If it turns out that evaluation of alignment proposals is not easier than generation, we’re in pretty big trouble because we’ll struggle to convince others that any good alignment proposals humans come up with are worth implementing.
But this is pretty likely the case though, isn’t it? Actually I think by default the situation will be the opposite: it will be too easy to convince others that some alignment proposal is worth implementing, because humans are in general too easily convinced by informal arguments that look good but contain hidden flaws (and formalizing the arguments is both very difficult and doesn’t help much because you’re still depending on informal arguments for why the formalized theoretical concepts correspond well enough to the pre-theoretical concepts that we actually care about). Look at the history of philosophy, or cryptography, if you doubt this.
But suppose we’re able to convince people to distrust their intuitive sense of how good an argument is, and to keep look for hidden flaws and counterarguments (which might have their own hidden flaws and so on). Well how do we know when it’s safe to end this process and actually hit the run button?
It feels to me like there’s basically no question that recognizing good cryptosystems is easier than generating them. And recognizing attacks on cryptosystems is easier than coming up with attacks (even if they work by exploiting holes in the formalisms). And recognizing good abstract arguments for why formalisms are inadequate is easier than generating them. And recognizing good formalisms is easier than generating them.
This is all true notwithstanding the fact that we often make mistakes. (Though as we’ve discussed before, I think that a lot of the examples you point to in cryptography are cases where there were pretty obvious gaps in formalisms or possible improvements in systems, and those would have motivated a search for better alternatives if doing so was cheap with AI labor.)
The example of cryptography was mainly intended to make the point that humans are by default too credulous when it comes to informal arguments. But consider your statement:
It feels to me like there’s basically no question that recognizing good cryptosystems is easier than generating them.
Consider some cryptosystem widely considered to be secure, like AES. How much time did humanity spend on learning / figuring out how to recognize good cryptosystems (e.g. finding all the attacks one has to worry about, like differential cryptanalysis), versus specifically generating AES with the background knowledge in mind? Maybe the latter is on the order of 10% of the former?
Then consider that we don’t actually know that AES is secure, because we don’t know all the possible attacks and we don’t know how to prove it secure, i.e., we don’t know how to recognize a good cryptosystem. Suppose one day we figure that out, wouldn’t finding an actually good cryptosystem be trivial at that point compared to all the previous effort?
Some of your other points are valid, I think, but cryptography is just easier than alignment (don’t have time to say more as my flight is about to take off), and philosophy is perhaps a better analogy for the more general point.
But this is pretty likely the case though, isn’t it? Actually I think by default the situation will be the opposite: it will be too easy to convince others that some alignment proposal is worth implementing, because humans are in general too easily convinced by informal arguments that look good but contain hidden flaws (and formalizing the arguments is both very difficult and doesn’t help much because you’re still depending on informal arguments for why the formalized theoretical concepts correspond well enough to the pre-theoretical concepts that we actually care about). Look at the history of philosophy, or cryptography, if you doubt this.
But suppose we’re able to convince people to distrust their intuitive sense of how good an argument is, and to keep look for hidden flaws and counterarguments (which might have their own hidden flaws and so on). Well how do we know when it’s safe to end this process and actually hit the run button?
It feels to me like there’s basically no question that recognizing good cryptosystems is easier than generating them. And recognizing attacks on cryptosystems is easier than coming up with attacks (even if they work by exploiting holes in the formalisms). And recognizing good abstract arguments for why formalisms are inadequate is easier than generating them. And recognizing good formalisms is easier than generating them.
This is all true notwithstanding the fact that we often make mistakes. (Though as we’ve discussed before, I think that a lot of the examples you point to in cryptography are cases where there were pretty obvious gaps in formalisms or possible improvements in systems, and those would have motivated a search for better alternatives if doing so was cheap with AI labor.)
The example of cryptography was mainly intended to make the point that humans are by default too credulous when it comes to informal arguments. But consider your statement:
Consider some cryptosystem widely considered to be secure, like AES. How much time did humanity spend on learning / figuring out how to recognize good cryptosystems (e.g. finding all the attacks one has to worry about, like differential cryptanalysis), versus specifically generating AES with the background knowledge in mind? Maybe the latter is on the order of 10% of the former?
Then consider that we don’t actually know that AES is secure, because we don’t know all the possible attacks and we don’t know how to prove it secure, i.e., we don’t know how to recognize a good cryptosystem. Suppose one day we figure that out, wouldn’t finding an actually good cryptosystem be trivial at that point compared to all the previous effort?
Some of your other points are valid, I think, but cryptography is just easier than alignment (don’t have time to say more as my flight is about to take off), and philosophy is perhaps a better analogy for the more general point.