"Outside View!" as Conversation-Halter

I've put far more time that most engaging your singularity arguments, my responses have consisted of a lot more than just projecting a new growth jump from stats on the last three jumps, and I've continue to engage the topic long after that June 2008 post. So it seems to me unfair to describe me as someone arguing "for ending argument-gathering" on the basis that this one projection says all that can be said.

I agree that inside vs outside viewing is a continuum, not a dichotomy. I'd describe the key parameter as the sort of abstractions used, and the key issue is how well grounded are those abstractions. Outside views tend to pretty directly use abstractions that are based more "surface" features of widely known value. Inside views tend to use more "internal" abstractions, and inferences with longer chains.

Responding most directly to your arguments my main critiques have been about the appropriateness of your abstractions. You may disagree with them, and think I try to take the conversation in the wrong direction, but I don't see how I can be described as trying to halt the conversation.

"inside view" and "outside view" seem misleading labels for things that are actually "bayesian reasoning" and "bayesian reasoning deliberately ignoring some evidence to account for flawed cognitive machinery". The only reason for applying the "outside view" is to compensate for our flawed machinery, so to attack an "inside view", one needs to actually give a reasonable argument that the inside view has fallen prey to bias. This argument should come first, it should not be assumed.

We say: "Would you care to make a side bet on that?"

And I'd say . . . . "Sure! I recognize that I normally plan to finish 9 to 10 days early to ensure that I finish before the deadline and that I normally "fail" and only finish a day or two early (but still succeed at the real deadline) . . . . but now, you've changed the incentive structure (i.e. the entire problem) so I will now plan to finish 9 or 10 days before my new deadline (necessary to take your money) of 9 or 10 days before the real deadline. Are you sure that you really want to make that side bet?

I note also that "Would you care to make a side bet on that? is interesting as a potential conversation-filter but can also, unfortunately, act as a conversation-diverter.

Eliezer, the 'outside view' concept can also naturally be used to describe the work of Philip Tetlock, who found that political/foreign affairs experts were generally beaten by what Robin Dawes calls the "the robust beauty of simple linear models." Experts relying on coherent ideologies (EDIT: hedgehogs) did particularly badly.

Those political events were affected by big systemic pressures that someone could have predicted using inside view considerations, e.g. understanding the instability of the Soviet Union, but in practice acknowledged experts were not good enough at making use of such insights to generate net improvements on average.

Now, we still need to assign probabilities over different different models, not all of which should be so simple, but I think it's something of a caricature to focus so much on the homework/curriculum planning problems.

I think there probably is a good reference class for predictions surrounding the singularity. When you posted on "what is wrong with our thoughts? you identified it: the class of instances of the human mind attempting to think and act outside of its epistemologically nurturing environment of clear feedback from everyday activities.

See, e.g. how smart humans like Stephen Hawking, Ray Kurzweil, Kevin Warwick, Kevin Kelly, Eric Horowitz, etc have all managed to say patently absurd things about the issue, and hold mutually contradictory positions, with massive overconfidence in some cases. I do not exclude myself from the group of people who have said absurd things about the Singularity, and I think we shouldn't exclude Eliezer either. At least Eliezer has put in massive amounts of work for what may well be the greater good of humanity, which is morally commendable.

To escape from this reference class, and therefore from the default prediction of insanity, I think that bringing in better feedback and a large diverse community of researchers might work. Of course, more feedback and more researchers = more risk according to our understanding of AI motivations. But ultimately, that's an unavoidable trade-off; the lone madman versus the global tragedy of the commons.

Hanson's argument was interesting but ultimately I think it's just numerology - there's no real physical reason to expect that pattern to continue, especially given how different/loosely-related the 3 previous changes were.

This is an excellent post, thank you.

An earlier comment of yours pointed out that one compensates for overconfidence not by adjusting ones probability towards 50%, but by adjusting it towards the probability that a broader reference class would give. In this instance, the game of reference class tennis seems harder to avoid.

It seems like the Outside View should only be considered in situations which have repeatably provided consistent results. This is an example of the procrastinating student. The event has been repeated numerous time with closely similar outcomes.

If the data is so insufficient that you have a hard time casting it to a reference class, that would imply that you don't have enough examples to make a reference and that you should find some other line of argument.

This whole idea of outside view is analogous to instance based learning or case based reasoning. You are not trying to infer some underlying casual structure to give you insight in estimating. You are using an unknown distance and clustering heuristic to do a quick comparison. Just like in machine learning it will be fast, but it is only as accurate as your examples.

If you're using something like Eigenfaces for face recognition, and you get a new face in, if it falls right in the middle of a large cluster of Jack's faces, you can safely assume you are looking at Jack. If you get a face that is equally close to Susan, Laura, and Katherine, you wouldn't want to just roll the dice with that guess. The best thing to do would be to recognize that you need to fill in this area of this map a little more if you want to use it here. Otherwise switch to a better map.

Edit: spelling

I may be overlooking something, but I'd certainly consider Robin's estimate of 1-2 week doublings a FOOM. Is that really a big difference compared with Eliezer's estimates? Maybe the point in contention is not the time it takes for super-intelligence to surpass human ability, but the local vs. global nature of the singularity event; the local event taking place in some lab, and the global event taking place in a distributed fashion among different corporations, hobbyists, and/or governments through market mediated participation. Even this difference isn't that great, since there will be some participants in the global scenario with much greater contributions and may seem very similar to the local scenario, and vice versa where a lab may get help from a diffuse network of contributors over the internet. If the differences really are that marginal, then Robin's 'outside view' seems to approximately agree with Eliezer's 'inside view'.

If the Japanese students had put as much effort into their predictions as Eliezer has put into thinking about the singularity then I dare say they would have been rather more accurate, perhaps even more so than the "outside view" prediction.

I prefer the outside view when speaking with good friends, because they know me well enough to gather what I'm really saying isn't 'Stop Here!' but rather 'Explain to me why I shouldn't stop here?'

Perhaps this isn't really the outside view but the trappings of the outside view used rhetorically to test whether the other party is willing to put some effort into explaining their views. The Outside View as a test of your discussion partner.

The Inside View can be a conversation halter as well; going 'farther inside' or 'farther outside' than your partner can deal with halts the conversation, not the fact that you've taken an inside/outside view by itself.

Also, am I the only one who sees clear links between Outside/inside Views and methods of avoiding the tragedies of the Anticommons/Commons? Seems like the Outside view does a good job of saying 'By continuing to gather evidence you are hurting your ability to remain rational!' while the Inside view says 'Your Grand Idea is irrational considering this evidence!'

Someone should point out that "That is a conversation-halter" is very often a conversation halter.

The outside view technique is as follows:

You are given an estimation problem f(x)=?. x is noisy and you don't know all of the internals of f. First choose any set of functions F containing f. Then find a huge subset G of F such that g in G has that for all y in Y, g(y) is (say) bounded to some nice range R. Now find your probability p that x is in Y and your probability q that f is in G. Then with probability p*q f(x) is in R and this particular technique says nothing about f(x) in the remaining 1-p*q of your distribution.

Sometimes this is extremely helpful. Suppose you have the opportunity to bet $1 and you win $10 if a < f(x) < b. Then if you can find G,Y,R with R within (a,b) and with p*q > (1/10), you know the bet's good without having to bother with "well what does f look like exactly?".

Obvious pitfalls:

• Depending on f and G, sometimes p is not much easier to estimate than f(x). If you do a bad job estimating p and don't realize it, your bounds will be artificially confident. This IMO is what is happening when we pick any-reference-class-we-want F and then say the probability f is in G is equal to the number of things in G divided by the number of things in F.
• Estimate the wrong quantity. For example, instead of estimating the EV of a bet, estimate the probability you lose. You will establish a very nice bound on the probability, but the quantity you care about has an extra component which is WinPayoff*WinProbability, and if WinPayoff is greater order of magnitude than the other quantities, your bound tells you little.
• Mis-estimate q. It feels to me like this rarely happens, and that often it's the clarity of q's estimation that makes outside view arguments feel so persuasive.

What does this mean for continued investigation of the structure of f? It crucially depends on how we estimate p. If further knowledge about the structure of f does not affect how we should estimate p, then changing our estimate of the R*(p*q) component of f(x) based on our inside view is a bad plan and makes our estimate worse. If further knowledge about the structure of f does affect how we should estimate p, then to keep our R*(p*q) component around is also invalid.

So I see 3 necessary criteria to show that investigating the structure of f or the specifics of x won't help our estimate of f(x) much based on an outside view G,Y,R:

• An argument that 1-p*q is small.
• An argument that we cannot estimate the probability that f is in G much better given further knowledge of the structure of f.
• An argument that we cannot estimate the probability that x is in Y much better given further knowledge of the specifics of x.

Again, even if I don't have time for it myself, I think it would be useful to gather data on particular disagreements based on such "outside views" with vague similarities, and then see how often each side happened to be right.

Of course, even if the "outside view" happened to be right in most such cases, you might just respond with the same argument that all of these particular disagreements are still radically different from your case. But it might not be a very good response, in that situation.

I always love reading Less Wrong. I am just sometimes confused, for many days, about what exactly I have read. Until, something pertinent comes along and reveals the salience of what I had read, and then I say "OH! Now I get it!"

At present, I am between those two states... Waiting for the Now I get it moment.

"Eventually, some AI will go FOOM, locally self-improvingly rather than global-economically"

Ouch. This statement smells to me like backtracking from your actual position. If you honestly have no time estimate beyond "eventually", why does the SIAI exist? Don't you have any more urgent good things to do?

(edited to remove unrelated arguments, there will be time for them later)

It's a bit off topic, but I've been meaning to ask Eliezer this for a while. I think I get the basic logic behind "FOOM." If a brain as smart as ours could evolve from pretty much nothing, then it seems likely that sooner or later (and I have not the slightest idea whether it will be sooner or later) we should be able to use the smarts we have to design a mind that is smarter. And if we can make a mind smarter than ours, it seems likely that that mind should be able to make one smarter than it, and so on. And this process should be pretty explosive, at least for a while, so that in pretty short order the smartest minds around will be way more than a match for us, which is why it's so important that it be baked into the process from the beginning that it proceed in a way that we will regard as friendly.

But it seems to me that this qualitative argument works equally well whether "explosive" means "box in someone's basement to Unchallenged Lord and Master of the Universe Forever and Ever" before anyone else knows about it or can do anything about it, or it means "different people/groups will innovate and and borrow/steal each others' innovations over a period of many years, at the end of which where we end up will depend only a little on the contribution of the people who started the ball rolling." And if that's right, doesn't it follow that what really matters is not the correctness of the FOOM argument (which seems correct to me), but rather the estimate of how big the exponent is in the exponential growth is likely to be? Is this (and much of your disagreement with Robin Hanson) just a disagreement over an estimate of a number? Does that disagreement stand any chance of being anywhere near resolved with available evidence?

Once again, Bayesian reasoning comes to the rescue. The assertion to stop updating based on new data (ignore the inside view!) is just plain wrong.

However a reminder to be careful and objective about the probability one might assign to a new bit of data (Inside view data is not privileged over outside view data! And it might be really bad!) is helpful.

I see a couple of problems with classifying "intelligent design by machines" as a big evolutionary leap away from "intelligent design by humans".

The main difference is one of performance. Performance has been increasing gradually anyway - what is happening now is that it is now increasing faster.

Also, humans routinely augment their intelligence by using machine tools - blurring any proposed line between the machine-augmented humans that we have today and machine intelligence.

My favoured evolutionary transition classification scheme is to bundle all the modern changes together - and describe them as being the result of the rise of the new replicators. Machine intelligence is just the new replicators making brains for themselves. Nanotechnology and robotics are just the new replicators making bodies for themselves.

These phenomena had a single historical source. Future historians will see them as intimately linked. They happen rapidly in quick succession in geological time.

If you want to subdivide further, fine - but then I think you have to consider the origin of language, and the origin of writing and the origin of the computer to be the next-most important recent events.

You seem to be phrasing this as an either/or decision.

Remembering that all decisions are best formalized as functions, the outside view asks, "What other phenomena are like this one, and what did their functions look like?" without looking at the equation. The inside view tries to analyze the function. The hardcore inside view tries to actually plot points on the function; the not-quite-so-ambitious inside view just tries to find its zeros, inflection points, regions where it must be positive or negative, etc.

For complex issues, you should go back and forth between these views. If your outside view gives you 5 other functions you think are comparable, and they are all monotonic increasing, see if your function is monotonic increasing. If your inside view suggests that your function is everywhere positive, and 4 of your 5 outside-view functions are everywhere positive, throw out the 5th. And so on.

For example, the Singularity is unusual enough that looking past it calls for some inside-view thinking. But there are a few strong outside-view constraints that you can invoke that turn out to have strong implications, such as the speed of light.

The one that's on my mind at present is my view that there will be scarcity of energy and physical resources after the Singularity, an outside view based on general properties of complex systems such as markets and ecosystems, plus the relative effects I expect the Singularity to have on the speed of computation and development of new information vs. the speed of development of energy and physical resources. A lot of people on LW make the contrary assumption that there will be abundance after the Singularity (often, I think, as a necessary article of faith for the Church of the Friendly AI Santa). The resulting diverging opinions on what is likely to happen (such as, Am I likely to be revived from cryonic suspension after the Singularity?) are an example of opinions resulting from similar inside-view reasoning within different outside-view constraints. The argument isn't inside view vs. outside view; the argument in this case is between two outside views.

(Well, actually there's more to our differences than that. I think that asking "Will I be revived after the Singularity?" is like a little kid asking "Will there be Bugs Bunny cartoons in heaven?" Asking the question is at best humorous, regardless of whether the answer is yes or no. But for purposes of illustrating my point, the differing outside views is what matters.)

The "Outside View" is the best predictor of timeframes and happiness (Dan Gilbert 2007)

The reason why people have choosen to study students and what they think about homework is probably because they supposed there were mistakes in average students declarations. Same for studying affective forecast (technical term for 'predicting future happiness given X').

I suspect this kind of mistake does not happen in engineering companies when they evaluate next year's profits given their new technical environment... Therefore no one bothers to study engineers inside views.

I see a couple of problems with classifying "intelligent design by machines" as a big leap away from "intelligent design by humans".

The main difference is one of performance. Performance has been increasing gradually anyway - what is happening now is that it is now increasing faster.

Also, humans routinely augment their intelligence by using machine tools - blurring the proposed line between human and machine intelligence.

My favoured evolutionary transition classification scheme is to bundle the modern changes together - and describe them as being the result of the rise of the new replicators. Machine intelligence is just the new replicators making brains for themselves. Nanotechnology and robotics are just the new replicators making bodies for themselves.

These phenomena had a single historical source. Future historians will see them as intimately linked. They happen rapidly in quick succession in geological time.

If you want to subdivide further, fine - but then I think you have to consider the origin of language, and the origin of writing and the origin of the computer to be the next-most important recent events.

You are using inside view arguments to argue against outside view.

I think the only thing that could convince me that outside view of predictions of the future works worse than inside view, is big database of such predictions showing how outside view did worse - that is outside view arguments against outside view.

Outside view arguments against inside view - countless failed expert predictions - is easy to find.

I tend to think that the most relevant piece of information about the singularity is Moore's Second Law, "the cost of a semiconductor fab rises exponentially with each generation of chips."

Corollary 1: At some point, the rate of increase in computing power will be limited by the rate of growth in the overall global economy.

Corollary 2: AI will not go FOOM (at least, not by a process of serially improved computer designs).