Johnicholas

The Robots, AI, and Unemployment Anti-FAQ

Steve Keen's Debunking Economics blames debt, not automation.

Essentially, many people currently feel that they are deep in debt, and work to get out of debt. Keen has a ODE model of the macroeconomy that shows various behaviors, including debt-driven crashes.

Felix Martin's Money goes further and argues that strong anti-inflation stances by central bank regulators strengthen the hold of creditors over debtors, which has made these recent crashes bigger and more painful.

Replying toKevin T. Kelly's Ockham Efficiency Theorem

Kevin T. Kelly's Ockham Efficiency Theorem

The statements, though contradictory, refer to two different thought experiments.

Replying toKevin T. Kelly's Ockham Efficiency Theorem

Kevin T. Kelly's Ockham Efficiency Theorem

The two comments, though contradictory, refer to two different thought experiments.

Replying toPascal's Muggle: Infinitesimal Priors and Strong Evidence

Pascal's Muggle: Infinitesimal Priors and Strong Evidence

Is it reasonable to take this as evidence that we shouldn't use expected utility computations, or not only expected utility computations, to guide our decisions?

If I understand the context, the reason we believed an entity, either a human or an AI, ought to use expected utility as a practical decision making strategy, is because it would yield good results (a simple, general architecture for decision making). If there are fully general attacks (muggings) on all entities that use expected utility as a practical decision making strategy, then perhaps we should revise the original hypothesis.

Utility as a theoretical construct is charming, but it does have to pay its way, just like anything else.

P.S. I think the reasoning from "bounded rationality exists" to "non-Bayesian mind changes exist" is good stuff. Perhaps we could call this "on seeing this, I become willing to revise my model" phenomenon something like "surprise", and distinguish it from merely new information.

Magic Haskeller and Augustsson's Djinn are provers (or to say it another way, comprehensible as provers, or to say it another way, isomorphic to provers). They attempt to prove the proposition, and if they succeed they output the term corresponding (via the Curry-Howard Isomorphism) to the proof.

I believe they cannot output a term t :: a->b because there is no such term, because 'anything implies anything else' is false.

The type constructors that you're thinking of are Arrow and Int. Forall is another type constructor, for constructing generic polymorphic types. Some types such as "Forall A, Forall B, A -> B" are uninhabited. You cannot produce an output of type B in a generic way, even if you are given access to an element of type A.

The type corresponding to a proposition like "all computable functions from the reals to the reals are continuous" looks like a function type consuming some representation of "a computable function" and producing some representation of "that function is continuous". To represent that, you probably need dependent types - this would be a type constructor that... (read more)

Replying toForcing Anthropics: Boltzmann Brains

Forcing Anthropics: Boltzmann Brains

I think you may be sincerely confused. Would you please reword your question?

If your question is whether someone (either me or the OP) has committed a multiplication error - yes, it's entirely possible, but multiplication is not the point - the point is anthropic reasoning and whether "I am a Bolzmann brain" is a simple hypothesis.

The arithmetical hierarchy is presuming a background of predicate logic; I was not presuming that. Yes, the type theory that I was gesturing towards would have some similarity to the arithmetical hierarchy.

I was trying to suggest that the answer to "what is a prediction" might look like a type theory of different variants of a prediction. Perhaps a linear hierarchy like the arithmetical hierarchy, yes, perhaps something more complicated. There could be a single starting type "concrete prediction" and a type constructor that, given source type and a destination type, gives the type of statements defining functions that take arguments of the source type and give arguments of the destination type.

The... (read more)

Recognizing memetic infections and forging resistance memes

Perhaps there is a type theory for predictions, with concrete predictions like "The bus will come at 3 o'clock", and functions that output concrete predictions like "Every monday, wednesday and friday, the bus will come at 3 o'clock" (consider the statement as a function taking a time and returning a concrete prediction yes or no).

An ultrafinitist would probably not argue with the existence of such a function, even though to someone other than an ultrafinitist, the function looks like it is quantifying over all time. From the ultrafinitist's point of view, you're going to apply it to some concrete time, and at that point it's going to output a some concrete prediction.

Evaluating weather forecast accuracy: an interview with Eric Floehr

14y

What does an memetic infection look like? Well, you would encounter something (probably on the internet) that seems very compelling. You think intensely about it for a while, and it spurs you to do something - probably to post something related on the internet. After a while, the meme may not seem that compelling to you anymore, and you wonder why you invested that time and energy. The meme has reproduced itself. For example, Bruce Sterling's response to the 'New Aesthetic' is a paradigmatic example of memetic infection: he encountered it, he found it compelling, he wrote about it, I read about it and now I know about it. (Note that the word 'infection'... (read 918 more words →)

http://www.johndcook.com/blog/2011/04/12/weather-forecast-accuracy/

15y

Eric Floehr has a business that "holds a mirror up" to weather forecasters, and aggregates and evaluates forecasters for weather forecast consumers. Rationalists interested in improving our societies truth orientation might be mildly interested.

Failure Modes sometimes correspond to Game Mechanics

The null model of science

15y

If you want to carry a brimming cup of coffee without spilling it, you may want to "change" your goal to instead primarily concentrate on humming. This is an example of a general pattern. It sometimes helps to focus on a nearby artificial goal rather than your actual goal. Let me call that strategy "gamification". There is a business strategy, also named "gamification", of adding game mechanics to a website in order to achieve various business goals. This is related but different. Here I'm referring to a strategy for problem solvers.

We sometimes fail, and sometimes one failure is very similar to another failure. That is, there are characteristic ways that we fail.... (read 1073 more words →)

http://m.newyorker.com/reporting/2010/12/13/101213fa_fact_lehrer?currentPage=all

15y

Jonah Lehrer wrote about the (surprising?) power of publication bias.

Cosma Shalizi (I think) said something, or pointed to something, about the null model of science - what science would look like if there were no actual effects, just statistical anomalies that look good at first. I can't find the reference, though.

What are Arguments, from an Agorics point of view?

Move meetups to the sidebar?

15y

Background on Agorics:

The idea of software agents cooperating in an open market or "agora". Described by Mark Miller and Eric Drexler here: http://e-drexler.com/d/09/00/AgoricsPapers/agoricpapers.html Depicted by Greg Egan in his novel "Diaspora", exerpt here: http://gregegan.customer.netspace.net.au/DIASPORA/01/Orphanogenesis.html

Background on Argument: http://en.wikipedia.org/wiki/Argument

Let's start by supposing that an argument is a variety of persuasive message. If Bob trusts Alice though, Bob could be persuaded by simply recieving a claim from Alice. That is a kind of persuasive message, but it's not an argument. If Bob is insecure, then Bob's mind could be hacked and therefore changed. However, that's not an argument either. (The "Buffer Overflow Fallacy"?)

Possibly arguments are witnesses (or "certificates"), as used in computational complexity. Alice could spend exp-time to solve... (read more)

Kevin T. Kelly's Ockham Efficiency Theorem

15y

The number of meetup announcements on the main blog has been increasing. Though it's reasonable to try to get meetups high visibility to increase the chance that people who are nearby see the announcement, the posts themselves are content-free.

How difficult would it be to, instead of promoting meetup announcements, tag them "meetup" and put a "meetups" section in the sidebar, similar to "recent comments" or "recent posts"?

16y

There is a game studied in Philosophy of Science and Probably Approximately Correct (machine) learning. It's a cousin to the Looney Labs game "Zendo", but less fun to play with your friends. http://en.wikipedia.org/wiki/Zendo_(game) (By the way, playing this kind of game is excellent practice at avoiding confirmation bias.) The game has two players, who are asymmetric. One player plays Nature, and the other player plays Science. First Nature makes up a law, a specific Grand Unified Theory, and then Science tries to guess it. Nature provides some information about the law, and then Science can change their guess, if they want to. Science wins if it converges to the rule that Nature made up.

Kevin T. Kelly is a philosopher of science, and... (read 1276 more words →)

30th Soar workshop

Stigmergy and Pickering's Mangle

16y

This is a report from a LessWrong perspective, on the 30th Soar workshop. Soar is a cognitive architecture that has been in continuous development for nearly 30 years, and is in a direct line of descent from some of the earliest AI research (Simon's LT and GPS). Soar is interesting to LessWrong readers for two reasons:

Soar is a cognitive science theory, and has had some success at modeling human reasoning - this is relevant to the central theme of LessWrong, improving human rationality.
Soar is an AGI research project - this is relevant to the AGI risks sub-theme of LessWrong.

Where I'm coming from: I'm a skeptic about EY/SIAI dogmas that AI research is... (read 2250 more words →)

The Argument from Witness Testimony

16y

Stigmergy is a notion that an agent's behavior is sometimes best understood as coordinated by the agent's environment. In particular, social insects build nests, which have a recognizable standard pattern (different patterns for different species). Does the wasp or termite have an idea of what the standard pattern is? Probably not. Instead, the computation inside the insect is a stateless stimulus/response rule set. The partially-constructed nest catalyzes the next construction step.

An unintelligent "insect" clambering energetically around a convoluted "nest", with the insect's local perceptions driving its local modifications is recognizably something like a Turing machine. The system as a whole can be more intelligent than either the (stateless) insect or the (passive)... (read 874 more words →)