| ▲ | stymaar 3 hours ago | |||||||||||||||||||||||||
> The first is that it would still misclassify human-authored text written under the same incentive, and most people have various incentives to "maximize engagement". The thing is, humans are significantly worse at maximizing numerical goals than computers. > And the second is that then people would just make other models that are tuned for defeating that sort of classifier, which would be used whenever the classifier is being used. Anyone can already do that right now, just grab unsloth studio and fine-tune your local Gemma, but nobody cares. People posting slop content don't care if pangram or I flag their slop with certainty, they are using the easiest option, which is commercial chat models. And given this segment of user doesn't care, the provider have zero incentive to provide a dedicated stealth model for that purpose. | ||||||||||||||||||||||||||
| ▲ | AnthonyMouse 3 hours ago | parent | next [-] | |||||||||||||||||||||||||
> The thing is, humans are significantly worse at maximizing numerical goals than computers. I'm not sure this is even the right premise. Existing LLMs try to maximize engagement, and they often write in a particular style that has tells, but these two things are not necessarily related. Over-using em-dash or whatever isn't the thing that maximizes engagement. So the two problems really are, what happens to the actual humans whose writing style is a close match for what a given generation of LLMs output? And, what stops LLMs from using a different style when someone wants to fool the classifier? > People posting slop content don't care if pangram or I flag their slop with certainty, they are using the easiest option, which is commercial chat models. They don't care as long as the consequences of identifying it are immaterial, but in that case what's the point of classifying it? Whereas if they need to fool the classifier some threshold percentage of the time in order for enough of their spam to get through, they're going to care. | ||||||||||||||||||||||||||
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| ▲ | pixl97 3 hours ago | parent | prev [-] | |||||||||||||||||||||||||
I mean, back when I was spam filtering setting up a simple Bayesian classifier was easy. Train it on your spam and ham and it worked damned good. "Mission Accomplished".... until it wasn't. Spam rates started climbing and it started getting harder than ever to filter them. There is always an incentive to get spam to bypass filters, so as your filters increase in accuracy, those attempting to pass said filters adjust their behaviors. Spammers/cheaters/whateverers will at least just use a second pass filter that uses one of these 'ai scoring' systems to beat said AI scoring systems. So while it's worthwhile to do it at this moment, this window will rapidly close. | ||||||||||||||||||||||||||
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