AI can cheaply fake almost every signal we traditionally used to judge quality. I now see this pattern everywhere, in open source, in education, in research, all breaking at the same time. I find signaling theory useful for diagnosing what is happening and why it is so disorienting, and signaling theory and adjacent literature can provide the vocabulary to discuss possible solutions.
I don’t entirely agree with the doom and gloom of that article. Humans are particularly good at adapting to changes. And humans are particularly good at detecting patterns and anti-patterns. Patterns are signals, and while adaption will take a while and will be painful, I think we’ll work it out. For example, detecting AI slop reliably and intuitively is a skill that more and more people learn. Once the pattern is learnt, it’s a new useful signal. Other new signals emerge for quality detection. In a world of crap software, the few that work well will stand out. Anything that can be “created” by anyone with a few prompts loses its value. What’s valuable will be what stands out from the slop.