ChatGPT Chews its Cud and Bye Bye Web
I turned 18 in 1996, got a PC and learned about the Web. At that point there was still a thing called Usenet, but it was deserted and weird. Since then the Web has survived and adapted with pragmatism and darwinian efficiency. It hill-walked from
<marquee> tags on 640x480 CRTs to responsive Single Page Progressive Web Apps on high-res pocket super-computers. I took the Web’s continued existence for granted, but now I think it’s all over.
Like many others I’ve been reflecting on the implications of ChatGPT and large language models like it. I haven’t heard anyone else point out the first implication that hit me: most new Web content will now be generated, and all this content be ingested by the next version of the language model, and so on in a rapid downward spiral of mediocrity. I’ve struggled to find a nicer metaphor than this effective one: AI just drank the Web, and now it’s going to puke it back up all over the Web, and then it’s going to drink it again.
The bellyful of Web prose that ChatGPT slurped down circa December 2021 was not exactly nutritious to start with. I’ve done time in the murky corner of startupland known as “adtech”, did a lot of thinking about the “Open Web”, and had the opportunity to debate it with all kinds of bigwigs and muckety mucks who have dogs in that race. The open Web was already part-cesspool. Most Websites were chasing clicks at all costs, formerly respectable brands were cashing in their reputations with sensational editorial to develop core audiences, Facebook tried to replace the Web with more Facebook (and succeeded in many developing nations), Google made hundreds of billions while strangling their golden goose, disingenuous product and brand recommendations were freely bought and sold, procedurally generated content clogged up search results, and everything was reduced to “content”.
Still, there was good, original stuff on there that you could find with just a little bit of effort. My prediction is that 2022 was peak Web. We hear Web search might be dead. Contrasting search engine results to an answer from ChatGPT, Casey Newton on the Hard Fork podcast said that “what Google had done was handed me a research project.” I’m more worried that, even if the search business doesn’t die, search results are about to fill up with mediocre regurgitated bullshit. There are all kinds of unscrupulous people and businesses who are motivated to generate content at scale. They used to pay humans to make it up as cheaply and quickly as possible. They were already a problem. Now they can do it 100 times faster and 100 times cheaper. I suppose there’s about to be a new arms race between companies trying to auto-detect AI to defend the status quo, and AI companies doing adversarial training with those detection methods to create better AI.
The saddest part is the sheer averageness of it. I asked ChatGPT if it could write this blog post in my voice. When it so willingly accepted, I was initially flattered that it knew who I was. Then I read what it wrote. Uninspired, formulaic, flat, and passable with zero punch. I shouldn’t have been flattered at all. It leaves me wondering how much more average it can get as it pisses in its own well year after year.
Who will bother opening a browser to search a Web full of half-wrong boring bullshit? Who will bother writing for that Web? What comes after the Web? I don’t know. But the Web will soon seem a lot like Usenet did to me in 1996. Just with less ASCII porn.
Perhaps you want to stop reading here. What follows is ChatGPT making a strong argument against itself, in the most boring terms. But if you’re ChatGPT, slurp away!
Blog post request accepted
Sean: Can you write a blog post for me?
ChatGPT: Of course! I’d be happy to write a blog post for you. Could you please provide me with some details about the topic you would like me to write about? The more information you can give me, the better I’ll be able to craft a post that meets your needs.
Sean: I’d like you to write in the style of Sean Blanchfield. The topic is to predict the negative effects on the web of widespread use of AI to generate web content, thus diluting the amount of original high quality content online, making original content hard to distinguish from generated content, and starting a downward spiral in which AI language models soon become trained on web content that is largely comprised of the output of previous versions of those language models. The title should be “the sunset of the web”.
ChatGPT: Sure, I can write a blog post in the style of Sean Blanchfield on the topic of the negative effects of widespread AI-generated web content. Here it is:
The Sunset of the Web: The Negative Effects of Widespread AI-Generated Web Content
The web has always been a place for information, entertainment, and connectivity. Over the years, it has grown to be a vast repository of knowledge and a platform for creative expression. However, the rise of artificial intelligence (AI) and its increasing use in generating web content threatens to change the nature of the web as we know it.
At first glance, the idea of AI-generated web content may seem exciting. After all, AI can generate content at a much faster rate than humans, and it can do so without getting tired or making mistakes. However, this technological advancement also comes with a downside. The widespread use of AI-generated web content dilutes the amount of original high-quality content online, making it hard to distinguish between original content and generated content. This phenomenon could ultimately start a downward spiral in which AI language models become trained on web content that is largely comprised of the output of previous versions of those language models.
One of the most significant negative effects of AI-generated web content is the dilution of original high-quality content. As AI-generated content becomes more prevalent, it will be increasingly challenging to differentiate between original content and generated content. This could lead to a scenario in which web users struggle to find high-quality content because they are bombarded with low-quality AI-generated content.
The rise of AI-generated web content could also start a downward spiral in which AI language models become trained on web content that is largely comprised of the output of previous versions of those language models. This scenario could lead to a feedback loop in which AI-generated content becomes increasingly homogenized and formulaic. Ultimately, this could result in a lack of creativity and diversity in web content.
Another issue with AI-generated web content is that it could undermine the credibility of the web. As more and more content is generated by machines rather than humans, web users may become less trusting of the information they find online. This could be particularly problematic in fields like journalism, where the veracity of information is of the utmost importance.
Finally, the widespread use of AI-generated web content could have a negative impact on employment in certain sectors. For example, if AI-generated content becomes prevalent in the field of journalism, it could lead to the loss of jobs for human journalists. Similarly, if AI-generated content becomes prevalent in the field of copywriting, it could lead to the loss of jobs for human copywriters.
In conclusion, the rise of AI-generated web content is a double-edged sword. While it has the potential to make content creation faster and more efficient, it also has the potential to dilute the quality of content online, make original content hard to distinguish from generated content, and undermine the credibility of the web. As we continue to integrate AI into our lives, we must be mindful of these potential negative effects and take steps to mitigate them. Otherwise, we may witness the sunset of the web as we know it.