iPhones are no longer cameras in the traditional sense. Instead, they are devices at the vanguard of “computational photography,” a term that describes imagery formed from digital data and processing as much as from optical information. Each picture registered by the lens is altered to bring it closer to a pre-programmed ideal. Gregory Gentert, a friend who is a fine-art photographer in Brooklyn, told me, “I’ve tried to photograph on the iPhone when light gets bluish around the end of the day, but the iPhone will try to correct that sort of thing.”

Advertisers don’t really want to know who you are - they want to show diaper ads to people who have babies, not to show them to people who don’t, and to have some sense of which ads drove half a million sales and which ads drove a million sales.

In practice, ‘showing car ads to people who read about cars’ led the adtech industry to build vast piles of semi-random personal data, aggregated, disaggregated, traded, passed around and sometimes just lost, partly because it could and partly because that appeared to be the only way to do it. After half a decade of backlash, there are now a bunch of projects trying to get to the same underlying advertiser aims - to show ads that are relevant, and get some measure of ad effectiveness - while keeping the private data private.

Apple has pursued a very clear theory that analysis and tracking is private if it happens on your device and is not private if leaves your device or happens in the cloud. Hence, it’s built a complex system of tracking and analysis on your iPhone, but is adamant that this is private because the data stays on the device. People have seemed to accept this (so far - or perhaps the just haven’t noticed it), but acting on the same theory Apple also created a CSAM scanning system that it thought was entirely private - ‘it only happens your device!’ - that created a huge privacy backlash, because a bunch of other people think that if your phone is scanning your photos, that isn’t ‘private’ at all. So is ‘on device’ private or not? What’s the rule? What if Apple tried the same model for ‘private’ ads in Safari? How will the public take FLoC? I don’t think we know.

On / off device is one test, but another and much broader is first party / third party: the idea it’s OK for a website to track what you do on that website but not OK for adtech companies to track you across many different websites. This is the core of the cookie question

At this point one answer is to cut across all these questions and say that what really matters is whether you disclose whatever you’re doing and get consent. Steve Jobs liked this argument. But in practice, as we've discovered, ‘get consent’ means endless cookie pop-ups full of endless incomprehensible questions that no normal consumer should be expected to understand, and that just train people to click ‘stop bothering me’. Meanwhile, Apple’s on-device tracking doesn't ask for permission, and opts you in by default, because, of course, Apple thinks that if it's on the device it's private. Perhaps ‘consent’ is not a complete solution after all.

If you can only analyse behaviour within one site but not across many sites, or make it much harder to do that, companies that have a big site where people spend lots of time have better targeting information and make more money from advertising. If you can only track behaviour across lots of different sites if you do it ‘privately’ on the device or in the browser, then the companies that control the device or the browser have much more control over that advertising

when you try to implement one of these specs you quickly realize that you cannot do it with the spec alone. You need example code, base implementations, test suite software and test data to build conformant software. Unfortunately, the Bluetooth SIG hides these resources behind a membership wall. Guess what happens then? You get lots of implementations of these specs that are a little bit off and don't handle all edge cases.

it is very difficult to figure out what specific effect ATT has because there are so many factors involved

If ATT were so significantly kneecapping revenue, I would think we would see a pronounced skew against North America compared to elsewhere. But that is not the case. Revenue in North America is only slightly off compared to the company total, and it is increasing how much it earns per North American user compared to the rest of the world.

iOS is far more popular in the U.S. and Canada than it is in Europe, but Meta incurred a greater revenue decline — in absolute terms and, especially, in percentage terms — in Europe. Meta was still posting year-over-year gains in both those regions until this most recent quarter, even though ATT rolled out over a year ago.

there are those who believe highly-targeted advertisements are a fair trade-off because they offer businesses a more accurate means of finding their customers, and the behavioural data collected from all of us is valuable only in the aggregate. That is, as I understand it, the view of analysts like Seufert, Benedict Evans, and Ben Thompson. Frequent readers will not be surprised to know I disagree with this premise. Regardless of how many user agreements we sign and privacy policies we read, we cannot know the full extent of the data economy. Personal information about us is being collected, shared, combined, and repackaged. It may only be profitable in aggregate, but it is useful with finer granularity, so it is unsurprising that it is indefinitely warehoused in detail.

Seufert asked, rhetorically, “what happens when ads aren’t personalized?”, answering “digital ads resemble TV ads: jarring distractions from core content experience. Non-personalized is another way of saying irrelevant, or at best, randomly relevant.”

does it make sense to build the internet’s economy on the backs of a few hundred brokers none of us have heard of, trading and merging our personal information in the hope of generating a slightly better click-through rate?

Then there is the much bigger question of whether people should even be able to opt into such widespread tracking. We simply cannot be informed consumers in every aspect of our lives, and we cannot foresee how this information will be used and abused in the full extent of time. It sounds boring, but what is so wrong with requiring data minimization at every turn, permitting only the most relevant personal data to be collected, and restricting the ability for this information to be shared or combined?

Does ATT really “[deprive] consumers of widespread ad relevancy and advertisers and publishers of commercial opportunity”? Even if it does — which I doubt — has that commercial opportunity really existed with meaningful consumer awareness and choice? Or is this entire market illegitimate, artificially inflated by our inability to avoid becoming its subjects?

Conflicts like these are one of many reasons why privacy rights should be established by regulators, not individual companies. Privacy must not be a luxury good, or something you opt into, and it should not be a radical position to say so. We all value different degrees of privacy, but it should not be possible for businesses to be built on whether we have rights at all. The digital economy should not be built on such rickety and obviously flawed foundations.

“I’ve been on the internet for the last 10 years and I don’t know if I like what I like or what an algorithm wants me to like,” Peter wrote. She’d come to see social networks’ algorithmic recommendations as a kind of psychic intrusion, surreptitiously reshaping what she’s shown online and, thus, her understanding of her own inclinations and tastes.

Besieged by automated recommendations, we are left to guess exactly how they are influencing us, feeling in some moments misperceived or misled and in other moments clocked with eerie precision.

When Messages in iCloud is enabled, iMessage, Apple Messages for Business, text (SMS), and MMS messages are removed from the user’s existing iCloud Backup and are instead stored in an end-to-end encrypted CloudKit container for Messages. The user’s iCloud Backup retains a key to that container. If the user later disables iCloud Backup, that container’s key is rolled, the new key is stored only in iCloud Keychain (inaccessible to Apple and any third parties), and new data written to the container can’t be decrypted with the old container key.

I care about people more than I care about positions or beliefs, which I tend to consider a subservient class of psychological phenomena. That is to say: I think people wear beliefs like clothes; they wear what they have grown to consider sensible or attractive; they wear what they feel flatters them; they wear what keeps them dry and warm in inclement winter. They believe their opinions, tastes, philosophies are who they are, but they are mistaken. (Aging is largely learning what one is not, it seems to me).

Criticism must serve some function to justify the pain it causes: it must, say, avert a disastrous course of action being deliberated by a group, or help thwart the rise of a barbarous politician. But this rarely occurs. Most criticism, even of the most erudite sort, is, as we all know, wasted breath: preached to one’s own choir, comically or indignantly cruel to those one doesn’t respect, unlikely to change the behavior of anyone not already in agreement.On the other hand! There persists the idea that culture arises out of the scrum of colliding perspectives, and that it is therefore a moral duty to remonstrate against stupidity, performative emoting, deceitful art, destructively banal fiction, and so on. If one doesn’t speak up, one cannot lament the triumph of moral and imaginative vacuity.

One must believe, of course, that there are abstractions worth protecting, and therefore abstractions worth hurting others for, in order to criticize; and the endless repetitiveness of cultural history seems to devalue such abstractions as surely as bad art and cliche devalue words.

My biggest concern about the bill is that a huge chunk of the revenue raised ($124 billion) is purportedly going to come from increased IRS enforcement — enforcement that requires an $80 billion investment. But the image of a super-IRS going after wealthy corporations and rich billionaires who skirt tax laws is not the reality. Instead, the IRS usually spends its money where it is most efficient: Auditing the middle class and the most economically vulnerable taxpayers who can't afford teams of lawyers. According to The Washington Post, More than 4 in 10 of its audits in 2021 targeted recipients of the earned income tax credit, one of the country’s main anti-poverty measures.

The bill is a climate change and health care bill with very clear direct tax hikes on profitable corporations to offset the spending. It will almost certainly reduce emissions and, in the long term, bring more green energy onto the grid. Health insurance and drug prices for Medicare recipients and people on the ACA will probably come down. They may go up for others, depending on how private insurers react. Some of the new revenue will come from increased IRS enforcement, which could hit middle and lower-income people hardest. And, of course, corporations are liable to pass on tax hikes with increased prices or layoffs, along with stock shares falling.

The goal? To make new green energy production cheaper for utilities to build than fossil fuel plants are.

Material-based software can also have gentler learning curves, because the user only needs to learn a small set of rules about how different metaphors in the software interact with each other rather than learning deep hierarchies of menus and terminologies. In the best case, users can continue to discover new capabilities and workflows long after the initial release of the software.

Take nonlinear video editing software, like Final Cut Pro and Premiere Pro, for example. Though they have their fair share of menu complexity, it’s pretty intuitive for anyone to understand the basic building blocks of video and audio clips sitting on a layered timeline. Here, the video and audio clips are composed of a software material that have their own laws of physics: they can grow and shrink to take up more or less time on the timeline. They can be moved around and layered in front of or behind other clips, but they can’t occupy the same space on the same “track” of the timeline. The timeline that runs left-to-right is a kind of “world” in which the materials of audio and video exist.

In complexity science, ‘emergence’ describes the way that interactions between individual components in a complex system can give rise to new behavior, patterns, or qualities. For example, the quality of ‘wetness’ cannot be found in a single water molecule, but instead arises from the interaction of many water molecules together. In living systems, emergence is at the core of adaptive evolution.

Design for emergence prioritizes open-ended combinatorial possibilities such that the design object can be composed and adapted to a wide variety of contextual and idiosyncratic niches by its end-user. LEGO offers an example — a simple set of blocks with a shared protocol for connecting to one another from which a nearly infinite array of forms can emerge. Yet as we will see, design for emergence can generate value well beyond children’s toys.

In contrast to high modern design, user-centered design takes a more modest position; the designer does not inherently know everything, and therefore she must meticulously study the needs and behaviors of users in order to produce a good design. User-centered design remains the dominant design paradigm today, employed by environmental designers, tech companies, and design agencies around the world.

In this paradigm, design is about gaining knowledge from the user, identifying desirable outcomes, and controlling as much of the process as possible to achieve those outcomes. ‘Design’ remains synonymous with maximizing control.

But consider even the ‘desire path’ example pictured above. The modal user may be well supported by paving the desire path indicated by their behavior, but what good is a paved path leading to stairs for a wheelchair user? In practice, user-centered design tends to privilege the modal user at the expense of the long-tail user whose needs may be just as great.

User-centered design has a better track record than high modern design, but it still exerts a homogenizing effect. The needs of the modal user are accommodated and scaled through software or industrial manufacturing, while power users and those with edge cases can do nothing but actively petition the designer for attention. In most cases, diverse users with a wide variety of niche use cases are forced to conform to the behavior of the modal user.

In design for emergence, the designer assumes that the end-user holds relevant knowledge and gives them extensive control over the design. Rather than designing the end result, we design the user’s experience of designing their own end result. In this way we can think of design for emergence as a form of ‘meta-design.’

In other words, to address the long-tail problem, the tool must be flexible enough that it can be adapted to unexpected and idiosyncratic problem spaces—especially those unanticipated by the tool’s designer.

In contrast to user-centered design, design for emergence invites the user into the design process not only as a subject of study, but as a collaborator with agency and control.

What all these tools have in common is support for open-ended adaptation to highly contextual problems without the need for technical knowledge. Rather than building a static, purpose-built solution to a single common problem with lots of users (and lots of competitors), they’ve won robust user bases by supporting a broad swath of long-tail user needs.

Design for emergence is composable. It provides a limited ‘alphabet’ and a generative grammar that’s easy to learn and employ, yet can be extended to create powerful, complex applications. As Seymour Papert once remarked, “English is a language for children,” but this fact, “does not preclude its being also a language for poets, scientists, and philosophers.”

Subject after subject reported that they were on Tinder to find someone to love and to love them back and defined love in the most traditional of terms: something that took work, a container in which sex was sacred and where intimacy built over time. They acknowledged that their encounters on Tinder didn’t offer that, yet they went to Tinder to find it. The contradiction was confusing: They wanted sex to be meaningful but felt that Tinder removed the sacredness. They wanted bonds to be lasting but acknowledged they were easily broken.