Our main argument is that outputs will become increasingly indistinguishable, but the processes won't. E.g. in 5 years if you watch an AI book a flight it will do it in a very non-human way, even if it gets the same flight you yourself would book.
I find myself wondering why Google isn't doing as good a job as you guys. In particular, I'm wondering if you think they've been kind of lazy about the problem because they don't see captcha detection as faring particularly poorly, and perhaps once AI agents really start taking off and becoming prevalent, then Google will buckle down, at which point they'll be able to hone their troves of data to build a newer captcha even better than yours. Or is there an additional secret sauce you guys have?
That kind of leads me to my other question-I assume your secret sauce is the cognitive science, stroop-esque approach to bot detection (which I think is brilliant in the abstract). But I'm curious how that scales. Like, do you go one-by-one for each website you have a partnership with and figure out how a human would likely use the site, or do you use general techniques (besides the obvious ones like typing speed and mouse movements, which almost certainly Google could implement too if it decided to buckle down). Like, can you scale some broad stroop task across websites?
By the way, asking all of this out of admiration. You guys are doing really clever work!
> in 5 years if you watch an AI book a flight it will do it in a very non-human way
I would bet completely against this, models are becoming more human-like, not less, over time.
What's more likely to change (that would cause a difference) is the work itself changing to adapt to areas where models are already super-human, such as being able to read entire novels in seconds with full attention.
If the observable behavior (output) becomes indistinguishable (which I’m doubtful of), what does it matter that the internal process is different? Surely only to the extent that the behavior still exhibits differences after all?
