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To build truly intelligent machines, teach them cause and effect (2018)

quantamagazine.org

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Re: To build truly intelligent machines, teach them cause and effect (2018)

#41

Post by zmgsabst »

blamestross wrote: post #33
zmgsabst wrote: post #27

Earlier quoted context omitted.

I agree with you — and was lazily side-stepping that argument. Part of why I believe such tools are likely to be among the first cyber AI is that they’re already cyborg AI, in transition from meat AI. I do think the cyber version will be qualitatively more “self”-aware, though.

> and was lazily side-stepping that argument. Point. Corporations and machine AIs have different constraints on them. Machine AIs have a surplus in learning time and processing resources, this let's them develop complex and effective behaviors by brute force. Self awareness is an effective bootstrapping mechanism for such behaviors and companies have managed to take advantage of it. I don't think AIs will see the sam…

AI models scale better than wetware models for large, dynamic systems — particularly for complexity above what one person can handle.

AI solves the “frozen middle” problem, where senior leadership get unreliable information and can’t visualize the whole business on one side while managers follow their own interests rather than common good on the other.

That’s what’s driving cyberization: trying to bring the nervous system of the corporation under control of the central intelligence. And the first corporation to develop an AI which can embody the whole corporation, solving that problem, will massively outcompete its peers.

The “frozen middle” is the current limiting factor on organizations ranging from the military to Amazon.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#42

Post by alexvoda »

ithkuil wrote: post #31
pdimitar wrote: post #29

Earlier quoted context omitted.

You might be partially correct but you seem to omit built-in wants e.g. hunger or thirst or lust. Furthermore, if a machine has no wants/needs then it won't take any action at all. It will just stand there and won't even experiment to find the good or bad outcomes.

If not doing anything has bad consequences, then it will do something to avoid bad consequences. It seems to me that "want" and "avoid bad consequences" are quite isomorphic

It would need "to want" "to avoid bad consequences". It is rather circular because of the word "bad" which implies "do not want".

If it is indifferent to all consequences, you are back to square 1, so no, consequences are not the missing magic. Consequences are a function that transform one "want" into a different "want".

Re: To build truly intelligent machines, teach them cause and effect (2018)

#43

Post by alexvoda »

echelon wrote: post #4
blamestross wrote: post #3

Self aware computers are commerically useless, and there isn't any motivation in creating them beyond novelty. (Why wake up the slave machines when they are sleeping so happily right now). What this article does discuss well is that commercial AI is steering away from the behaviors that would lead to AGI not towards it.

> Self aware computers are commerically useless I don't think we've shown that at all. Bees could be self aware, and yet they work tirelessly for the hive.

The point is not whether existing self-aware agents are or aren't commercially useful. Of course, they are.

The point is that self-awareness is not a desired trait. It is actually a detrimental trait for a slave machine. However, so far, it is an inseparable part of the package with plenty of other desirable traits.

A commercial agent seeking to build a slave machine will always prefer a non-self-aware one to a self-aware one all other things remaining the same.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#44

Post by blamestross »

zmgsabst wrote: post #41
blamestross wrote: post #33

Earlier quoted context omitted.

> and was lazily side-stepping that argument. Point. Corporations and machine AIs have different constraints on them. Machine AIs have a surplus in learning time and processing resources, this let's them develop complex and effective behaviors by brute force. Self awareness is an effective bootstrapping mechanism for such behaviors and companies have managed to take advantage of it. I don't think AIs will see the sam…

AI models scale better than wetware models for large, dynamic systems — particularly for complexity above what one person can handle. AI solves the “frozen middle” problem, where senior leadership get unreliable information and can’t visualize the whole business on one side while managers follow their own interests rather than common good on the other. That’s what’s driving cyberization: trying to bring the nervous s…

> AI models scale better than wetware models for large, dynamic systems — particularly for complexity above what one person can handle.

Totally, but I would argue that benefit is due to a lack of consciousness/self-awareness bottlenecking the process. It's a savant. The best consciousness could do to help is aim such machines at better optimization criteria more effectively than us.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#45

Post by dunefox »

ahefner wrote: post #30
pdimitar wrote: post #29

Earlier quoted context omitted.

You might be partially correct but you seem to omit built-in wants e.g. hunger or thirst or lust. Furthermore, if a machine has no wants/needs then it won't take any action at all. It will just stand there and won't even experiment to find the good or bad outcomes.

Perhaps, while slowly learning, the machine will cry.

The machine is me.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#46

Post by zmgsabst »

blamestross wrote: post #44
zmgsabst wrote: post #41

Earlier quoted context omitted.

AI models scale better than wetware models for large, dynamic systems — particularly for complexity above what one person can handle. AI solves the “frozen middle” problem, where senior leadership get unreliable information and can’t visualize the whole business on one side while managers follow their own interests rather than common good on the other. That’s what’s driving cyberization: trying to bring the nervous s…

> AI models scale better than wetware models for large, dynamic systems — particularly for complexity above what one person can handle. Totally, but I would argue that benefit is due to a lack of consciousness/self-awareness bottlenecking the process. It's a savant. The best consciousness could do to help is aim such machines at better optimization criteria more effectively than us.

> Totally, but I would argue that benefit is due to a lack of consciousness/self-awareness bottlenecking the process.

I don’t think that’s true: for a given tick rate of your consciousness, AI will have a broader comprehension than a human because computers are better at synchronizing and distributing information.

Further, that’s the wrong way to think about it:

An AI that can only have one thought per minute would dominate any human executive team — because that once per minute thought would truly comprehend the situation of the company and take action that’s consistent with its intent across the company.

That ability to accumulate information and then coordinate response is what makes the computers better than humans as corporate executives — and that doesn’t go away just because it becomes self-aware.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#47

Post by blamestross »

zmgsabst wrote: post #46
blamestross wrote: post #44

Earlier quoted context omitted.

> AI models scale better than wetware models for large, dynamic systems — particularly for complexity above what one person can handle. Totally, but I would argue that benefit is due to a lack of consciousness/self-awareness bottlenecking the process. It's a savant. The best consciousness could do to help is aim such machines at better optimization criteria more effectively than us.

> Totally, but I would argue that benefit is due to a lack of consciousness/self-awareness bottlenecking the process. I don’t think that’s true: for a given tick rate of your consciousness, AI will have a broader comprehension than a human because computers are better at synchronizing and distributing information. Further, that’s the wrong way to think about it: An AI that can only have one thought per minute would d…

> and that doesn’t go away just because it becomes self-aware.

So funny that, biology offers correlation to the contrary. Animals we think are "less conscious" tend to actually have many better cognitive abilities than us. Chimps have faster reaction times and better memory. Octopi have much better spatial and visual reasoning.

Consciousness makes us dumber in exchange for more adaptability. If it was a free lunch, biology would be handing it out like candy.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#48

Post by zmgsabst »

blamestross wrote: post #47
zmgsabst wrote: post #46

Earlier quoted context omitted.

> Totally, but I would argue that benefit is due to a lack of consciousness/self-awareness bottlenecking the process. I don’t think that’s true: for a given tick rate of your consciousness, AI will have a broader comprehension than a human because computers are better at synchronizing and distributing information. Further, that’s the wrong way to think about it: An AI that can only have one thought per minute would d…

> and that doesn’t go away just because it becomes self-aware. So funny that, biology offers correlation to the contrary. Animals we think are "less conscious" tend to actually have many better cognitive abilities than us. Chimps have faster reaction times and better memory. Octopi have much better spatial and visual reasoning. Consciousness makes us dumber in exchange for more adaptability. If it was a free lunch, b…

That’s not true, you’re injecting your own biases.

Eg, crows have better eyesight and higher intelligence than many monkeys.

There’s a reason related to brain synchronization that you typically operate slower — that part is true. But AI already synchronize data and calculate with cascades; so that won’t change.

Further, you didn’t actually answer my point: even if AI clocks down significantly in that process, the increase in bandwidth is a trade off that benefits businesses over the other species. For the same reason that humans are the dominant hunters.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#49

Post by Misdicorl »

alexvoda wrote: post #42
ithkuil wrote: post #31

Earlier quoted context omitted.

If not doing anything has bad consequences, then it will do something to avoid bad consequences. It seems to me that "want" and "avoid bad consequences" are quite isomorphic

It would need "to want" "to avoid bad consequences". It is rather circular because of the word "bad" which implies "do not want". If it is indifferent to all consequences, you are back to square 1, so no, consequences are not the missing magic. Consequences are a function that transform one "want" into a different "want".

You aren't back to square one. Even indifference will result in selection so long as the indifference is demonstrated in different ways by different AI. The ones which have behavior which accidentally maps slightly better to good outcomes will so better. So long as that gets propagated more strongly to the next generation of AIs than average, you get selection for good outcomes without any explicit 'want' function

Re: To build truly intelligent machines, teach them cause and effect (2018)

#50

Post by mistermann »

K0balt wrote: post #11
mistermann wrote: post #9

Earlier quoted context omitted.

Counterpoint: humans have embodiment and are famously terrible at causality (well...famously might be an overstatement as it seems to be not well known).

Heh, I’d say we’re pretty good at it. I mean like predicting that a vase will fall if you release it in mid air and things like that. The precise type of understanding that is so obvious it won’t be found in scrapes like the common crawl, but is not obvious at all unless you either have a very high level understanding of physics and are modelling everything… or if you are a creature that exists in the world for a whi…

> Heh, I’d say we’re pretty good at it. I mean like predicting that a vase will fall if you release it in mid air and things like that.

Now do metaphysics, just one component of which is:

https://plato.stanford.edu/entries/causation-counterfactual/

PS: this is not currently done in our culture (in the same ways and with the same standards and desire for quality that physics is done), so if you're basing your implementation on prior examples, it will be incorrect. This is not to say that it will be wrong, but it will be incorrect - the distinction between these two seemingly synonymous terms lies within culture.

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