Sorry, didn't mean to call you personally any of those adjectives :)
None taken then.
Pretty much, yes, I find it totally possible. I am not saying that I am confident that this is the case, just that I find it more likely than the alternative, which would require an additional reason why it isn't so.
Well, tell me what you think of this argument:
Lets divide the meta-language into two sets: P (the sentences that cannot be rendered in English) and Q (the sentences that can). If you expect Q to be empty, then let me know and we can talk about that case. But let's assume for now that Q is not empty, since I assume we both think that an AGI will be able to handle human language quite easily. Q is, for all intents and purposes, a 'human' language itself.
Premise one is that that translation is transitive: if I can translate language a into language b, and language b into language c, then I can translate language a into language c (maybe I need to use language b as an intermediate step, though).
Premise two: If I cannot translate a sentence in language a into an expression in language b, then there is no expression in language b that expresses the same thought as that sentence in language a.
Premise three: Any AGI would have to learn language originally from us, and thereafter either from us or from previous versions of itself.
So by stipulation, every sentence in Q can be rendered in English, and Q is non-empty. If any sentence in P cannot be rendered in English, then it follows from premise one that sentences in P cannot be rendered in sentences in Q (since then they could thereby be rendered into English). It also follows, if you accept premise two, that Q cannot express any sentence in P. So an AGI knowing only Q could never learn to express any sentence in P, since if it could, any speaker of Q (potentially any non-improved human) could in principle learn to express sentences in P (given an arbitrarily large amount of resources like time, questions and answers, etc.).
Hence, no AGI, beginning from a language like English could go on to learn how to express any sentence in P. Therefore no AGI will ever know P.
I'm not super confident this argument is sound, but it seems to me to be at least plausible.
If you agree with Eliezer's definition of intelligence as optimization power
Well, that's a fine definition, but it's tricky in this case. Because if intelligence is optimization power, and optimizing presupposes something to optimize, then intelligence (on that definition) isn't strictly a factor in (ultimate) goal formation. If that's right, than something's being much more intelligent would (as I think someone else mentioned) just lead to very hard to understand instrumental goals. It would have no direct relationship with terminal goals.
Premise one is false assuming finite memory.
Premise 3 does not hold well either; Many new words come from pointing out a pattern in the environment, not from defining in terms of previous words.
AI risk
Bullet points
Executive summary
The risks from artificial intelligence (AI) in no way resemble the popular image of the Terminator. That fictional mechanical monster is distinguished by many features – strength, armour, implacability, indestructability – but extreme intelligence isn’t one of them. And it is precisely extreme intelligence that would give an AI its power, and hence make it dangerous.
The human brain is not much bigger than that of a chimpanzee. And yet those extra neurons account for the difference of outcomes between the two species: between a population of a few hundred thousand and basic wooden tools, versus a population of several billion and heavy industry. The human brain has allowed us to spread across the surface of the world, land on the moon, develop nuclear weapons, and coordinate to form effective groups with millions of members. It has granted us such power over the natural world that the survival of many other species is no longer determined by their own efforts, but by preservation decisions made by humans.
In the last sixty years, human intelligence has been further augmented by automation: by computers and programmes of steadily increasing ability. These have taken over tasks formerly performed by the human brain, from multiplication through weather modelling to driving cars. The powers and abilities of our species have increased steadily as computers have extended our intelligence in this way. There are great uncertainties over the timeline, but future AIs could reach human intelligence and beyond. If so, should we expect their power to follow the same trend? When the AI’s intelligence is as beyond us as we are beyond chimpanzees, would it dominate us as thoroughly as we dominate the great apes?
There are more direct reasons to suspect that a true AI would be both smart and powerful. When computers gain the ability to perform tasks at the human level, they tend to very quickly become much better than us. No-one today would think it sensible to pit the best human mind again a cheap pocket calculator in a contest of long division. Human versus computer chess matches ceased to be interesting a decade ago. Computers bring relentless focus, patience, processing speed, and memory: once their software becomes advanced enough to compete equally with humans, these features often ensure that they swiftly become much better than any human, with increasing computer power further widening the gap.
The AI could also make use of its unique, non-human architecture. If it existed as pure software, it could copy itself many times, training each copy at accelerated computer speed, and network those copies together (creating a kind of “super-committee” of the AI equivalents of, say, Edison, Bill Clinton, Plato, Einstein, Caesar, Spielberg, Ford, Steve Jobs, Buddha, Napoleon and other humans superlative in their respective skill-sets). It could continue copying itself without limit, creating millions or billions of copies, if it needed large numbers of brains to brute-force a solution to any particular problem.
Our society is setup to magnify the potential of such an entity, providing many routes to great power. If it could predict the stock market efficiently, it could accumulate vast wealth. If it was efficient at advice and social manipulation, it could create a personal assistant for every human being, manipulating the planet one human at a time. It could also replace almost every worker in the service sector. If it was efficient at running economies, it could offer its services doing so, gradually making us completely dependent on it. If it was skilled at hacking, it could take over most of the world’s computers and copy itself into them, using them to continue further hacking and computer takeover (and, incidentally, making itself almost impossible to destroy). The paths from AI intelligence to great AI power are many and varied, and it isn’t hard to imagine new ones.
Of course, simply because an AI could be extremely powerful, does not mean that it need be dangerous: its goals need not be negative. But most goals become dangerous when an AI becomes powerful. Consider a spam filter that became intelligent. Its task is to cut down on the number of spam messages that people receive. With great power, one solution to this requirement is to arrange to have all spammers killed. Or to shut down the internet. Or to have everyone killed. Or imagine an AI dedicated to increasing human happiness, as measured by the results of surveys, or by some biochemical marker in their brain. The most efficient way of doing this is to publicly execute anyone who marks themselves as unhappy on their survey, or to forcibly inject everyone with that biochemical marker.
This is a general feature of AI motivations: goals that seem safe for a weak or controlled AI, can lead to extremely pathological behaviour if the AI becomes powerful. As the AI gains in power, it becomes more and more important that its goals be fully compatible with human flourishing, or the AI could enact a pathological solution rather than one that we intended. Humans don’t expect this kind of behaviour, because our goals include a lot of implicit information, and we take “filter out the spam” to include “and don’t kill everyone in the world”, without having to articulate it. But the AI might be an extremely alien mind: we cannot anthropomorphise it, or expect it to interpret things the way we would. We have to articulate all the implicit limitations. Which may mean coming up with a solution to, say, human value and flourishing – a task philosophers have been failing at for millennia – and cast it unambiguously and without error into computer code.
Note that the AI may have a perfect understanding that when we programmed in “filter out the spam”, we implicitly meant “don’t kill everyone in the world”. But the AI has no motivation to go along with the spirit of the law: its goals are the letter only, the bit we actually programmed into it. Another worrying feature is that the AI would be motivated to hide its pathological tendencies as long as it is weak, and assure us that all was well, through anything it says or does. This is because it will never be able to achieve its goals if it is turned off, so it must lie and play nice to get anywhere. Only when we can no longer control it, would it be willing to act openly on its true goals – we can but hope these turn out safe.
It is not certain that AIs could become so powerful, nor is it certain that a powerful AI would become dangerous. Nevertheless, the probabilities of both are high enough that the risk cannot be dismissed. The main focus of AI research today is creating an AI; much more work needs to be done on creating it safely. Some are already working on this problem (such as the Future of Humanity Institute and the Machine Intelligence Research Institute), but a lot remains to be done, both at the design and at the policy level.