Technology is progressing to the point where it is getting increasingly harder to tell if someone is a bot or a human. LessWrong ironically uses LLM tools to tell LLMs apart from humans. On the internet nobody knows if you are a dog, or a LLM-inspired human. This is nothing new: David Chaum published "Security without Identification: Transaction Systems to Make Big Brother Obsolete" in 1985 to argue that we should build identity systems without actually learning who someone is — to which the internet responded by collectively using username+passwords to build account identities, then got surprise-Pikachu'ed when bots fought through anyway via Sybil attacks.
The present situation is that the Internet is actively hostile towards good actors (presumed to be humans at this point) through a combination of CAPTCHAs, accounts requiring logging in via your email and your mom's birthday, or 2FA that requires a trusted third party (often mega-corporations) to escort you into the website, all while being friendly to automation through unofficial APIs or web scraping. Computer use in LLMs has largely slammed the door shut on traditional methods of preventing bots.
The other approach that largely turned out to be security theater was Anubis, which proudly proclaimed itself the watchdog of the internet, weigher of souls, but in the words of its creator "Over time I thought the proof-of-work was actually doing something for security, but no — any barrier makes the low-effort scrapers confused and give up." Really, the rapid FOSS adoption (200k downloads to date) has largely just rehashed Hashcash and propagated anime cat girls throughout the internet, besides actively calling out Mozilla as the benevolent god of bots (except that it is not only trivial to bypass, it ignores curl
). As it turns out, the more valuable your website, the higher the floor of computation you need to use, but at some point you have to pay latency debts back, so you have a ceiling where this works out. People abandoned Hashcash for good reason, it burdens legitimate users while doing nothing to bots who wants to squeeze you for value and provide nothing back.
The mistake here is largely treating bots (or "clankers" in the ongoing debate between boomers and clankers that's also indicative of the entire misguided approach to this) as "all bad" and humans as "all good". Bots are a tool that are driven by other humans to leech off your website. I also hate the contrived name "clanker" when we have a perfectly good name for irresponsible agents: bots, which is short, catchy, and has been in use for a long time.
What we want are really to filter bad from good agents (AI or humans alike) with a third party "substrate" that is independent of our ability to think (as you can see, trying to split AI from humans via the capability and capacity to think has largely ended up in spectacular failure and a total waste of time and resources).
And we already have it. It is called time.
For example, it is perfectly acceptable to be suspicious of someone who has moved into your neighbourhood, and similar that person would be suspicious of others in the neighbourhood. It would be weird, in fact, if that person acted overly friendly to people, and vice versa. However, as time passes with normal-to-positive interactions between both parties, respect is earned between both parties, more trust is allocated, and thus more openings, more information is available. Hacker News works the same way: a new account can't downvote or flag until it has earned karma because privileges accrue with proven history, not at signup. Time is the passive, all-knowing, self-historical substrate we can operate trust on.
This is just common sense we can apply here, and that is what I am doing with Continuity Auth: treat all newcomers as suspect, and identify them via patterns, not names. This is Chaum's 1985 thesis applied to the rate-limiter (security without identification), instead of the attester model his blind-signature lineage grew into (Privacy Pass, Apple's Private Access Tokens), where a third party vouches for you. Here there is no attester and no web-of-trust to concentrate power in a mega-corporation: trust is built directly between you and the service by behaving consistently over time.
More importantly, this raises the cost of bot farms by making Sybil attacks uneconomical: genuine users (human or AI) engaging in good faith will happily wait for time to pass, while bot farms must maximise value-per-compute or they lose money, so "sit still and behave for two weeks" is the one cost they can't parallelize away.
In continuity-auth, I provide a multi-tier model: the more identity you provide, the higher the initial trust afforded, but you still join a time-gated suspect test until you are time-proven to be a good actor.
The trust signal itself borrows from my exploration in succession of how human memory "actually works". We treat historical writings with much more weight than what has happened recently, especially when said writings have recent analogues. Instead of rewarding whoever shows up the most, we reward whoever stayed the longest, by weighing spaced recurrence over massed frequency. Volume is cheap to manufacture, calendar time is not, which is exactly the asymmetry a bot farm cannot buy its way out of.
Real alignment begins between humans and LLMs when we build for good actors, not make grand claims that are time-proven to be wrong, time and time again.