Just like we trained on human language to create LLMs, we can train on human keystrokes with a similar algorithm and spit out believable (at least statistically) "human" keystrokes generated by machine.
Yeah I think the "how can you prove text was handwritten" question is a subset of the larger "how can you prove that a computer is being driven by a human" problem that all of the work around captcha, attestations, biometrics, and government-id auth has been aimed at. The fundamental issue, it seems to me, is that any signal that a human can provide to a computer (keystroke, camera frame, mouse click, etc) is inherently only parsable by code because a sensor has translated the analog signal into a digital one. That same requirement also ensures that the input can be digitally spoofed or automated. There's a similar problem on the output side: how can an analog user trust a digital certificate? What's stopping me from copying the certificate HTML or taking a screenshot and using it to trick people into thinking my AI content is handwritten?
I don't have any suggestions. I worry that the only strong solutions require a lot of power to be given to a centralized authority.
> One could work around Semoi by, for example, typing out a bunch of gibberish, leaving their editor open, and then pasting in an LLM generated texting and minting the proof. To which I would respond: why? That’s really pathetic.
Except quite oddly, virtually no one has collected precise keystroke information or if they have it certainly is not public. I genuinely wonder if such a dataset exists