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> Published content will be later used to train subsequent models, and being able to distinguish AI from human input may be very valuable going forward<p>I find this to be a particularly interesting problem in this whole debacle.<p>Could we end up having AI quality trend downwards due to AI ingesting its own old outputs and reinforcing bad habits? I think it's a particular risk for text generation.<p>I've already run into scenarios where ChatGPT generated code that looked perfectly plausible, except for that the actual API used didn't really exist.<p>Now imagine a myriad fake blogs using ChatGPT under the hood to generate blog entries explaining how to solve often wanted problems, and that then being spidered and fed into ChatGPT 2.0. Such things could end up creating a downwards trend in quality, as more and more of such junk gets posted, absorbed into the model and amplified further.<p>I think image generation should be less vulnerable to this since all images need tagging to be useful, "ai generated" is a common tag that can be used to exclude reingesting old outputs, and also because with artwork precision doesn't matter so much. If people like the results, then it doesn't matter that much that something isn't drawn realistically.