Apple’s services. They are not getting a free ride just by linking to an external payment option.

Moreover, developers do not “advertise” in the App Store. They can, but that is not what is being adjudicated in this case.

Media commentators can disagree on this ruling, on the provisions of the Digital Markets Act, and on Apple’s treatment of developers. There are many legitimate views and angles, and I think it is great to see so much discussion about this leading up to WWDC. But we can all do this without resorting to lazy sexism. Do better.

U.S. Judge Rules Apple Is Not in Compliance With Injunction in Epic Games Case

In September 2021, U.S. judge Yvonne Gonzalez Rogers issued a judgement in Epic Games’ case against Apple. She mostly sided with Apple but, critically, ruled third-party developers must be permitted to link to external purchasing mechanisms from within their apps.

Even that barest of changes, however, has apparently been too onerous for Apple to comply with in the spirit the court intended. Instead of collecting a typical 30% commission on in-app purchases, Apple said it would take 27% of external purchases made within seven days of someone using an in-app link. This sucks. The various rules Apple implemented, including the different commission rate, have been a problem ever since. In a ruling today, Gonzalez Rogers finds Apple’s measures do not comply with the court’s expectations.

Kif Leswing, CNBC:

Apple willfully violated a 2021 injunction that came out of the Epic Games case, Judge Yvonne Gonzalez Rogers said in a court filing on Wednesday.

[…]

Rogers added that she referred the matter to U.S. attorneys to investigate whether to pursue criminal contempt proceedings on both [Apple executive Alex] Roman and Apple.

The judge’s order (PDF) is full of withering remarks and findings, like this footnote on the sixth page (citation removed):

Apple’s “entitlement” perspective and mantra persisted beyond the Injunction. For example, Apple’s Communications Director, Marni Goldberg, texted her colleague during the first evidentiary hearings, that “It’s Our F***ING STORE.” Not surprisingly (nor convincingly), she did not “recall” sending those messages.

There are several points like these where the judge makes clear she does not appreciate Apple’s obstinate approach. But the business-related findings are notable, too. For example, this passage on pages 17–18 (citations removed for clarity):

Further, in May 2023, Apple through Oliver and others received feedback from Bumble, a large, well-known developer on Apple’s and Google’s alternative billing programs. Bumble specifically advised Apple that “[p]ayment processing fees average out significantly higher than the 4% fee reduction currently offered by Google in the [user choice billing] program or [the] 3% fee in Apple’s … solution resulting in negative margin for developers.” In other words, Bumble explained to Apple that a “3% discount” was not economically viable for a developer because the external cost of payments exceeds 3%. Apple’s own internal assessment from February 2023 reflects data meriting the same conclusion — that the external costs of payments for developers on link-out purchases would exceed Apple’s 3% discount if it demanded a 27% rate.

The evidence uncovered in the 2025 hearing demonstrated Apple’s knowledge and expectation that the restrictions would effectively dissuade any real developer participation, to Apple’s economic advantage.

To all those who have said Apple’s regulatory and legal responses have amounted to malicious compliance, you appear to be correct. Stripping more formal language, as the judge has done here, reveals how fed up she is with Apple’s petulant misconduct.

Throughout this filing, Phil Schiller comes across very well, unlike fellow executives Luca Maestri, the aforementioned Alex Roman, and Tim Cook. In internal discussions, he consistently sounds like the most reasonable voice in the room — though Gonzalez Rogers still has stern words for him throughout. (For example, Schiller claimed external purchasing links alongside in-app options would make users more susceptible to fraud, even though under Apple’s rules it must review and approve those links. The judge writes “[n]o real-time business documents credit that view”.)

Gonzalez Rogers also has critical words about Apple’s current visual interface design patterns. In a section on page 32 featuring screenshots of possible button styles permissible for developers to provide external links, she writes of a “plain link or button style” not dissimilar to many post-iOS 7-style “buttons”:

Nothing about either example appears to be a “button,” by the ordinary usage and understanding of the word. There is, certainly, an external-link icon next to the call to action and hyperlink, but Apple strains to call either of these strings of text a “button.”

Yet, of a subsequent screenshot featuring one button of this style and another with a rounded rectangle background:

The lower example is readily identifiable as a button.

A final set of passages I would like to point to in this filing is the suspicion of Apple’s intellectual property justification for charging such onerous fees in the first place. Quite a bit of this is repeated from other judgements and filings in this case, but it is quite something to read them all together. For example, in a footnote on page 60 (citations removed for clarity):

[…] Apple also argues that the question of whether Apple’s commission appropriately reflects the value of its intellectual property is not an issue for injunction compliance, and that it is legitimate for a business to promote the value of its corporation for stockholders. Apple misses the point. The issue is that Apple flouted the Court’s order by designing a top-down anticompetitive system, in which its commission played a fundamental role.

For the same reasons, the Court disagrees that requiring Apple to set a commission of zero constitutes and unconstitutional taking. For instance, as described infra Section IV, in the trademark context, “a party who has once infringed is allowed less leniency for purposes of injunction enforcement than an innocent party.” Apple does not have an absolute right to the intellectual property that it wields as a shield to competition without adequate justification of its value. Apple was provided with an opportunity to value that intellectual property and chose not to do so.

On page 21, the judge cites an internal email on the topic:

[T]he team has discussed variations on the commission options with lower rates, but we struggled to land on ironclad pricing rationales that would (1) stand up to scrutinizing comparisons with defenses of the commission and existing discounting approaches in other jurisdictions and (2) that we could substantiate solidly on a bottoms up basis without implicitly devaluing our IP / proprietary technology.

The justification for Apple’s commission is entirely fictional. The company is not expected to, in its words, “give away [its] technology for free”, but it is clearly charging commissions like these simply because it can. It owns the platform and it believes it is entitled to run it in any way it chooses. At Apple’s scale, however, that argument does not fly.

Legal bodies around the world are requiring similar changes, and Apple’s reluctance to rip off the bandage and adopt a single global policy seems increasingly stupid. The longer it drags this stuff out, the worse it looks.

I am sure there are smart people at Apple who believe they are morally and legally correct to keep fighting. But Gonzalez Rogers accused an executive of lying under oath, seems to find the rest of the company’s executive team legally contemptible, and finds the behaviour of the world’s most valuable company to be pretty outrageous. All of this because, according to the company’s internal records on page 42, it might “lose over a billion [dollars] in revenue” if 25% of users chose to use external purchase links and the company collected no commission on them.

The Carelessness of Perplexity

Alex Heath, of the Verge, spoke with Aravind Srinivas, CEO of Perplexity, earlier this week, and they had quite the conversation.

Many publishers have been upset with you for scraping their content. You’ve started cutting some of them checks. Do you feel like you’re in a good place with publishers now, or do you feel there’s still more work to be done?

I’m sure there’s more work to be done, but it’s in a way better place than it was last time we spoke. We are scraping but respecting robots.txt. We only use third-party data providers for anything that doesn’t allow us to scrape.

Heath has no followup, no request for clarification — nothing — so I am not sure if I am reading this right, but I think I am. Srinivas here says that Perplexity’s scraper itself respects website owners’ permissions but, if it is disallowed, the company gets the same data through third-parties. If a website owner does not want their data used by Perplexity, they must disallow its own scraper plus every single scraper that might sell to Perplexity. That barely resembles “respecting robots.txt”.

Again, I could have this wrong, but Heath does not bother to clarify this response.

Perplexity is currently working on its own web browser, Comet, and has signalled interest in buying Chrome should Google be forced to divest it. Srinivas calls it a “containerized operating system” and explains the company’s thinking in response to a question about ChatGPT’s Memory feature:

Our strategy is to allow people to stay logged in where they are. We’re going to build a browser, and that’s how we’ll access apps on behalf of the user on the client side.

I think memory will be won by the company that has the most context. ChatGPT knows nothing about what you buy on Instagram or Amazon. It also knows nothing about how much time you spend on different websites. You need to have all this data to deeply personalize for the user. It’s not about who rolls out memory based on the retrieval of past queries. That’s very simple to replicate.

If you are a money person, there is a logical next step to this, which Srinivas revealed on a small podcast with a couple of finance bros as they ask a question that just so happens to promote one of their sponsors: “how are you thinking about advertising in the context of search? […] Is there a future where, if you search for ‘what’s the best corporate card?’, Ramp is going to show up at the top if they bid on that?”, to which Srinivas responds “hopefully not” before going on to explain how Perplexity could eventually become ad-supported.

Julie Bort, TechCrunch:

“On the other hand, what are the things you’re buying; which hotels are you going [to]; which restaurants are you going to; what are you spending time browsing, tells us so much more about you,” he explained.

Srinivas believes that Perplexity’s browser users will be fine with such tracking because the ads should be more relevant to them.

“We plan to use all the context to build a better user profile and, maybe you know, through our discover feed we could show some ads there,” he said.

These are comments on a podcast and perhaps none of this will come to pass, but anyone can see how this is financially alluring. The “business friendly” but privacy hostile environment of the U.S. means companies like Perplexity can do this stuff with impunity. Its pitch sounds revolting now — exactly how Google’s behaviourally targeted ads sounded twenty years ago.

Perplexity is another careless business. It does not care if a website has specifically prohibited it from scraping; Perplexity will simply rely on a third-party scraper. Perplexity does not care about your privacy. I see no reason to treat this as a problem specific to individual companies, and these technologies do not respect geographic boundaries, either. We need better protections as users, which means more policy-based protections by governments taking privacy seriously.

But this industry is moving too fast. It is a “race”, after all, and any attempts to regulate it are either knocked down or compromised. There is a real need for lawmakers and regulators who care about privacy as a fundamental human right. These companies do not care and will not regulate themselves.

Meta’s Poor Prebuttal to “Careless People”

I would have loved to have been a fly on the wall when Mark Zuckerberg and the rest of the Meta’s leadership team found out about Sarah Wynn-Williams’ book “Careless People”. This conversation could have taken place anywhere, but I imagine it was in a glass-walled meeting room which would allow one of these millionaire’s shouted profanities to echo. That feels right. Wynn-Williams, a former executive at Facebook, is well-placed to tell stories of the company’s indifference to user privacy, its growth-at-all-costs mentality, its willingness to comply with the surveillance and censorship requirements of operating in China, and alleged sexual harassment by Joel Kaplan. And, of course, its inaction in Myanmar that played a “determining role” in a genocide that killed thousands in one month in 2017 alone.

Based on some of the anecdotes in this book, I am guessing Zuckerberg, Kaplan, and others learned about this from a public relations staffer. That is how they seem to learn about a lot of pretty important things. The first public indication this book was about to be released came in the form of a preview in the Washington Post. Apparently, Meta had only found out about it days before.

It must have been a surprise as Meta’s preemptive response came in the form of a barely formatted PDF sent to Semafor, and it seems pretty clear the company did not have an advance copy of the book because all of its rebuttals are made in broad strokes against the general outline reported by the Post. Now that I have read the book, I thought it would be fun and educational to compare Meta’s arguments against the actual claims Wynn-Williams makes. I was only half right — reading about the company’s role in the genocide in Myanmar remains a chilling exercise.

A caveat: Wynn-Williams’ book is the work of a single source — it is her testimony. Though there are references to external documents, there is not a single citation anywhere in the thing. In an article critical of the book, Katie Harbath, one of Wynn-Williams’ former colleagues, observes how infrequently credit is given to others. And it seems like it, as with most non-fiction books, was not fact-checked. That is not to disparage the book or its author, but only to note that this is one person’s recollections centred around her own actions and perspective.

One other caveat: I have my own biases against Meta. I think Mark Zuckerberg is someone who had one good idea and has since pretended to be a visionary while stumbling between acquisitions and bad ideas. Meta’s services are the product of bad incentives, an invasive business model, and a caustic relationship with users. I am predisposed to embracing a book validating those feelings. I will try to be fair.

Anyway, the first thing you will notice is that most of the points in Meta’s response do not dispute the stories Wynn-Williams tells; instead, the company wants everyone to think it is all “old news” and it resents all this stuff being dredged up again. Yet even though this is apparently a four-hundred-page rehash, Meta is desperate to silence Wynn-Williams in a masterful gambit. But of course Wynn-Williams is going to write about things we already know a little bit about; even so, there is much to learn.

Most of Meta’s document is dedicated to claims about the company’s history with China, beginning with the non-news that it wanted to expand into the country:

SWW’s “New” Claim:

Facebook Had A Desire To Operate In China.

Old News:

Zuckerberg Addressed This In 2019 Televised Speech. Mark himself said in a televised address in 2019, “[He] wanted our services in China … and worked hard to make this happen. But we could never come to agreement on what it would take for us to operate there.’ That is why we don’t operate our services in China today.”

No, it is not just you: the link in this section is, indeed, broken, and has been since this document was published, even though the page title suggests it was available six months prior. Meta’s communications staff must have known this because they include a link to the transcript, too. No, I cannot imagine why Meta thought it made sense to send people to an inactive video.

At any rate, Zuckerberg’s speech papers over the lengths to which the company and he — personally — went to ingratiate himself with leaders in China. Wynn-Williams dedicates many pages of her book to examples, but only one I want to focus on for now.

But let me begin with the phrase “we could never come to an agreement on what it would take for us to operate there”. In the context of this speech’s theme, the importance of free expression, this sounds like Meta had a principled disagreement with the censorship required of a company operating in China. This was not true. Which brings me to another claim Meta attempts to reframe:

SWW’s “New” Claim:

Facebook Developed Censorship Tools For Use By Chinese Officials.

Old News:

2016 New York Times Report On Potential Facebook Software Being Used By Facebook In Regard To China; Noted It “So Far Gone Unused, And There Is No Indication That Facebook Has Offered It To The Authorities In China.” […]

This is not a denial.

Wynn-Williams says she spent a great deal of time reading up on Facebook’s strategy in China since being told to take it over on a temporary basis in early 2017. Not only was the company okay with censoring users’ posts on behalf of the Chinese government, it viewed the capability as leverage and built software to help. She notices in one document “the ‘key’ offer is that Facebook will help China ‘promote safe and secure social order’”:

I find detailed content moderation and censorship tools. There would be an emergency switch to block any specific region in China (like Xinjiang, where the Uighurs are) from interacting with Chinese and non-Chinese users. Also an “Extreme Emergency Content Switch” to remove viral content originating inside or outside China “during times of potential unrest, including significant anniversaries” (like the June 4 anniversary of the Tiananmen Square pro-democracy protests and subsequent repression).

Their censorship tools would automatically examine any content with more than ten thousand views by Chinese users. Once this “virality counter” got built, the documents say that Facebook deployed it in Hong Kong and Taiwan, where it’s been running on every post.

Far from a principled “agreement on what it would take for us to operate [in China]”, Facebook was completely fine with the requirements of the country’s censorial regime until it became more of a liability. Then, it realized it was a better deal to pay lobbyists to encourage the U.S. government to ban TikTok.

SWW’s “New” Claim:

Facebook Tested Stealth App In China.

Old News:

2017 New York Times Headline: “In China, Facebook Tests The Waters With A Stealth App” “We have long said that we are interested in China, and are spending time understanding and learning more about the country in different ways,” Facebook said in a statement.”

Wynn-Williams provides plenty more detail than is contained in the Times report. I wish I could quote many pages of the book without running afoul of copyright law or feeling like a horrible person, so here is a brief summary: Facebook created an American shell company, which spun up another shell company in China. Meta moved one of its employees to an unnamed “Chinese human resources company” and makes her the owner of its Chinese shell company. A subsidiary of that company then launched two lightly reskinned Facebook apps in China, which probably violate Chinese data localization laws. And I need to quote the next part:

“Are Mark and Sheryl okay with it?” I ask.

He [Kaplan] admits that they weren’t aware of it.

I am unsure I believe Zuckerberg did not know about this arrangement.

As far as I can find, most of these details are new. The name of the Chinese shell company’s subsidiary was published by the Times, but the only reference I can find — predating this book — to the other shell companies is in an article on Sohu. I cannot find any English-language coverage of this situation.

Nor, it should be said, can I find any discussion of the legality of Facebook’s Chinese operations, the strange leadership in the documentation for the shell companies, the other apps Facebook apparently released in China, and the fallout after the Times article was published. Meta’s anticipatory response to Wynn-Williams’ book pretends none of this is newsworthy. I found it captivating.

SWW’s “New” Claim:

Chinese Dissident Guo Wengui Was Removed Due To Pressure From The Chinese Government.

Old News:

The Reasons Facebook Removed Guo Wengui From The Platform Were Publicly Reported In 2017;

Unpublished His Page And Suspended His Profile Because Of Repeated Violations Of Company’s Community Standards.

Wynn-Williams says this is false. She quotes the same testimony Facebook’s general counsel gave before a Senate Intelligence Committee hearing, but only after laying out the explicit discussions between Facebook and the Cyberspace Administration of China saying the page needed to be removed. At a time when Facebook was eager to expand into China, the company’s compliance was expected.

Then we get to Myanmar:

SWW’s “New” Claim:

Facebook Dragged Its Feet On Myanmar Services.

Old News:

Facebook Publicly Acknowledged Myanmar Response In 2018. The facts here have been public record since 2018, and we have said publicly we know we were too slow to act on abuse on our services in Myanmar […]

“Too slow to act” is one way to put it — phrasing that, while not absolving Meta, obscures a more offensive reality.

Myanmar, Wynn-Williams writes, was a particularly good market for Facebook’s Free Basics program, a partnership with local providers that gives people free access to services like Facebook and WhatsApp, plus a selection of other apps and websites. It is an obvious violation of net neutrality principles, the kind Zuckerberg framed in terms of civil rights in the United States, but seemed to find more malleable in India. Wynn-Williams’ description of the company’s campaign to save it in India, one that was ultimately unsuccessful, is worth reading on its own. Facebook launched Free Basics in Myanmar in 2016; two years later, the company pulled the plug.

From 2014 to 2017, Kevin Roose reported for the New York Times, Facebook’s user base in Myanmar — a country of around fifty million people — grew from two million to thirty million, surely accelerated by Free Basics. During that time period, Wynn-Williams writes, Facebook observed a dramatic escalation in hate speech directed toward the Rohingya group. As this began, Meta had a single contractor based in Dublin who was reviewing user reports. One person.

Also, according to Wynn-Williams, Facebook is not available in Burmese, local users “appear to be using unofficial Facebook apps that don’t offer a reporting function”, and there incompatibility between Unicode and Zawgyi. As a result, fewer reports are received, they are not necessarily in a readable format, and they are processed by one person several time zones away.

Leading up to the November 2015 election, Wynn-Williams says they doubled the number of moderators speaking Burmese — two total — plus another two for election week. Wynn-Williams says she worked for more than a year to get management’s attention in a candidate for Myanmar-specific policies, only for Kaplan to reject the idea in early 2017.

From the end of August to the end of September that year, 6,700 people are killed. Hundreds of thousands more are forced to leave the country. All of this was accelerated by Facebook’s inaction and ineptitude. “Too slow to act” hardly covers how negligent Facebook was at the scale of this atrocity.

SWW’s New Claim:

Facebook Offered Advertisers The Ability To Target Vulnerable 13-17 Year Olds.

Old News:

Claim Was Based On A 2017 Article By The Australian, Which Facebook Refuted. “On May 1, 2017, The Australian posted a story regarding research done by Facebook and subsequently shared with an advertiser. The premise of the article is misleading. Facebook does not offer tools to target people based on their emotional state.”

In fact, Wynn-Williams quotes the refutation, calling it a “flat-out lie”. She says this is one of at least two similar slide decks discussing targeting ads based on a teenager’s emotional state, and in an internal discussion, finds an instance where Facebook apparently helped target beauty ads to teenage girls when they deleted pictures of themselves from their accounts. She also writes that the deputy chief privacy officer confirmed it is entirely possible to target ads based on implied emotion.

After the “lie” is released as a statement anyway, Wynn-Williams says she got a phone call from a Facebook ad executive frustrated by how it undermined their pitch to advertisers for precise targeting.

SWW’s New Claim:

Donald Trump Was Charged Less Money For Incendiary Adverts Which Reached More People.

Old News:

Claim Was Based On A 2018 Article By Wired, Which Facebook Refuted.

The argument made by Meta’s Andrew Bosworth, in a since-deleted Twitter thread, was that Trump’s average CPM was almost always higher than that of the Clinton campaign. But while this is one interpretation of the Wired article — one the publication disputed — this is not the claim made by Wynn-Williams. She only says the high levels of engagement on Trump’s ads drove their prices down, but not necessarily less than Clinton’s ads.

Those were all of the claims Meta chose to preemptively dispute or reframe. The problem is that Wynn-Williams did make news in this book. There are plenty of examples of high-level discussions, including quoted email messages, showing the contemporaneous mindset to build its user base and market share no matter the cost. It is ugly. Meta’s public relations team apparently thought it could get in front of this thing without having all the details, but their efforts were weak and in vain.

Following its publication, Meta not only sought and received a legal demand that Wynn-Williams must stop talking about the book, it followed its “playbook for answering whistleblowers”. I am not a highly paid public relations person; I assume those who are might be able to explain if this strategy is effective. It does not seem as though it is, however.

This is all very embarrassing for Meta, yet seems entirely predictable. Like I wrote, I have my own biases against the company. I already thought it was a slimy company and I hate how much this confirms my expectations. So I think it is important to stay skeptical. Perhaps there are other sides to these stories. But nothing in “Careless People” seems unbelievable — only unseemly and ugly.

Credit Card Insurance Is, in My Case, a Good Replacement for AppleCare

A little over a month ago, I had the misfortune of breaking both a fifteen-year record of intact phone screens and, relatedly, my phone’s screen. This sucked in part because I can no longer be so smug about not using a case, and also because I do not have AppleCare. I do have insurance coverage on my credit card. I had never gone through this process before, but it would turn out to be perfectly adequate.

There was some paperwork involved, of course. There was a fair bit of waiting, too. But I got paid in full for the repair. That is, while I had to put $450 up front, I ultimately paid nothing to fix my own accidental damage. For comparison, if I had purchased AppleCare when I got my iPhone 15 Pro, at $13.50 per month, it would have cost me over $240, plus $40 for the screen replacement itself.

I am not saying you should not buy AppleCare or extended warranties in general. Go bananas. In my case, I do not think it would have been worth $280 to save some paperwork and time.

This is also an example of how having a lower income makes everything cost more. There are usually minimum financial requirements for having a card with insurance like this, a level I thankfully meet. It allowed me to briefly shoulder the out-of-warranty repair cost and, ultimately, gave me a free repair. If I did not meet that threshold, I would have had to pay instalments of $13.50 just in case I dropped my phone. It does not seem right I paid nothing for this repair when someone earning less than I do would have paid so much.

Apple Could Build Great Platforms for Third-Party A.I. If It Wanted To

There is a long line of articles questioning Apple’s ability to deliver on artificial intelligence because of its position on data privacy. Today, we got another in the form of a newsletter.

Reed Albergotti, Semafor:

Meanwhile, Apple was focused on vertically integrating, designing its own chips, modems, and other components to improve iPhone margins. It was using machine learning on small-scale projects, like improving its camera algorithms.

[…]

Without their ads businesses, companies like Google and Meta wouldn’t have built the ecosystems and cultures required to make them AI powerhouses, and that environment changed the way their CEOs saw the world.

Again, I will emphasize this is a newsletter. It may seem like an article from a prestige publisher that prides itself on “separat[ing] the facts from our views”, but you might notice how, aside from citing some quotes and linking to ads, none of Albergotti’s substantive claims are sourced. This is just riffing.

I remain skeptical. Albergotti frames this as both a mindset shift and a necessity for advertising companies like Google and Meta. But the company synonymous with the A.I. boom, OpenAI, does not have the same business model. Besides, Apple behaves like other A.I. firms by scraping the web and training models on massive amounts of data. The evidence for this theory seems pretty thin to me.

But perhaps a reluctance to be invasive and creepy is one reason why personalized Siri features have been delayed. I hope Apple does not begin to mimic its peers in this regard; privacy should not be sacrificed. I think it is silly to be dependent on corporate choices rather than legislation to determine this, but that is the world some of us live in.

Let us concede the point anyhow, since it suggests a role Apple could fill by providing an architecture for third-party A.I. on its products. It does not need to deliver everything to end users; it can focus on building a great platform. Albergotti might sneeze at “designing its own chips […] to improve iPhone margins”, which I am sure was one goal, but it has paid off in ridiculously powerful Macs perfect for A.I. workflows. And, besides, it has already built some kind of plugin architecture into Apple Intelligence because it has integrated ChatGPT. There is no way for other providers to add their own extension — not yet, anyhow — but the system is there.

Gus Mueller:

The crux of the issue in my mind is this: Apple has a lot of good ideas, but they don’t have a monopoly on them. I would like some other folks to come in and try their ideas out. I would like things to advance at the pace of the industry, and not Apple’s. Maybe with a blessed system in place, Apple could watch and see how people use LLMs and other generative models (instead of giving us Genmoji that look like something Fisher-Price would make). And maybe open up the existing Apple-only models to developers. There are locally installed image processing models that I would love to take advantage of in my apps.

Via Federico Viticci, MacStories:

Which brings me to my second point. The other feature that I could see Apple market for a “ChatGPT/Claude via Apple Intelligence” developer package is privacy and data retention policies. I hear from so many developers these days who, beyond pricing alone, are hesitant toward integrating third-party AI providers into their apps because they don’t trust their data and privacy policies, or perhaps are not at ease with U.S.-based servers powering the popular AI companies these days. It’s a legitimate concern that results in lots of potentially good app ideas being left on the table.

One of Apple’s specialties is in improving the experience of using many of the same technologies as everyone else. I would like to see that in A.I., too, but I have been disappointed by its lacklustre efforts so far. Even long-running projects where it has had time to learn and grow have not paid off, as anyone can see in Siri’s legacy.

What if you could replace these features? What if Apple’s operating systems were great platforms by which users could try third-party A.I. services and find the ones that fit them best? What if Apple could provide certain privacy promises, too? I bet users would want to try alternatives in a heartbeat. Apple ought to welcome the challenge.

Canadian Sovereignty, Digital and Geographic

In just about every discussion concerning TikTok’s ability to operate within the United States, including my own, two areas of concern are cited: users’ data privacy, and the manipulation of public opinion through its feeds by a hostile foreign power. Regarding the first, the U.S., Canada, and any other country is not serious about the mishandling of private information unless it passes comprehensive data privacy legislation, so we can ignore that for now. The latter argument, however, merited my writing thousands of words in that single article. So let me dig into it again from a different angle.

In a 2019 speech at Georgetown University, Mark Zuckerberg lamented an apparently lost leadership by the U.S. in technology. “A decade ago, almost all of the major internet platforms were American,” he said. “Today, six of the top ten are Chinese”.

Incidentally, Zuckerberg gave this speech the same year in which his company announced, after five years of hard work and ingratiation, it was no longer pursuing an expansion into China which would necessarily require it to censor users’ posts. It instead decided to mirror the denigration of Chinese internet companies by U.S. lawmakers and lobbied for a TikTok ban. This does not suggest a principled opposition on the grounds of users’ free expression. Rather, it was seen as a good business move to expand into China until it became more financially advantageous to try to get Chinese companies banned stateside.

I do not know where Zuckerberg got his “six of the top ten” number. The closest I could find was five — based solely on total user accounts. Regardless of the actual number, Zuckerberg was correct to say Chinese internet companies have been growing at a remarkable rate, but it is a little misleading; aside from TikTok, these apps mostly remain a domestic phenomenon. WeChat’s user base, for example, is almost entirely within China, though it is growing internationally as one example of China’s “Digital Silk Road” initiative.

Tech companies from the U.S. still reign supreme nearly everywhere, however. The country exports the most popular social networks, messaging services, search engines, A.I. products, CDNs, and operating systems. Administration after administration has recognized the value to the U.S. of boosting the industry for domestic and foreign policy purposes. It has been a soft power masterstroke for decades.

In normal circumstances, this is moderately concerning for those of us in the rest of the world. Policies set in the U.S. — either those set by companies because of cultural biases or, in the case of something like privacy or antitrust, legal understanding — may not reflect expectations in other regions, and it is not ideal that so much of modern life depends so heavily on the actions of a single country.

These are not normal circumstances — especially here, in Canada. The president of the U.S. is deliberately weakening the Canadian economy in an attempt to force us to cede our sovereignty. Earlier this week, while he was using his extraordinary platform to boost the price of Tesla shares, the president reiterated this argument while also talking about increasing the size of the U.S. military. This is apparently all one big joke in a broadly similar way as is pushing a live chicken into oncoming traffic. Many people have wasted many hours and words trying to understand why he is so focused on this fifty-first state nonsense — our vast natural resources, perhaps, or the potential for polar trade routes because of warming caused by those vast natural resources. But this is someone whose thoughts, in the words of David Brooks, “are often just six fireflies beeping randomly in a jar”. He said why he wants Canada in that Tesla infomercial. “When you take away that [border] and you look at that beautiful formation,” he said while gesticulating with his hands in a shape unlike the combined area of Canada and the United States but quite like how someone of his vibe might crassly describe a woman’s body, “there is no place anywhere in the world that looks like that”. We are nothing more than a big piece of land, and he would like to take it.

Someone — I believe it was Musk, standing just beside him — then reminded him of how he wants Greenland, too, which put a smile on his face as he said “if you add Greenland […] it’s gonna look beautiful”. In the Oval Office yesterday, he sat beside NATO’s Mark Rutte and said “we have a couple of [military] bases on Greenland already”, and “maybe you will see more and more soldiers go there, I don’t know”. It is all just a big, funny joke, from a superpower with the world’s best-funded military, overseen by a chaotic idiot. Ha ha ha.

The U.S. has become a hostile foreign power to Canada and, so, we should explore its dominance in technology under the same criteria as it has China’s purported control over TikTok and how that has impacted U.S. sovereignty. If, for instance, it makes sense to be concerned about the obligation of Chinese companies to reflect ruling party ideology, it is perhaps more worrisome U.S. tech companies are lining up to do so voluntarily. They have a choice.

Similarly, should we be suspicious that our Instagram feeds and Google searches are being tilted in a pro-U.S. direction? I am certain one could construct a study similar to those indicating a pro-China bias on TikTok (PDF) with U.S. platforms. Is YouTube pushing politically divisive videos to Canadians in an effort to weaken our country? Is Facebook suggesting pro-U.S. A.I. slop to Canadians something more than algorithmic noise?

This is before considering Elon Musk who, as both a special government employee and owner of X, is more directly controlling than Chinese officials are speculated to be over TikTok. X has become a solitary case study in state influence over social media. Are the feeds of Canadian users being manipulated? Is his platform a quasi-official propaganda outlet?

Without evidence, these ideas all strike me as conspiracy-brained nonsense. I imagine one could find just as much to support these ideas as is found in those TikTok studies, a majority of which observe the effects of select searches. The Network Contagion one (PDF), linked earlier, is emblematic of these kinds of reports, about which I wrote last year referencing two other examples — one written for the Australian government, and a previous Network Contagion report:

The authors of the Australian report conducted a limited quasi-study comparing results for certain topics on TikTok to results on other social networks like Instagram and YouTube, again finding a handful of topics which favoured the government line. But there was no consistent pattern, either. Search results for “China military” on Instagram were, according to the authors, “generally flattering”, and X searches for “PLA” scarcely returned unfavourable posts. Yet results on TikTok for “China human rights”, “Tianamen”, and “Uyghur” were overwhelmingly critical of Chinese official positions.

The Network Contagion Research Institute published its own report in December 2023, similarly finding disparities between the total number of posts with specific hashtags — like #DalaiLama and #TiananmenSquare — on TikTok and Instagram. However, the study contained some pretty fundamental errors, as pointed out by — and I cannot believe I am citing these losers — the Cato Institute. The study’s authors compared total lifetime posts on each social network and, while they say they expect 1.5–2.0× the posts on Instagram because of its larger user base, they do not factor in how many of those posts could have existed before TikTok was even launched. Furthermore, they assume similar cultures and a similar use of hashtags on each app. But even benign hashtags have ridiculous differences in how often they are used on each platform. There are, as of writing, 55.3 million posts tagged “#ThrowbackThursday” on Instagram compared to 390,000 on TikTok, a ratio of 141:1. If #ThrowbackThursday were part of this study, the disparity on the two platforms would rank similarly to #Tiananmen, one of the greatest in the Institute’s report.

The problem with most of these complaints, as their authors acknowledge, is that there is a known input and a perceived output, but there are oh-so-many unknown variables in the middle. It is impossible to know how much of what we see is a product of intentional censorship, unintentional biases, bugs, side effects of other decisions, or a desire to cultivate a less stressful and more saccharine environment for users. […]

The more recent Network Contagion study is perhaps even less reliable. It comprises a similar exploration of search results, and surveys comparing TikTok users’ views to those of non-users. In the first case, the researchers only assessed four search terms: Tibet, Tiananmen, Uyghur, and Xinjiang. TikTok’s search results produced the fewest examples of “anti-China sentiment” in comparison with Instagram and YouTube, but the actual outcomes were not consistent. Results for “Uyghur” and “Xinjiang” on TikTok were mostly irrelevant; on YouTube, however, nearly half of a user’s journey would show videos supportive of China for both queries. Results for “Tibet” were much more likely to be “anti-China” on Instagram than the other platforms, though similarly “pro-China” as TikTok.

These queries are obviously sensitive in China, and I have no problem believing TikTok may be altering search results. But this study, like the others I have read, is not at all compelling if you start picking it apart. For the “Uyghur” and “Xinjiang” examples, researchers say the heavily “pro-China” results on YouTube are thanks to “pro-CCP media assets” and “official or semi-official CCP media sources” uploading loads of popular videos with a positive spin. Sometimes, TikTok is more likely to show irrelevant results; at other times, it shows “neutral” videos, which the researchers say are things like unbiased news footage. In some cases — as with results for “Tiananmen” and “Uyghur” — TikTok was similarly likely to show “pro-China” and “anti-China” results. The researchers hand-wave away these mixed outcomes by arguing “the TikTok search algorithm systematically suppresses undesirable anti-China content while flooding search results with irrelevant content”. Yet the researchers document no effort to compare the results of these search terms with anything else — controversial or politically sensitive terms outside China, for example, or terms which result in overwhelmingly dour results, or generic apolitical terms. In all cases, TikTok returns more irrelevant results than the other platforms; maybe it is just bad at search. We do not know because we have nothing to compare it to. Again, I have no problem believing TikTok may be suppressing results, but this study does not convince me it is uniformly reflecting official Chinese government lines.

As for the survey results, they show TikTok users had more favourable views of China as a travel destination and were less concerned about its human rights abuses. This could plausibly be explained by TikTok users skewing younger and, therefore, growing up seeing a much wealthier China than older generations. Younger people might simply be less aware of human rights abuses. For contrast, people who do not use TikTok are probably more likely to have negative views of China — not just because they are more likely to be older, but because they are suspicious of the platform. “When controlling for age,” the researchers say, “TikTok use significantly and uniquely predicted more positive perceptions of China’s human rights record” among video-based platforms, but Facebook users also had more positive perceptions, and nobody is claiming Facebook is in the bag for China. Perhaps there are other reasons — but they go unexplored.

This is a long digression, but it indicates to me just how possible it would be to create a similar understanding for social media’s impact on Canada. In my own experience on YouTube — admittedly different from a typical experience because I turned off video history — the Related Videos on just about everything I watch are packed with recommendations for Fox News, channels dedicated to people getting “owned”, and pro-Trump videos. I do not think YouTube is trying to sway me into a pro-American worldview and shed my critical thinking skills, but one could produce a compelling argument for it.

This is something we are going to need to pay an increasing level of attention toward. People formerly with Canadian intelligence are convinced the U.S. president is doing to Canada in public what so many before him have done to fair-weather friends in private. They believe his destabilization efforts may be supported by a propaganda strategy, particularly on Musk’s X. These efforts may not be unique to social media, either. Postmedia, the publisher of the National Post plus the most popular daily newspapers in nearly every major Canadian city, is majority U.S.-owned. This is not good.

Yet we should not treat social platforms the same as we do media organizations. We should welcome foreign-owned publications to cover our country, but the ownership of our most popular outlets should be primarily domestic. The internet does not work like that — for both good and bad — nor should we expect it to. Requiring Canadian subsidiaries of U.S. social media companies or banning them outright would continue the ongoing splintering of internet services with little benefit for Canadians or, indeed, the expectations of the internet. We should take a greater lead in determining our digital future without being so hostile to foreign services. That means things like favouring protocols over platforms, which give users more choice over their experience, and permit a level of autonomy and portability. It means ensuring a level of digital sovereignty with our most sensitive data.

It is also a reminder to question the quality of automated recommendations and search results. We do not know how any of them work — companies like Google often cite third-party manipulation as a reason to keep them secret — and I do not know that people would believe tech companies if they were more transparent in their methodology. To wit, digital advertisements often have a button or menu item explaining why you are seeing that particular ad, but it has not stopped many people from believing their conversations are picked up by a device’s microphone and used for targeting. If TikTok released the source for its recommendations engine, would anyone trust it? How about if Meta did the same for its products? I doubt it; nobody believes these companies anyway.

The tech industry is facing declining public trust. The United States’ reputation is sinking among allies and its domestic support for civil rights is in freefall. Its leader is waging economic war on the country where I live. CEOs lack specific values and are following the shifting tides. Yet our world relies on technologies almost entirely dependent on the stability of the U.S., which is currently in short supply. The U.S., as Paris Marx wrote, “needs to know that it cannot dominate the tech economy all on its own, and that the people of the world will no longer accept being subject to the whims of its dominant internet and tech companies”. The internet is a near-miraculous global phenomenon. Restricting companies based on their country of origin is not an effective way to correct this imbalance. But we should not bend to U.S. might, either. It is, after all, just one country of many. The rest of the world should encourage it to meet us at our level.

Apple Confirms Delayed Launch of Personalized Siri Features

Apple spokesperson Jacqueline Roy, in a statement provided seemingly first to both Stephen Nellis, of Reuters, and John Gruber:

[…] We’ve also been working on a more personalized Siri, giving it more awareness of your personal context, as well as the ability to take action for you within and across your apps. It’s going to take us longer than we thought to deliver on these features and we anticipate rolling them out in the coming year.

Unsurprisingly, this news comes on a Friday and is announced via a carefully circulated statement instead of on Apple’s own website. It is a single feature, but it is a high-priority one showcased in its celebrity infused ads for its flagship iPhone models. I think Apple ought to have published its own news instead of relying on other outlets to do its dirty work, but it fits a pattern. It happened with AirPods and again with AirPower; the former has become wildly successful, while the latter was canned.

This announcement reflects rumours of the feature’s fraught development. Mark Gurman, Bloomberg, in February:

The company first unveiled plans for a new AI-infused Siri at its developers conference last June and has even advertised some of the features to customers. But Apple is still racing to finish the software, said the people, who asked not to be identified because the situation is private. Some features, originally planned for April, may have to be postponed until May or later, they said.

Do note how “or later” is doing the bulk of the work in this paragraph. Nevertheless, he seems to have forecasted the delay announced today.

While it is possible to reconcile Apple’s “coming year” timeline with Gurman’s May-or-later availability while staying within the current release cycle, the statement is a tacit acknowledgement these features are now slated for the next major versions of Apple’s operating system, perhaps no sooner than a release early next year. I do not see why Apple would have issued this statement if it were confident it could ship personalized Siri before September’s new releases. That is a long time between marketing and release for any company, and particularly so for Apple.

This is a risk of announcing something before it is ready, something the WWDC keynote is increasingly filled with. Instead of monolithic September releases with occasional tweaks throughout the year, Apple adopted a more incremental strategy. I would like to believe this has made Apple’s software more polished — or, less charitably, slowed its quality decline. What it has actually done is turn Apple’s big annual software presentation into a series of promises to be fulfilled throughout the year. To its credit, it has almost always delivered and, so, it has been easy to assume the hot streak will continue. This is a good reminder we should treat anything not yet shipping in a release or beta build as a potential feature only.

The delay may ultimately be good news. It is better for Apple to ship features that work well than it is to get things out the door quickly. Investors do not seem bothered; try spotting the point on today’s chart when Gruber and Reuters published the statements they received. And, anyway, most Apple Intelligence features released so far seem rushed and faulty. I would not want to see more of the same. Siri has little reputation to lose, so it makes sense to get this round of changes more right than not.

Besides, Apple only just began including the necessary APIs in the latest developer betas of iOS 18.4. No matter when Apple gets this out, the expansiveness of its functionality is dependent on third-party buy-in. There was a time when developer adoption of new features was a given. That is no longer the case.

According to Gurman as recently as earlier this week, a May release is possible (Update: Oops, I should have checked again.), but I would bet against it. If his reporting is to be believed, however, the key features announced as delayed today require a wholly different architecture which Apple was planning on merging with the existing Siri infrastructure midway through the iOS 19 cycle. It seems possible to me the timeline on both projects could now be interlinked. After all, why not? It is not like Siri is getting worse. No rush.