Established publishers seeking relief from the whims of social-media platforms and a brutal advertising environment found in product recommendations steady growth and receptive audiences, especially as e-commerce became a more dominant mode of shopping. Today, these businesses are materially significant — in a 2023 survey, 41 percent of surveyed media companies said that e-commerce accounted for more than a fifth of their revenue, which few can afford to lose. It is a relatively new way in which publishers have become reacquainted — after social-media traffic disappeared and “pivots to video” completed their rotations — with queasy feelings of dependence on massive tech companies, from Facebook and Google to Amazon and, well, Google.

Time magazine announced a brand called Time Stamped, “a project to make perplexing choices less perplexing by supplying our readers with trusted reviews and common sense information,” with “a rigorous process for testing products, analyzing companies,” and making recommendations. In early 2024, the Associated Press announced its own recommendation site, AP Buyline, as an “initiative designed to simplify complex consumer-made decisions by providing its audience with reliable evaluations and straightforward insights,” based on “a thorough method of testing items, evaluating companies and suggesting choices.” Both sites currently recommend money-related products and services, including credit cards, debt-consolidation loans, and insurance policies, categories that can command very high commissions; the AP reportedly plans to expand to home products, beauty, and fashion this month.

Time Stamped and AP Buyline share strikingly similar designs, layouts, and sensibilities. Their content is broadly informative but timid about making strong judgments or comparisons — an AP Buyline article about “The Best Capital One Credit Cards for 2024” heartily recommends nine of them. The writer credited for the article can also be found on Time Stamped writing about Chase credit cards, banks, and rental-car insurance. On both sites, if you look for it, you’ll also find a similar disclaimer. For Time: The information presented here is created independently from the TIME editorial staff. For the AP: AP Buyline’s content is created independently of The Associated Press newsroom. By independently, both companies mean that their product-recommendation sites are operated by a company called Taboola.

Over the years, Taboola, which is best understood as an advertising company, became a major player in affiliate marketing, too, through its acquisition of Skimlinks, a popular service for adding affiliate tags to content. In 2023, it started pitching a product called Taboola Turnkey Commerce, which claims to offer the benefits of starting a product-recommendation sub-brand minus the hassle of actually building an operation.

As her site has disappeared from view on Google, Navarro has been keeping an eye on popular search terms to see what’s showing up in its place. Legacy publishers seem to be part of Google’s plan, but a recent emphasis on what the company calls “perspectives” could also be in play. Reddit content is getting high placement as it contains a lot of conversations about products from actual customers and users. As its visibility in Google has increased, though, so has the prevalence of search-adjacent Reddit spam. Since the update has started rolling out, Navarro says, she has “seen a lot of generic review sites” getting ranked with credible-sounding names, .org domains, and content ripped straight from Amazon reviews.

“You can search all day and learn nothing,” she says. “It’s like trying to find information inside of Walmart.”

For now, Navarro is unimpressed with these AI experiments. “It’s just shut-up-and-buy,” she says — if you’re doing this search in the first place, you’re probably looking for a bit more information. In its emphasis on aggregation, its reliance on outside sources of authority, and its preference for positive comparison and recommendation over criticism, it also feels familiar: “Google is the affiliate site now.”

It's just a bit depressing to see how much it's all become a numbers game, whether those numbers are dollars in your pocket or followers on your Instagram. I'm probably saying nothing new to anybody who's been on the blogging scene for some time, but as a newcomer who's just here to write creatively and have fun, it was a stark reminder of how corporate the web has become. Why is that the end goal of blogging? Of writing? Just to make money and grow our followers? To increase our traffic so we can expose our visitors to 300 repetitive ads that take up their entire phone screen? To "convert" our readers into our customers, because them reading and enjoying what we have to say simply isn't enough? Personally, I want nothing to do with it. I'm sick of everything having to be a hustle now, even something personal like sharing our ramblings with strangers on the internet. I have little else to say other than that I hate how capitalism ruins everything fun it touches. I'll continue to write about things that make me feel passionate, not how to make money or gain followers.

Google is trying to kill the 10 blue links. Twitter is being abandoned to bots and blue ticks. There’s the junkification of Amazon and the enshittification of TikTok. Layoffs are gutting online media. A job posting looking for an “AI editor” expects “output of 200 to 250 articles per week.” ChatGPT is being used to generate whole spam sites. Etsy is flooded with “AI-generated junk.” Chatbots cite one another in a misinformation ouroboros. LinkedIn is using AI to stimulate tired users. Snapchat and Instagram hope bots will talk to you when your friends don’t. Redditors are staging blackouts. Stack Overflow mods are on strike. The Internet Archive is fighting off data scrapers, and “AI is tearing Wikipedia apart.”

it’s people who ultimately create the underlying data — whether that’s journalists picking up the phone and checking facts or Reddit users who have had exactly that battery issue with the new DeWalt cordless ratchet and are happy to tell you how they fixed it. By contrast, the information produced by AI language models and chatbots is often incorrect. The tricky thing is that when it’s wrong, it’s wrong in ways that are difficult to spot.

The resulting write-up is basic and predictable. (You can read it here.) It lists five companies, including Columbia, Salomon, and Merrell, along with bullet points that supposedly outline the pros and cons of their products. “Columbia is a well-known and reputable brand for outdoor gear and footwear,” we’re told. “Their waterproof shoes come in various styles” and “their prices are competitive in the market.” You might look at this and think it’s so trite as to be basically useless (and you’d be right), but the information is also subtly wrong.

It’s fluent but not grounded in real-world experience, and so it takes time and expertise to unpick.

it is a seemingly inevitable consequence arising from the combination of the ease of changing how a platform allocates value, combined with the nature of a "two sided market," where a platform sits between buyers and sellers, holding each hostage to the other, raking off an ever-larger share of the value that passes between them.

Today, Marketplace sellers are handing 45%+ of the sale price to Amazon in junk fees. The company's $31b "advertising" program is really a payola scheme that pits sellers against each other, forcing them to bid on the chance to be at the top of your search.

Search Amazon for "cat beds" and the entire first screen is ads, including ads for products Amazon cloned from its own sellers, putting them out of business (third parties have to pay 45% in junk fees to Amazon, but Amazon doesn't charge itself these fees).

This is enshittification: surpluses are first directed to users; then, once they're locked in, surpluses go to suppliers; then once they're locked in, the surplus is handed to shareholders and the platform becomes a useless pile of shit.

This made publications truly dependent on Facebook – their readers no longer visited the publications' websites, they just tuned into them on Facebook. The publications were hostage to those readers, who were hostage to each other. Facebook stopped showing readers the articles publications ran, tuning The Algorithm to suppress posts from publications unless they paid to "boost" their articles to the readers who had explicitly subscribed to them and asked Facebook to put them in their feeds.

Today, Facebook is terminally enshittified, a terrible place to be whether you're a user, a media company, or an advertiser. It's a company that deliberately demolished a huge fraction of the publishers it relied on, defrauding them into a "pivot to video" based on false claims of the popularity of video among Facebook users. Companies threw billions into the pivot, but the viewers never materialized, and media outlets folded in droves:

These videos go into Tiktok users' ForYou feeds, which Tiktok misleadingly describes as being populated by videos "ranked by an algorithm that predicts your interests based on your behavior in the app." In reality, For You is only sometimes composed of videos that Tiktok thinks will add value to your experience – the rest of the time, it's full of videos that Tiktok has inserted in order to make creators think that Tiktok is a great place to reach an audience.

"Sources told Forbes that TikTok has often used heating to court influencers and brands, enticing them into partnerships by inflating their videos’ view count.

"Monetize" is a terrible word that tacitly admits that there is no such thing as an "Attention Economy." You can't use attention as a medium of exchange. You can't use it as a store of value. You can't use it as a unit of account. Attention is like cryptocurrency: a worthless token that is only valuable to the extent that you can trick or coerce someone into parting with "fiat" currency in exchange for it.

For Tiktok, handing out free teddy-bears by "heating" the videos posted by skeptical performers and media companies is a way to convert them to true believers, getting them to push all their chips into the middle of the table, abandoning their efforts to build audiences on other platforms (it helps that Tiktok's format is distinctive, making it hard to repurpose videos for Tiktok to circulate on rival platforms).

every time Tiktok shows you a video you asked to see, it loses a chance to show you a video it wants you to se

I just handed Twitter $8 for Twitter Blue, because the company has strongly implied that it will only show the things I post to the people who asked to see them if I pay ransom money.

Compuserve could have "monetized" its own version of Caller ID by making you pay $2.99 extra to see the "From:" line on email before you opened the message – charging you to know who was speaking before you started listening – but they didn't.

Useful idiots on the right were tricked into thinking that the risk of Twitter mismanagement was "woke shadowbanning," whereby the things you said wouldn't reach the people who asked to hear them because Twitter's deep state didn't like your opinions. The real risk, of course, is that the things you say won't reach the people who asked to hear them because Twitter can make more money by enshittifying their feeds and charging you ransom for the privilege to be included in them.

Individual product managers, executives, and activist shareholders all give preference to quick returns at the cost of sustainability, and are in a race to see who can eat their seed-corn first. Enshittification has only lasted for as long as it has because the internet has devolved into "five giant websites, each filled with screenshots of the other four"

policymakers should focus on freedom of exit – the right to leave a sinking platform while continuing to stay connected to the communities that you left behind, enjoying the media and apps you bought, and preserving the data you created

technological self-determination is at odds with the natural imperatives of tech businesses. They make more money when they take away our freedom – our freedom to speak, to leave, to connect.

even Tiktok's critics grudgingly admitted that no matter how surveillant and creepy it was, it was really good at guessing what you wanted to see. But Tiktok couldn't resist the temptation to show you the things it wants you to see, rather than what you want to see.

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.

Every platform has its royalty. On Instagram it's influencers, foodies, and photographers. Twitter belongs to the founders, journalists, celebrities, and comedians. On LinkedIn, it’s hiring managers, recruiters, and business owners who hold power on the platform and have the ear of the people.

On a job site, they’re the provisioners of positions and never miss the chance to regale their audience with their professional deeds: hiring a teenager with no experience, giving a stressed single mother a chance to provide for her family, or seeing past a candidate’s imperfections to give them a once-in-a-lifetime opportunity. These stories are relayed dramatically in what’s now recognizable as LinkedIn-style storytelling, one spaced sentence at a time, told by job-givers with a savior complex.