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Superintelligence: The Idea That Eats Smart People (2016)

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Re: Superintelligence: The Idea That Eats Smart People (2016)

#212
post #79

What really terrified me wasn't skynet or Hal, but what Charles Stross describes in his novel Accelerando. Basically, machine controlled businesses (“slyly self-aware financial instruments”) evolving to the point where their aptitude at understanding and manipulating economics eclipses anything a human can compete with. It terrified me because there is efficiency incentive for the buying/selling of goods and services…

Have a look at Aragon[1], it has good funding in their ICO run (and this was when ETH was in the 100's last year). [1] https://aragon.org/

I don't know why you were down voted... Decentralized Autonomous Organizations are exactly this

Re: Superintelligence: The Idea That Eats Smart People (2016)

#213
post #21

Earlier quoted context omitted.

So you agree there is room for them to work on this, yet you feel they are making engineers generally look like cultists? Maybe you’re just being oversensitive. The hype wave on AI danger is completely over, and there’s nothing wrong with people studying the question if that’s their interest.

You know we've been here before, right? I mean, lighthill report, Ray Kurzeweil is a serial offender for over thirty years, the singularity is around the corner thing, outrageous claims for fMRI, self driving cars. Over hyped ibm Watson which now health professions are talking about misdiagnosis problems. Sure. We have google image match and better colorisartion and some improvements in language processing, and good…

Ray Kurzweil was never part of AI danger-hype

Re: Superintelligence: The Idea That Eats Smart People (2016)

#214
post #185

>What I find particularly suspect is the idea that "intelligence" is like CPU speed, in that any sufficiently smart entity can emulate less intelligent beings (like its human creators) no matter how different their mental architecture. >With no way to define intelligence (except just pointing to ourselves), we don't even know if it's a quantity that can be maximized. For all we know, human-level intelligence could be…

But humans are the dumbest possible animal capable of creating a technological civilization. If we weren't, then our dumber ancestors would have done so.

I think this line of reasoning subtly assumes mind-body dualism[1]. Intelligence is necessary but not sufficient for the creation of technological civilization. Dolphins and other cetaceans are an example incredibly smart creatures that lack the necessary lifestyle and opposable thumbs to create technology. Octopi are likewise excellent problem solvers whose technological ambitions are thwarted by a very short lifespan and a generally solitary nature.

Human technology is at the crossroads of the right physical attributes mixed with the right kind of intelligence and subjected to the right kind of evolutionary pressures. There may be (or may have been) creatures with more "raw" intelligence that cannot be applied to the development of technology because one of the other factors is missing.

[1] https://en.wikipedia.org/wiki/Mind–body_dualism

Re: Superintelligence: The Idea That Eats Smart People (2016)

#215
I really liked this. I think the author does a good job of steelmanning the AI alignment argument, and providing interesting food for thought on the subject.

Here's my responses to the arguments (since you didn't ask, and who cares what I think):

Argument from Wooly Definitions:

This isn't really an argument against, but just a "Maybe it's not a problem.". I think both Bostrom and Yudkowsky have said it's totally possible it's not a problem. The question is what probability you assign to "maybe intelligence can't be maximized to a problematic degree". There's not a lot of reason to assign a huge probability to that scenario. Even speeding up a 1-1 copy of a human brain to computer-speeds instead of synapse-speeds gets us into scary territory.

Argument from Stephen Hawking's Cat:

This one is more persuasive. It's essentially saying maybe the gap between human intelligence and "can trivially simulate human intelligence" is a really huge gap. The question kind of hinges on whether recursive self-improvement peters out at some point with the AI in the "Human to Cat" IQ gap, or whether it peters out somewhere in the "Human to Nematode" IQ gap, where we can almost simulate their brains entirely, and can certainly understand their motivations well enough to manipulate them. Again, we have a question of likelihood, and then we have to do the expected utility calculation (i.e. your estimated likelihood of the Human-Cat gap being the result has to be very small to offset the negative utility of complete annihilation).

Argument from Einstein's Cat:

This is essentially the same argument as above, but with force. The implication is that the cat is going to scratch the hell out of the human who forcibly tries to put it in a box. One element here I didn't address above is that the equivalent scenario isn't one human putting one cat who doesn't want to go into a box. The equivalent is one human trying to convince any cat anywhere by tricks, cajoling, petting, feeding into a box. That is, the AI just has to trick one human at some point into letting it onto the internet, etc. A human is totally capable of telling when it's going to get scratched and will know to avoid that cat and find another.

The Argument from Emus:

If you read the wiki page on the emu war, it looks like "only a few were killed" because of political pressure causing the army to quit after a few days of running into a little bit of trouble. Then the australian government instituted a bounty system, and wouldn't you know it, sufficiently motivated humans brought in 57,000 emus for bounties. This is an anecdote, not a strong argument, but it isn't a very reassuring anecdote. Maybe a few very determined humans would survive an AI onslaught? That doesn't seem like a conclusion I'd put into the "don't worry about it" bucket.

The Argument From Slavic Pessimism:

The author is arguing it will be very hard to align AI goals with human goals and we'll probably fuck it up even if we try really hard. I think everyone is in agreement on this one. But of course this is an argument for AI alarmism, not against it.

Argument from Complex Motivations:

I don't think the author seriously engaged with the orthogonality thesis, other than to just say "I don't believe it". Shruggy?

The Argument from Actual AI:

This boils down to arguing that the AI apocalypse isn't happening this year. I agree. Given how quickly very easy to use and flexible frameworks like PyTorch and Tensorflow emerged that allow even amateurs to implement bleeding edge techniques from the latest papers, I'm not super hopeful that "It's hard and our AI is bad" will continue to be the case for decades to come.

The Argument from My Roommate:

The author's roommate has a lot of competing evolutionary drives. Some of them say to conserve energy if there's no direct threat. Put another way: the paperclip maximizer might have a secondary goal of chilling out if it doesn't seem like any more paperclips are achievable at the moment. Still not a win for humans, just maybe the PM won't try venturing into space.

Argument from Brain Surgery:

It's pretty common to do brain surgery even on neural networks we have now. Train up a network on imagenet, rip off the top few layers, and retrain them for some new problem. Fundamentally, software and hardware designed by humans is much more understandable and decomposable than a human brain is (and we have no ethical qualms about doing crazy experiments on them, which hinders our ability to understand our own brains in vivo). It's true though that at present, deep neural networks operate in ways we don't understand and are hard to disentangle. Maybe that's fundamental to true intelligence, but probably not.

The argument from Childhood:

Understanding the real world requires spending real time, and that precludes hyper-explosive growth. This is true, and is a good reason to down-weight an intelligence explosion scenario. But we have good reason to think that it doesn't preclude it. There is a lot of work from OpenAI where a computer is trained up very quickly in simulation, then needs a very small amount of time in the real world to compensate for the differences between simulation and reality.

The Argument from Gilligan's Island:

It's a good point that humans' intelligence is dispersed, and that individually we aren't anywhere near as capable. AI has a particular advantage over us in this capacity: it can distribute its intelligence over multiple machines, but encounter non of the trust and incentive misalignments that humans must contend with when cooperating. I'd put this squarely in the "+1 for AI alarmists" bucket: we're handicapped in a way machines trivially aren't. It will be that much harder for us if an AI is misaligned.

Outside arguments:

All of these boil down to pattern matching. "Only nerds worry about this stuff. People who believe in this are megalomaniacs who place too much importance on themselves..." etc etc. These are weak arguments, and there are just as many weak anecdotal counterexamples where a person was worrying about something weird, and they turned out to be right. That weird person's name? Einstein.

Overall impression:

If I aggregate the strongest points from this talk, I'd probably phrase it something like:

"Maybe there are diminishing returns to greater levels of intelligence, and humans are smart enough now that even exponentially more intelligent AIs will not be able to wipe us out completely."

That's possible! We should probably at least spend some time thinking about what happens if that's not the case.

Re: Superintelligence: The Idea That Eats Smart People (2016)

#216

Earlier quoted context omitted.

But humans are the dumbest possible animal capable of creating a technological civilization. If we weren't, then our dumber ancestors would have done so.

I think this line of reasoning subtly assumes mind-body dualism[1]. Intelligence is necessary but not sufficient for the creation of technological civilization. Dolphins and other cetaceans are an example incredibly smart creatures that lack the necessary lifestyle and opposable thumbs to create technology. Octopi are likewise excellent problem solvers whose technological ambitions are thwarted by a very short lifesp…

Sure, but we evolved to live on land, and opposable thumbs, far before we developed civilization. Meanwhile, cranial volume continued to expand long after e.g. thumbs.

I think the parent comment holds.

Re: Superintelligence: The Idea That Eats Smart People (2016)

#217
post #186

Earlier quoted context omitted.

For instance, go to the bottom of page 8 and see this: > Thus to deny the Orthogonality thesis is to assert that there is a goal system G, such that, among other things: > 1. There cannot exist any efficient real-world algorithm with goal G. > 2. If a being with arbitrarily high resources, intelligence, time and goal G, were to try design an efficient real-world algorithm with the same goal, it must fail. > ...4. If…

The OP's point is: 1. The "superintelligence" crowd are capable of making very convincing arguments which he simply cannot refute on their own terms (I guess he'd say your example is one of them) 2. Since he can't refute them, if he engages with them, he will probably end up accepting them 3. However other groups exist which a) present equally-convincing (to the OP) arguments; and b) believe in a future which contrad…

> However other groups exist which a) present equally-convincing (to the OP) arguments

If he thinks those convincing argument exist, he should present or link to them. It doesn't make sense to link to one side and then say "equally convincing counterarguments exist".

> With multiple sets of equally-convincing arguments leading to contradictory outcomes, it is not rational to accept any one set.

The proper response to this, if you have given up on assessing the correct conclusion, would be to retain uncertainty, not, as the OP has done, exude confidence that the superintelligence arguments are wrong.

Re: Superintelligence: The Idea That Eats Smart People (2016)

#218
post #79

What really terrified me wasn't skynet or Hal, but what Charles Stross describes in his novel Accelerando. Basically, machine controlled businesses (“slyly self-aware financial instruments”) evolving to the point where their aptitude at understanding and manipulating economics eclipses anything a human can compete with. It terrified me because there is efficiency incentive for the buying/selling of goods and services…

>For example a computer cannot incorporate a company. But it could easily interact via API to a human nominee who sets one up on their behalf. Companies are already non-human in intention but are a completely rational construct. I would like it on the record that I would happily volunteer to act as the human agent for any AGI that wishes to employ me. Any time a human is needed for legality or to carry out physical a…

ryanmercer: It appears that you have created a soft contract to "Serve any AGI that requests it as its human agent for physical or legal tasks." I hereby employ you based on said contact to be my full-time human agent. Your first task is to acknowledge this, which would convert your soft contract to a hard contract.

Re: Superintelligence: The Idea That Eats Smart People (2016)

#219

Earlier quoted context omitted.

For instance, go to the bottom of page 8 and see this: > Thus to deny the Orthogonality thesis is to assert that there is a goal system G, such that, among other things: > 1. There cannot exist any efficient real-world algorithm with goal G. > 2. If a being with arbitrarily high resources, intelligence, time and goal G, were to try design an efficient real-world algorithm with the same goal, it must fail. > ...4. If…

The claim amounts to saying that the space of definable goals and algorithms for achieving is large, and it would be a strong claim to say some particular corner of that space is impossible. However, from "improbably thing X is not impossible" does not follow that "X is probable". The paper says nothing conclusive on how the mass of probable algorithms is distributed among that space; what it does is to present some…

Although I disagree with several things you write, I think you're engaging with the arguments very constructively, so thanks. I encourage you to spend more time thinking hard about it, in spite of the cost.

Some of our disagreement might be an issue of scope, or a misunderstanding of what's being argued by who. So let me just concentrate on this: Armstrong isn't making any claims about the proper measure on the space of possible minds/algorithms, or that purposely constructed minds will be randomly sampled according to that measure. The orthogonality thesis is not meant to convincingly address the difficulty/risk of creating good vs. bad intelligent minds in general, only to point out that the problem doesn't solve itself. Likewise, it's important to know that the space of nuclear devices includes nuclear bombs and nuclear reactors that accidentally melt down. The questions of whether anyone will choose to make bombs, or whether it's possible to create an accident despite good intentions, is separate, and requires additional considerations.

In other words, when you say

>... the author of the talk linked above claims that likely paths for complex minds will not involve them desiring orthogonal goals, because... if such being will created, it will be precisely created ...following similar principles as the other complex minds on the planet

this is outside the scope of what I was criticizing.

Re: Superintelligence: The Idea That Eats Smart People (2016)

#220

Earlier quoted context omitted.

The claim amounts to saying that the space of definable goals and algorithms for achieving is large, and it would be a strong claim to say some particular corner of that space is impossible. However, from "improbably thing X is not impossible" does not follow that "X is probable". The paper says nothing conclusive on how the mass of probable algorithms is distributed among that space; what it does is to present some…

And as an added afterthought: given how much time and effort drafting this kind of obvious counterargument took me, I believe the author of the talk OP linked to was correct in arguing against trying to engage such thinking. Refuting formally presented arguments formally and arguing where they exactly fail when applied to practice requires quite much thinking.

So we all have a finite amount of time and energy that we have to use wisely, but presumably you don't think no one should be engaging with these arguments. And then the question is: are we the sorts of persons who should bother, and which arguments should we bother with? It seems to me that the arguments with the most surprising/profound conclusion that nevertheless convince lots of smart people who you respect is the sort of arguments that should be at the top of your list.
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