Steelmaning AI risk critiques

I'm sure there's no need to point to Robin Hanson's anti-foom writings? The best single article is IMO Irreducible Detail essentially questioning the generality of intelligence.

One of the most common objection's I've seen is that we're too far from getting AGI to know what AGI will be like, so we can't productively work on the problem without making a lot of conjunctive assumptions -- e.g. see this post.

One may try the following conjecture: Synthetic biology is so simple and AI is so complex, that risks of extinction from artificial viruses are far earlier in time. Even if both risks have the same probability individually, the one that comes first gets biggest part of total probability.

For example, lets Pv = 0.9 is the risks of viruses in the absence of any other risks, and Pai = 0.9 is the risk of AI in absence of any viruses. But Pv may happened in the first half of 21 century, and Pai in the second. In this case we have total probability of extinction =0.99, from which 0.9 comes from viruses, and 0.09 comes cent from AI.

If it true, than promoting AI as the main existential risk is misallocation of resources.

If we look closer in Pv and Pai, we may find that Pv is exponentially increasing in time because of Moore law in biotech, while Pai describes one time event and is constant. AI will be friendly or not. (It also may have more complex time depending, but here I just estimate the probability that FAI theory will be created and implemented.)

And assuming that AI is the only mean to stop creating dangerous viruses (it may be untrue but for the sake of the argument we will suppose it) when we need AI as earlier as possible, even if it will have smaller chances to be friendly.

So, this line of reasoning suggests that AI is not risk because its benefits will outweigh its risks if we look in larger picture.

Personally I think that we must invest in creating Safe AI, but we need to do it as soon as possible.

Update: the same logic may be applied in different efforts in AI field. AI do not need to be able to self-improve to cause human extinction. It may be just 200 IQ Stuxnet that hacks critical infrastructure. Such AI may appear before real self-improving AI, as the latter must be based on non self-improving but clever AI. So our efforts to prevent dangerous non-self-improving AIs may be more urgent, and all work on Godelian agents is misallocation of resources.

Arguments against AI risk, .or arguments against the MIRI conception of AI risk?

I have heard a hint of a whisper of a rumour that I am considered a bit of a contrarian around here...but I am actually a little more convinced of AI threat in general than I used be before I encountered less wrong. (in particular, at one time, I would have said "just pull the plug out", but there's some mileage in the unknowing arguments)

The short version of the arguments against MIRIs version of AI threat is that it is highly conjunctive. The long version is long. a consequence of having a multi stage argument, with a fan out of alternative possibilities at each stage.

Ramez Naam discusses it here: http://rameznaam.com/2015/05/12/the-singularity-is-further-than-it-appears/

I find the discussion of corporations as superintelligences somewhat persuasive. I understand why Eliezer and others do not consider them superintelligences, but it seems to me a question of degree; they could become self-improving in more and more respects and at no point would I expect a singularity or a world-takeover.

I also think the argument from diminishing returns is pretty reasonable: http://www.sphere-engineering.com/blog/the-singularity-is-not-coming.html

Here is a novel argument you may or may not have heard: We live in the best of all probable worlds due to simulation anthropics. Future FAI civs spend a significant amount of their resources to resimulate and resurrect past humanity - winning the sim race by a landslide (as UFAI is not strongly motivated to sim us in large numbers). As a result of this anthropic selection force, we find ourselves in a universe that is very lucky - it is far more likely to lead to FAI than you would otherwise think.

The best standard argument is this: the brain is a universal learning machine - the same general architecture that will necessarily form the basis for any practical AGI. In addition the brain is already near optimal in terms of what can be done for 10 watts with any irreversible learning machine (this is relatively easy to show from wiring energy analysis). Thus any practical AGI is going to be roughly brain like, similar to baby emulations. All of the techniques used to raise humans safely can thus be used to raise AGI safely. LW/MIRI historically reject this argument based - as far as I can tell - on a handwavey notion of 'anthropomorphic bias', which has no technical foundation.

I've presented the above argument about four years ago, but I never bothered to spend the time backing it up in excruciating formal detail. Until more recently. The last 5 years of progress in AI strongly supports this anthropomorphic AGI viewpoint.

Here's one from a friend of mine. It's not exactly an argument against AI risk, but it is an argument that the problem may be less urgent than it's traditionally presented.

1. There's plenty of reason to believe that Moore's Law will slow down in the near future

2. Progress on AI algorithms has historically been rather slow.

3. AI programming is an extremely high level cognitive task, and will likely be among the hardest things to get an AI to do.

4. These three things together suggest that there will be a 'grace period' between the development of general agents, and the creation of a FOOM-capable AI.

5. Our best guess for the duration of this grace period is on the order of multiple decades.

6. During this time, general-but-dumb agents will be widely used for economic purposes.

7. These agents will have exactly the same perverse instantiation problems as a FOOM-capable AI, but on a much smaller scale. When they start trying to turn people into paperclips, the fallout will be limited by their intelligence.

8. This will ensure that the problem is taken seriously, and these dumb agents will make it much easier to solve FAI-related problems, by giving us an actual test bed for our ideas where they can't go too badly wrong.

This is a plausible-but-not-guaranteed scenario for the future, which feels much less grim than the standard AI-risk narrative. You might be able to extend it into something more robust.

http://kruel.co/2012/07/17/ai-risk-critiques-index/

Kruel's critique sounded very convincing when I first read it.

Thanks for doing this. A lack of self criticism about AI risk is one of the reasons I don't take it too seriously.

I generally agree with http://su3su2u1.tumblr.com/ , but it may not be organized enough to be helpful.

As for MIRI specifically, I think you'd be much better served by mainstream software verification and cryptography research. I've never seen anyone address why that is not the case.

I have a bunch of disorganized notes about why I'm not convinced of AI risk, if you're interested I could share more.

Holden Karnofsky's tool AI critique (see also Eliezer's response). Outdated wiki page.

I've always consider the psychological critiques of AI risk (eg "the singularity is just rapture of the nerds") to be very weak ad hominems. However, they might be relevant for parts of the AI risk thesis that depend on the judgements of the people presenting it. The most relevant part would be in checking whether people have fully considered the arguments against their position, and gone out to find more such arguments.

Creating stable AGI that operates in the real world may be unexpectedly difficult. What I mean by this is we might solve some hard problems in AI, and the result might work in some limited domains, but isn't stable in the real world.

An example would be Pascal's Mugging. An AI that maximizes expected utility with an unbounded utility function, would spend all it's time worrying about incredibly improbable scenarios.

Reinforcement learning agents might simply hijack their own reinforcement channel, set it to INF, and be done.

Or the Anvil Problem where a reinforcement learning-type AI simply doesn't act as though it's brain exists in the universe it's observing, and could result in strange behavior.

It might place a strong value on literal self preservation, and refuse to upgrade itself or create copies, or even allow it's physical computer to be rebooted. This would constrain the AI a great deal.

Further, it might not create other AIs that serve it, since the friendliness problem would be just as hard for it.

There could be technical or philosophical issues we haven't even thought of yet that a superintelligent AI would encounter and not be built to deal with. And most of these issues depend a great deal on the technical details of the AGI, which we don't even know yet. There are all sorts of hypothetical problems that are specific to neural networks, or evolved AIs, or open-cog like AIs, etc.

I'm not very confident that these will stop UFAI though. Pascal's Mugging can simply bound the utility function at some arbitrarily high number and create a dangerous AI. Reinforcement learning agents would probably still value self preservation after maximizing their input channel. The AI won't anvil itself since it would prevent it from manipulating the world or decrease it's reward. Self preservation for an AI is more about preserving it's reward machinery. Not the the actual AI program that maximizes it.

I definitely believe an unfriendly AI can be built that just maximizes some stupid goal. And if there are technical issues, it's only a matter of time before someone solves them. But I'm not 100% confident of it.

It doesn't matter how safe you are about AI if there's a million other civilizations in the universe and some non-trivial portion of them aren't being as careful as they should be.

A UFAI is unlikely to stop at the home planet of the civilization that creates it. Rather you'd expect such a thing to continue to convert the remainder of the universe into computronium to store the integer for it's fitness function or some similar doomsday scenario.

AI doesn't work as a filter because it's the kind of disaster likely to keep spreading and we'd expect to see large parts of the sky going dark as the stars get turned into pictures of smiling faces or computronium.

Which either argues for AI-risk not being so risky or for an early filter causing few civilisations.

There exists a technological plateau for general intelligence algorithms, and biological neural networks already come close to optimal. Hence, recursive self-improvement quickly hits an asymptote.

Therefore, artificial intelligence represents a potentially much cheaper way to produce and coordinate intelligence compared to raising humans. However, it will not have orders of magnitude more capability for innovation than the human race. In particular, if humans are unable to discover breakthroughs enabling vastly more efficient production of computational substrate, then artificial intelligence will likewise be unable. In that case, unfriendly AI poses an existential threat primarily through dangers that we can already imagine, rather than unanticipated technological breakthroughs.

It did a little bit of this towards the end of my review of EY's rationality book.

Ray Kurzwiel seems to believe that humans will keep pace with AI through implants or other augmentation, presumably up to the point that WBE becomes possible and humans get all/most of the advantages an AGI would have. Arguments from self-interest might show that humans will very strongly prefer human WBE over training an arbitrary neural network of the same size to the point that it becomes AGI simply because they hope to be the human who gets WBE. If humans are content with creating AGIs that are provably less intelligent than the most intelligent humans then AGIs could still help drive the race to superintelligence without winning it (by doing the busywork that can be verified by sufficiently intelligent humans).

The steelman also seems to require an argument that no market process will lead to a singleton, thus allowing standard economic/social/political processes to guide the development of human intelligence as it advances while preventing a single augmented dictator (or group of dictators) from overpowering the rest of humanity, or an argument that given a cabal of sufficient size the cabal will continue to act in humanity's best interests because they are each acting in their own best interest, and are still nominally human. One potential argument for this is that R&D and manufacturing cycles will not become fast enough to realize substantial jumps in intelligence before a significant number of humans are able to acquire the latest generation.

The most interesting steelman argument to come out of this one might be that at some point enhanced humans become convinced of AI risk, when it is actually rational to become concerned. That would leave only steelmanning the period between the first human augmentation and reaching sufficient intelligence to be convinced of the risk.

I wrote some arguments that I think are novel here: http://lesswrong.com/r/discussion/lw/ly8/values_at_compile_time/cam0

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