Cities are commonly mapped and surveilled like the internet, said to be made up of “networks” and clusters of “users.”

A City Is Not a Tree can provide us with some answers. As Alexander argued almost 60 years ago, our minds are inclined to categorize the world as a tree, but an organic society and city actually resembles a semilattice. And just like with a city, organizing the internet like a tree stifles it completely.

The internet hasn’t become a tree, but there are certainly those who would like it to resemble one. Both leading tech platforms and governments believe themselves to be capable of containing information and separating its parts. The process started in earnest after the Arab Spring (2010-2012), when it became clear that online activity could produce shocks with real-world consequences. A growing pessimism about technology in the hands of the public developed at the top, as the interests of both “public safety” and profit converged to more deliberately plan the internet and mediate its branches. Simply put, complex systems are easier to surveil when information is neatly siloed into branches. It also simplifies data collection for advertisers.

Overlap on the internet is made possible through search and indexing which has, in almost all cases, badly declined.28 Google, as the leading indexer, has been the prime target of enshittification despite its market dominance increasing.29 Additionally, most platforms are walled gardens that are not easily searchable, their content only being found because it was reposted in another walled garden. Platforms have an interest in making sure users stay in their domain as much as possible. This makes overlap especially difficult by design, and so much of the internet now exists as islands on the periphery as a result. Effectively, that which would make a semilattice of the internet dynamic and alive is being dismantled.

Like a city, the internet is a receptacle for life, and how it organizes itself has consequences for the psychological well-being of its users.

The first hyperlinks pointed within their own domain, like the doors separating the rooms in your home. However, with the world wide web, the doors became portals, and pioneers mapped out site directories to guide internet travelers to the frontier of development. Reject modern interstates and embody Tarzan, Jane, or the chimpanzee to swing from link to link, blue to purple.

if you like handmade websites, you should visit Gossips Web or Brutalist Websites. These are the digital equivalent to the jazz bar, punk record store, or other physical places where subcultures gather. There’s likely one made by a devotee whatever your interest, like cyberfeminism, tiny internet sites, cozy websites, niche museums, list of lists, LA sandwiches, and much more.

This analogy to lossy compression is not just a way to understand ChatGPT’s facility at repackaging information found on the Web by using different words. It’s also a way to understand the “hallucinations,” or nonsensical answers to factual questions, to which large language models such as ChatGPT are all too prone

When an image program is displaying a photo and has to reconstruct a pixel that was lost during the compression process, it looks at the nearby pixels and calculates the average. This is what ChatGPT does when it’s prompted to describe, say, losing a sock in the dryer using the style of the Declaration of Independence: it is taking two points in “lexical space” and generating the text that would occupy the location between them

they’ve discovered a “blur” tool for paragraphs instead of photos, and are having a blast playing with it.

A close examination of GPT-3’s incorrect answers suggests that it doesn’t carry the “1” when performing arithmetic. The Web certainly contains explanations of carrying the “1,” but GPT-3 isn’t able to incorporate those explanations. GPT-3’s statistical analysis of examples of arithmetic enables it to produce a superficial approximation of the real thing, but no more than that.

In human students, rote memorization isn’t an indicator of genuine learning, so ChatGPT’s inability to produce exact quotes from Web pages is precisely what makes us think that it has learned something. When we’re dealing with sequences of words, lossy compression looks smarter than lossless compression

Generally speaking, though, I’d say that anything that’s good for content mills is not good for people searching for information. The rise of this type of repackaging is what makes it harder for us to find what we’re looking for online right now; the more that text generated by large language models gets published on the Web, the more the Web becomes a blurrier version of itself.

Can large language models help humans with the creation of original writing? To answer that, we need to be specific about what we mean by that question. There is a genre of art known as Xerox art, or photocopy art, in which artists use the distinctive properties of photocopiers as creative tools. Something along those lines is surely possible with the photocopier that is ChatGPT, so, in that sense, the answer is yes

If students never have to write essays that we have all read before, they will never gain the skills needed to write something that we have never read.

Sometimes it’s only in the process of writing that you discover your original ideas.

Some might say that the output of large language models doesn’t look all that different from a human writer’s first draft, but, again, I think this is a superficial resemblance. Your first draft isn’t an unoriginal idea expressed clearly; it’s an original idea expressed poorly, and it is accompanied by your amorphous dissatisfaction, your awareness of the distance between what it says and what you want it to say. That’s what directs you during rewriting, and that’s one of the things lacking when you start with text generated by an A.I.