skepsci

• skepsciFeb 17, 2012, 12:30 PM

  2 points

  in reply to: David_Gerard’s comment on: Hearsay, Dou­ble Hearsay, and Bayesian Updates

  Yeah, I was wondering about the downvotes. The welcome thread says that it’s perfectly acceptable to ask for an explanation… So, for anyone who downvoted me, why?

• skepsciFeb 17, 2012, 8:31 AM

  0 points

  in reply to: nerzhin’s comment on: The math­e­mat­ics of re­duced im­pact: help needed

  Exactly. If you have determinism in the sense of a function from AI action to result world, you can directly compute some measure of the difference between worlds X and X’, where X is the result of AI inaction, and X’ is the result of some candidate AI action.

  As nerzhin points out, you can run into similar problems even in deterministic universes, including life, if the AI doesn’t have perfect knowledge about the initial configuration or laws of the universe, or if the AI cares about differences between configurations that are so far into the future they are beyond the AI’s ability to calculate. In this case, the universe might be deterministic, but the AI must reason in probabilities.

• skepsciFeb 16, 2012, 10:36 AM

  3 points

  in reply to: A1987dM’s comment on: Hearsay, Dou­ble Hearsay, and Bayesian Updates

  An unfriendly legal system might treat being born as a crime. In fact, I’d be surprised if some politician in Arizona hasn’t tried to make being born to illegal immigrant parents a crime.

• skepsciFeb 16, 2012, 10:09 AM

  1 point

  in reply to: skepsci’s comment on: Hard philos­o­phy prob­lems to test peo­ple’s in­tel­li­gence?

  On a related note, I remember the day when I found out my PhD advisor (a computability theorist!) revealed that he believed the argument against AI from Gödel’s incompleteness theorem. It was not reassuring.

• skepsciFeb 16, 2012, 9:58 AM

  1 point

  in reply to: prase’s comment on: Beyond Rea­son­able Doubt? - Richard Dawk­ins [link]

  Dawkins starts from the premise that there is high uncertainty about the outcome of the case, and concludes that there is high uncertainty about the guilt, which does not follow. Even if it is obvious to everyone that the defendant is very probably guilty, it may be far from obvious exactly how high the jury will estimate the probability of innocence, and where they will set the bar for reasonable doubt.*

  *It has never been clear to me where this should be. If I put the credence of guilt at g, should I convict when g>.9? .99? .999? Should I say “to hell with the idea of reasonable doubt anyways, I’m going to estimate myself appropriate relative weights to attach to the outcomes 1) innocent man spends a lifetime in prison, and 2) serial murderer is unleashed upon the public?” I suppose because the lawyers and judge are unlikely to provide me with a credence threshold to use, the most sensible thing to do would be to derive one myself.

• skepsciFeb 16, 2012, 9:43 AM

  1 point

  in reply to: JonathanLivengood’s comment on: Hard philos­o­phy prob­lems to test peo­ple’s in­tel­li­gence?

  What do you mean by “great (awful)”? Do you mean that the thought experiment itself is an awful argument against AI, but describing the argument is a good way to test how people think?

• skepsciFeb 16, 2012, 8:51 AM

  0 points

  in reply to: DanielLC’s comment on: What is the ad­van­tage of the Kol­mogorov com­plex­ity prior?

  Maybe there is some true randomness in the universe

  Not a problem.

  I know it’s not a problem. I explained exactly how to modify Solomonoff induction to handle universes that are generated randomly according to some computable law, as opposed to being generated deterministically according to an algorithm.

  Suppose you flip a quantum coin ten times. If you record the output, the K-complexity is ten bits.

  Maybe it is, maybe it isn’t. Maybe your definition of Kolmogorov complexity is such that the Kolmogorov complexity of every string is at least 3^^^3, because you defined Kolmogorov complexity using a really dumb universal machine. Maybe it’s 2, because you programmed a universal machine that was really good at compressing the string 0101110010, because you like it, and it so happens that was what you flipped. If you flip a coin a very large number of times, it’s very likely that the Kolmogorov complexity of the output is at least the number of flips, but it could be much smaller due to chance.

  As such, there’s a 1/​1024 prior probability of getting that exact output. This is exactly what you’d get if you assumed it was random.

  False, because you don’t actually know the complexity was 10.

  Basically, K-complexity is treating the very laws of physics as random. Any randomness on top of that works the same way as it would as part of that.

  No, it’s not doing that at all. Using a complexity-weighted prior is assuming that the universe follows some random computable law, which is more likely to be simple than complex. I suppose this is true to the extent that any probability distribution on a countable set vanishes in the limit (for any enumeration of the countable set!), but I see no reason to bring Kolmogorov complexity into it.

  The problem is that it seems that things that are definable but not computable should be above random chance. For example, the K-complexity of a halting oracle is infinite, but it can be defined in finite space. Would the probability of the fine structure constant being a halting oracle be infinitesimal?

  I have no idea how to make sense of this question. Are infinitely many bits of fine structure constant even physically meaningful? If beyond a certain point of precision, the fine structure constant can’t be measured even in principle because it has no detectable physical effects on accessible time/​space scales, it makes no sense to even have an answer to the question “is the fine structure constant a halting oracle?” let alone the probability of such an event.

  One reason to use K-complexity is that so far, it’s worked far better than anything else. As far as we know, we can fit the laws of physics on a note card, yet the universe contains well over 10^80 particles, and don’t get me started on the amount of computing power necessary to run it.

  I’ll grant you that Occam’s razor works well in science. That wasn’t the question. The question is what is the advantage, if any, of starting with a Kolmogorov prior for Solomonoff induction, as opposed to any other arbitrary prior. You haven’t answered my question.

• skepsciFeb 16, 2012, 8:25 AM

  5 points

  in reply to: [deleted]’s comment on: Hearsay, Dou­ble Hearsay, and Bayesian Updates

  The assumption was that 80% of defendants are guilty, which is more than 4 of 8. Under this assumption, asking whether p(guilty|convicted) > 80% is just asking whether conviction positively correlates with guilt. Asking if p(innocent|acquitted) > 20% is just asking if acquittal positively correlates with innocence. These are really the same question, because P correlates with Q iff ¬P correlates with ¬Q.

• skepsciFeb 16, 2012, 7:20 AM

  11 points

  in reply to: Douglas_Knight’s comment on: Hearsay, Dou­ble Hearsay, and Bayesian Updates

  It proves that mistakes have been made, but in the end, no, I don’t think it’s terribly useful evidence for evaluating the rate of wrongful convictions. Why not? There have been 289 post-conviction DNA exonerations in US history, mostly in the last 15 years. That gives a rate of under 20 per year. Suppose 10,000 people a year are incarcerated for the types of crime that DNA exoneration is most likely to be possible for, namely murder and rape (I couldn’t find exact figures, but I suspect the real number is at least this big). Then considering DNA exonerations gives us a lower bound of something like .2% on the error rate of US courts.

  That is only useful evidence about the error rate if your prior estimate of the inaccuracy was less than that, and I mean, come on, really? Only one conviction in 500 is a mistake?

• skepsciFeb 16, 2012, 3:04 AM

  1 point

  in reply to: skepsci’s comment on: Open Thread, Fe­bru­ary 15-29, 2012

  To me, the entire argument sounds like a rationalization for not signing up for cryo.

  Signed,

  Someone who has rationalized a reason for not signing up yet for cryo, and suspects that the real reason is laziness.

• skepsciFeb 16, 2012, 2:55 AM

  7 points

  in reply to: Metus’s comment on: What is the ad­van­tage of the Kol­mogorov com­plex­ity prior?

  The interesting thing is now that we can formalize various inductive hypotheses as priors such as “Everything goes” as a uniform distribution.

  A uniform distribution on what? If you start with a uniform distribution on binary sequences, you don’t get to perform inductive reasoning at all, as the observables X(1), X(2), etc. are all independent in that distribution. If you wanted to start with a uniform distribution on computable universes, you can’t, because there is no uniform distribution with countable support.

• skepsciFeb 16, 2012, 2:39 AM

  0 points

  in reply to: A1987dM’s comment on: GAZP vs. GLUT

  I was having trouble articulating why I was uncomfortable reasoning under a mathematical counterfactual, but more comfortable reasoning under a mathematical hypothesis that might turn out to be false. This comment helped me clarify that for myself.

  I’ll explain my reasoning using Boolean logic, since it’s easier to understand that way, but obviously the same problem must occur with Bayesian logic, since Bayes generalizes Boole.

  Suppose we are reasoning about the effects of a mathematical conjecture P, and conclude that P → Q, and ¬P → Q’. Let’s assume Q and Q’ can’t both be true, because we’re interested in the difference between how the world would look if P were true, and how the world would look if P’ were true. Let’s assume we don’t have any idea which of P or ¬P is true. We can’t also have concluded P → Q’, because then the contradiction would allow as to conclude ¬P, and for the same reason we can’t also have concluded ¬P → Q. When we assume P, we only have one causal chain leading us to distinguish between Q and Q’, so we have an unambiguous model of how the universe will look under assumption P. This is true even if P turns out to be false, because we are aware of a chain of causal inferences beginning with P leading to only one conclusion.

  However, the second we conclude ¬P, we have two contradictory causal chains starting from P: P → Q, and P → ¬P → Q’, so our model of a universe where P is true is confused. We can no longer make sense of this counterfactual, because we are no longer sure which causal inferences to draw from the counterfactual.

• skepsciFeb 16, 2012, 2:30 AM

  2 points

  in reply to: lsparrish’s comment on: Open Thread, Fe­bru­ary 15-29, 2012

  I noticed an obvious fallacy in the linked argument:

  If infinite person-years possible, life extension is amoral.

  What? Surely if infinite person-years are possible, it’s better for everyone to be immortal than only some, so life extension would be morally preferable, not morally neutral.

  Also, why are we assuming the number of person-years lived is independent of the average lifespan? All he exhibited was an upper bound independent of the average lifespan, which is not at all the same thing. If you can’t justify the hypothesis that lifespan is a zero-sum game, the entire argument falls apart.

What is the ad­van­tage of the Kol­mogorov com­plex­ity prior?

• skepsciFeb 15, 2012, 1:01 PM

  2 points

  in reply to: JoachimSchipper’s comment on: The AI in a box boxes you

  Thank you. I knew that, but didn’t make the association.

• skepsciFeb 15, 2012, 11:46 AM

  4 points

  in reply to: Eliezer Yudkowsky’s comment on: The AI in a box boxes you

  Is there some background here I’m not getting? Because this reads like you’ve talked someone into committing suicide over IRC...

• skepsciFeb 15, 2012, 10:29 AM

  2 points

  in reply to: skepsci’s comment on: GAZP vs. GLUT

  To elaborate on this a little bit, you can think of the laws of physics as a differential equation, and the universe as a solution. You can imagine what would happen if the universe passed through a different state (just solve the differential equation again, with new initial conditions), or even different physics (solve the new differential equation), but how do you figure out what happens when calculus changes?

• skepsci 15 Feb 2012 10:01 UTC

  5 points

  on: Harry Pot­ter and the Meth­ods of Ra­tion­al­ity dis­cus­sion thread, part 9

  A hypothesis I’m currently toying with: Quirrell and HJPEV are different versions of the same individual, in some sense, and the Quirrell version is using some form of magic (probably involving breaking the 6-hour-limit on sending information backwards through time, possibly involving possession of a real Quirrell) to carry out a process of recursive self-improvement on himself. The story we’re currently reading takes place in one iteration of the loop.

  Has anyone posted this idea before on the net?

  There are some serious problems with this hypothesis:

  • Quirrell and HJPEV appear to have very different utility functions.

  • Performing recursive self-improvement starting with a human hardly seems like the kind of thing Eliezer would advocate, considering the likelihood of ending up with an unfriendly superintelligence.

  So it’s probably wrong, but I thought it was interesting enough to post.

• skepsci 15 Feb 2012 3:59 UTC

  0 points

  in reply to: skepsci’s comment on: You can’t be­lieve in Bayes

  You might be able to get around this by following Bayesian methods to choose an action as long as P(Bayes’ theorem)>.5, and then scrapping your entire decision-making algorithm and building a new one from scratch when this stops being true. But how do you decide on a new decision-making algorithm once your old decision-making algorithm has failed you?

• skepsci 15 Feb 2012 3:53 UTC

  0 points

  on: You can’t be­lieve in Bayes

  Well, you can. It’s just oxymoronic, or at least ironic. Because belief is contrary to the Bayesian paradigm. You use Bayesian methods to choose an action. You have a set of observations, and assign probabilities to possible outcomes, and choose an action.

  If you’re always using Bayesian methods to choose an action, it doesn’t matter what value of P(Bayes’ theorem) is set in your skull; it may as well be 1. If Bayes’ theorem is built into your very thought processes, if it’s false you’re fucked.