trentmkelly/LessWrong-43k huggingface dataset:
Upcoming meet-ups:
by AnnaSalamon — 2011-06-11T22:16:09.641Z

There are upcoming irregularly scheduled meet-ups in:

DC: Sunday June 5 at 1pm

Edinburgh: Saturday June 4 at 2pm

Fort Collins, Colorado: Wednesday June 8 at 7pm

Houston: Saturday June 4 at 2pm

London: Sunday June 5 at 2pm

Ottawa: Thurs June 9 at 7pm (+ an Ottawa Bayesian statistics group)

West LA: Wednesday June 8th at 7pm

Cities with regularly scheduled meetups: Austin, Berkeley, Cambridge, MA, Irvine, Mountain View, New York, San Francisco, Seattle, Toronto.

If you'd like to talk with other LW-ers face to face, and there is no meetup in your area, consider starting your own meetup; it's easy (more resources here). Check one out, stretch your rationality skills, and have fun!

If you missed the deadline and wish to have your meetup featured, add a comment and send me a PM.

Meet-ups should be posted in the discussion session; I will then make a promoted post "upcoming meetups" post every Friday that links to every meet-up that has been planned for the next two weeks. Please let me know if your meetup is omitted.

Please note that for your meetup to appear in the weekly meetups feature, you need to post about your meetup before the Friday before your meetup!

If you check Less Wrong irregularly, consider subscribing to one or more city-specific mailing list in order to be notified when an irregular meetup is happening: London, Chicago, Southern California (Los Angeles/Orange County area), St. Louis, Ottawa, Helsinki, Melbourne.
Unconditionally Convergent Expected Utility
by DanielLC — 2011-06-11T20:00:23.355Z

Expected utility can be expressed as the sum ΣP(Xn)U(Xn). Suppose P(Xn) = 2-n, and U(Xn) = (-2)n/n. Then expected utility = Σ2-n(-2)n/n = Σ(-1)n/n = -1+1/2-1/3+1/4-... = -ln(2). Except there's no obvious order to add it. You could just as well say it's -1+1/2+1/4+1/6+1/8-1/3+1/10+1/12+1/14+1/16-1/5+... = 0. The sum depends on the order you add it. This is known as conditional convergence.

This is clearly something we want to avoid. Suppose my priors have an unconditionally convergent expected utility. This would mean that ΣP(Xn)|U(Xn)| converges. Now suppose I observe evidence Y. ΣP(Xn|Y)|U(Xn)| = Σ|U(Xn)|P(Xn∩Y)/P(Y) ≤ Σ|U(Xn)|P(Xn)/P(Y) = 1/P(Y)·ΣP(Xn)|U(Xn)|. As long as P(Y) is nonzero, this must also converge.

If my prior expected utility is unconditionally convergent, then given any finite amount of evidence, so is my posterior.

This means I only have to come up with a nice prior, and I'll never have to worry about evidence braking expected utility.

I suspect that this can be made even more powerful, and given any amount of evidence, finite or otherwise, I will almost surely have an unconditionally convergent posterior. Anyone want to prove it?

Now let's look at Pascal's Mugging. The problem here seems to be that someone could very easily give you an arbitrarily powerful threat. However, in order for expected utility to converge unconditionally, either carrying out the threat must get unlikely faster than the disutility increases, or the probability of the threat itself must get unlikely that fast. In other words, either someone threatening 3^^^3 people is so unlikely to carry it out to make it non-threatening, or the threat itself must be so difficult to make that you don't have to worry about it.
Ottawa LW meetup, June 16, 7pm; two Bayesian Conspiracy sessions
by Cyan — 2011-06-11T18:53:29.586Z

Less Wrong meeting:

Date: Thursday June 16, 7:00pm 'til whenever.

Venue: Fox and Feather, upstairs, possibly in back room #1 if it's free. Look for the LW sign.

Bayes study group: Anyone in the region interested in learning how to do Bayesian statistics is welcome to join us. We'll be using the statistical package R (http://cran.r-project.org/) as a platform, so bring your laptop if you have one. We're currently covering the binomial model with its conjugate prior, the beta distribution.

Date: Thursday June 16, 9:00am to 10:30am. NB: 9 in the morning.

Venue: Jeanne Mance Building, Tunney's Pasture. Meet me in the lobby.

Bayes study group: This session was to will run in parallel but slightly delayed relative to the sessions at Tunney's Pasture, but now it's caught up.

Date: Tuesday June 14 21, 9:30pm

Venue: wmiles's house; join the Google group for the address.
Q&A with Stan Franklin on risks from AI
by XiXiDu — 2011-06-11T15:22:10.495Z

[Click here to see a list of all interviews]

I am emailing experts in order to raise and estimate the academic awareness and perception of risks from AI.

Stan Franklin, Professor, Computer Science
W. Harry Feinstone Interdisciplinary Research Professor
Institute for Intelligent Systems
FedEx Institute of Technology
The University of Memphis

The Interview:

Q: What probability do you assign to the possibility of us being wiped out by badly done AI?

Stan Franklin: On the basis of current evidence, I estimate that probability as being tiny. However, the cost would be so high, that the expectation is really difficult to estimate.

Q: What probability do you assign to the possibility of a human level AI, respectively sub-human level AI, to self-modify its way up to massive superhuman intelligence within a matter of hours or days?

Stan Franklin: Essentially zero in such a time frame. A lengthy developmental period would be required. You might want to investigate the work of the IEEE Technical Committee on Autonomous Mental Development.

Q: Is it important to figure out how to make AI provably friendly to us and our values (non-dangerous), before attempting to solve artificial general intelligence?

Stan Franklin: Proofs occur only in mathematics. Concern about the "friendliness" of AGI agents, or the lack thereof, has been present since the very inception of AGI. The 2006 workshop <http://www.agiri.org/forum/index.php?act=ST&f=21&t=23>, perhaps the first organized event devoted to AGI, included a panel session entitled How do we more greatly ensure responsible AGI? Video available at <http://video.google.com/videoplay?docid=5060147993569028388> (There's also a video of my keynote address.) I suspect we're not close enough to achieving AGI to be overly concerned yet. But that doesn't mean we shouldn't think about it. The day may well come.

Q: What is the current level of awareness of possible risks from AI within the artificial intelligence community, relative to the ideal level?

Stan Franklin: I'm not sure about the ideal level. Most AI researchers and practitioners seem to devote little or no thought at all to AGI. Though quite healthy and growing, the AGI movement is still marginal within the AI community. AGI has ...
[SEQ RERUN] Scope Insensitivity
by Tyrrell_McAllister — 2011-06-11T01:08:46.996Z

Today's post, Scope Insensitivity, was originally published on 14 May 2007. A summary (taken from the LW wiki):

The human brain can't represent large quantities: an environmental measure that will save 200,000 birds doesn't conjure anywhere near a hundred times the emotional impact and willingness-to-pay of a measure that would save 2,000 birds.

Discuss the post here (rather than in the comments to the original post).

This post is part of the Rerunning the Sequences series, where we'll be going through Eliezer Yudkowsky's old posts in order so that people who are interested can (re-)read and discuss them. The previous post was Third Alternatives for Afterlife-ism, and you can use the sequence_reruns tag or rss feed to follow the rest of the series.

Sequence reruns are a community-driven effort. You can participate by re-reading the sequence post, discussing it here, posting the next day's sequence reruns post, or summarizing forthcoming articles on the wiki. Go here for more details, or to have meta discussions about the Rerunning the Sequences series.
General Bitcoin discussion thread (June 2011)
by SilasBarta — 2011-06-10T23:21:21.932Z

We've started a habit of creating periodic Bitcoin threads to confine discussion thereof to those threads and prevent excessive proliferation of Bitcoin topics in the discussion section. Here is a link to the last one, which links the other discussions. Lot's to talk about, and another bounce in Bitcoin's value (up to 33 then down to 24), so share your links and thoughts!
Outreach to probably compatible groups?
by NancyLebovitz — 2011-06-10T19:46:37.176Z

At Balticon, there was a table for humanists, the Ethical Society, and skeptics. I told one of the folks there about Less Wrong-- he seemed interested and I'll check back with him, but he'd never heard of it at all-- it took a little time to disambiguate between Less Wrong and what he heard as a human being named Les Wrong.

Anyway, what do you think of doing outreach to fairly compatible groups (I'd add Unitarians to the list)? And if so, what would be good methods?
A Philosophical Treatise of Universal Induction (Link)
by XiXiDu — 2011-06-10T18:53:19.630Z

Abstract: Understanding inductive reasoning is a problem that has engaged mankind for thousands of years. This problem is relevant to a wide range of fields and is integral to the philosophy of science. It has been tackled by many great minds ranging from philosophers to scientists to mathematicians, and more recently computer scientists. In this article we argue the case for Solomonoff Induction, a formal inductive framework which combines algorithmic information theory with the Bayesian framework. Although it achieves excellent theoretical results and is based on solid philosophical foundations, the requisite technical knowledge necessary for understanding this framework has caused it to remain largely unknown and unappreciated in the wider scientific community. The main contribution of this article is to convey Solomonoff induction and its related concepts in a generally accessible form with the aim of bridging this current technical gap. In the process we examine the major historical contributions that have led to the formulation of Solomonoff Induction as well as criticisms of Solomonoff and induction in general. In particular we examine how Solomonoff induction addresses many issues that have plagued other inductive systems, such as the black ravens paradox and the confirmation problem, and compare this approach with other recent approaches.

Link: mdpi.com/1099-4300/13/6/1076/

Download PDF Full-Text: mdpi.com/1099-4300/13/6/1076/pdf

Authors: Samuel Rathmanner and Marcus Hutter

Published: 3 June 2011

Via: vetta.org/2011/06/treatise-on-universal-induction/
Scientific misconduct misdiagnosed because of scientific misconduct
by GLaDOS — 2011-06-10T14:49:13.485Z

Please remember to have no heroes or villains, but this just looks plain bad to be honest. I'm lowering my estimation of the quality of Stephen J. Gould's work in this area.

USA today:

The late scientific icon, Stephen Jay Gould, botched and perhaps faked his critique of a racist 19th-Century scientist's skull collection, suggests a second look at his efforts.

CAPTION

UPenn

In a 1978 Science paper, Gould (1941 - 2002) , reported that the Samuel George Morton (1799-1851), "a prominent Philadelphia physician," had mis-measured the cranial capacities of his 1,000-skull "American Golgotha" collection gathered from around the world, to suit his racist beliefs. The finding led to one of Gould's best-known books, The Mismeasure of Man, a critique of scientific racism.

"Morton is now viewed as a canonical example of scientific misconduct. But did Morton really fudge his data?," asks a PLoS Biology study led by anthropologist Jason Lewis of Stanford University. "Are studies of human variation inevitably biased, as per Gould, or are objective accounts attainable, as Morton attempted?"

So, the study team remeasured the skulls collected by Morton, now owned largely by the University of Pennsylvania Museum of Archaeology and Anthropology in Philadelphia.

Overall, they find, Morton did make mistakes in measuring skull capacity (he first stuffed them with seeds, and later lead shot to measure their brain size). But the mistakes were random. The random mistakes didn't favor any racial theory of larger brain sizes for white people over others.

"Given how long Gould's work has been criticized in this arena, I'm a little surprised that it took this long for the work to be done to write this article," says the University of Texas's David Prindle, author of Stephen Jay Gould and the Politics of Evolution. "People who dislike Gould's work will likely go on disliking him even more after this article. People who are fans of his writing will likely go on supporting his views."

Haha. Humans.

The paper itself:

In reevaluating Morton and Gould, we do not dispute that racist views were unfortunately common in 19th-century science or that bias has inappropriately influenced research in some cases. Furthermore, studies have demonstrated that modern human variation is generally continuous, rather than discrete or ''racial,'' and that most variation in modern humans is within, rather th

...
Help: Writing Marvin Minsky
by XiXiDu — 2011-06-10T12:45:03.421Z

I want to raise awareness of risks from AI and the challenges to mitigate those risks by writing experts and asking them questions. The e-Mail below is a template. Please help me improve it and to devise more or better questions.

Dear Mr Minsky,

I am currently trying to learn more about risks from artificial intelligence [1]. In the course of this undertaking I plan to ask various experts and influencers about their opinion. Consequently I am curious about your opinion as a noted author and cognitive scientist in the field of artificial intelligence. But first I want to apologize if I intrude on your privacy, it is not my intention to offend you or to steal your time. If that is the case, please just ignore the rest of this e-Mail.

One of the leading textbooks in artificial intelligence, 'AI: A Modern Approach' [2], states:

Omohundro (2008) hypothesizes that even an innocuous chess program could pose a risk to society. Similarly, Marvin Minsky once suggested that an AI program designed to solve the Riemann Hypothesis might end up taking over all the resources of Earth to build more powerful supercomputers to help achieve its goal. The moral is that even if you only want you program to play chess or prove theorems, if you give it the capability to learn and alter itself, you need safeguards.

In this regard I would like to draw your attention to the Singularity Institute for Artificial Intelligence (SIAI) [3] and their mission to solve the problem of Friendly AI [4]. One example of the research interests of the SIAI is a reflective decision theory [5] of self-modifying decision systems. The SIAI does believe that "it is one of the many fundamental open problems required to build a recursively self-improving [6] Artificial Intelligence with a stable motivational system." [7]

With this in mind, I would like to ask you the following questions:

Do you agree that risks from artificial intelligence have to be taken very seriously?

Is it important to raise awareness of those risks within the artificial intelligence community?

Should we figure out how to make AI provably friendly (non-dangerous [9]), before attempting to solve artificial general intelligence?

How do risks from AI compare to other existential risks, e.g. advanced nanotechnology?

What probability do you assign to the possibility of us being wiped out by badly done

...
Simulation Argument errors
by Will_Newsome — 2011-06-10T12:15:08.254Z

I was reading the simulation argument again for kicks and a few errors tripped me up for a bit. I figured I'd point them out here in case anyone's interested or noticed the same problems. If I made a mistake in my analysis please let me know so I can promptly put a bolded warning saying so at the top of this article. (I do not endorse the method of thinking that involves naive anthropics or probabilities of simulation but nonetheless I am willing to play with that framework sometimes for communication's sake.)

We can reasonably argue that all three of the propositions at the end of section 4 of the paper, titled "The core of the simulation argument", are false. Most human-level technological civilizations can survive to reach a posthuman stage (fp=.9), and want to (fI=.9) and are able to run lots of ancestor simulations; and yet there can conceivably be no observers with human-type experiences that live in simulations (fsim=0). Why? Because not all human-level technological civilizations are human technological civilizations; it could easily be argued that most aren't. Human technological civilizations could be part of the fraction of human-level technological civilizations that do not survive to reach a posthuman stage, or survive but do not want to run lots of ancestor simulations. Thus there will be no human ancestor-simulations even if there are many many alien ancestor-simulations who humans do not share an observer moment reference class with.

Nitpicking? Not quite. This forces us to change "fraction of all human-level technological civilizations that survive to reach posthuman stage" to "probability of human civilization reaching posthuman stage", but then some of the discussion in the paper's Interpretation section (section 6) sounds pretty weird because it's comparing human civilization to other human-level civilizations. The equivocation on "posthuman" causes various other statements and passages in the original article to be false-esque or ambiguous, and these would need to be changed. fsim should be changed to fancestor_sim as well; we might be in non-ancestor simulations. The fraction of us in ancestor-simulations is just one possible lower bound for the fraction of us in simulations generally. Luckily, besides that error I think the paper mostly avoids insinuating that we are unlikely to be in a simulation...
Bangalore Meetup: 19th June 4 pm
by  — 2011-06-10T11:56:52.994Z

This is the second meetup being organized in Bangalore.

The previous one had two attendees and at least 6 more people in Bangalore and a few in other cities have expressed an interest for another one in the comments. Since the discussions petered out without reaching a consensus on the date for the next one, I'm going ahead and proposing 19th June 4 pm at Cafe Coffee Day on Brigade Road (this is the one on the Brigade Road/Magrath Road junction - close to Eva Mall.)

Do respond in the comments if you'd like the date/time/place to be changed. I hope there'll be a good turn out this time!
Edinburgh LW meetup, as usual
by sark — 2011-06-10T10:17:52.752Z

Saturday 2pm at the Delhi cafe

The reason why this announcement is so minimalistic is that it's bowing in humility to the yet-to-be-born Once In A Month Meetup.

Here's the story: last week, orthonormal suggest we create a Schelling point around meetups at the beginning of each month. Just so that people would then expect lots of each other to come, and hence they would in fact come. But this is only possible if we distinguish that meetup from the others in the month you see?

Make no mistake, this meetup will also be attended by stellar folks, it just won't be as great the July 2nd one.

See you there!
What would defuse unfriendly AI?
by asr — 2011-06-10T07:27:12.623Z

It seems to be a widely held belief around here that unfriendly artificial general intelligence is dangerous, and that (provably) friendly artificial general intelligence is the soundest counter to it.
But I'd like to see some analysis of alternatives. Here are some possible technical developments. Would any of these defuse the threat? How much would they help?

A tight lower bound on the complexity of SAT instances. Suppose that P != NP, and that researchers develop an algorithm for solving instances of Boolean satisfiability that is optimal in terms of asymptotic complexity, but far from efficient in practice.

The opposite: a practical, say, quartic-time SAT algorithm, again with a proof that the algorithm is optimal.

High-quality automated theorem proving technology, that's not self-modifying except in very narrow ways.

Other special-purpose 'AI', such as high-quality natural-language processing algorithms that aren't self-modifying or self-aware. For example, suppose we were able to do language-to-language translation as well as bilingual but not-very-smart humans.

Robust tools for proving security properties of complex programs. "This program can only produce output in the following format or with the following properties and cannot disable or tamper with the reference monitor or operating systems."

Are there other advances in computer science that might show up within the next twenty years, that would make friendly-AI much less interesting?
Would anything on this list be dangerous? Obviously, efficient algorithms for NP-complete problems would be very disruptive. Nearly all of modern cryptography would become irrelevant, for instance.
Memory, Spaced Repetition and Life
by Duke — 2011-06-10T00:07:04.447Z

I have made the case that with the advent of the internet went the need to memorize anything. Why worry about memorizing when I'll never be tested for a grade and can access knowledge nearly instantaneously? As well, I reasoned, I have probably already memorized everything I need to. I focused my time instead on learning thinking techniques, such as Bayesian calculations, expected value calculations and various things for improving emotional control.

But after reading this a couple months back I decided to experiment with Anki, a digital flashcard program which exploits a cognitive phenomenon called the Spacing Effect by implementing a memorization technique called Spaced Repetition. The Spacing Effect is the widely observed tendency for people to recall information better when studied a few times over a long period than when studied many times over a short period. Balota et al (2007):

Spacing effects occur across domains (e.g., learning perceptual motor tasks vs. learning lists of words), across species (e.g., rats, pigeons, and humans), across age groups and individuals with different memory impairments, and across retention intervals of seconds to months.

Gwern analogizes the spacing effect with radioactive decay:

You can think of the ‘forgetting curve’ as being like a chart of radioactive half-lives: each review bumps your memory up in strength 50% of the chart, say, but review doesn’t do very much in the early days because the memory simply hasn’t decayed very much! (Chart)

One consequence of the spacing effect is that cramming is useful for recalling things shortly after memorizing them; however, if those crammed memories are not eventually refreshed then they are likely to decay to nothing. From this observation came Spaced Repetition: a memorization technique using flashcards (usually) shown at increasing intervals of time to optimize the relationship between number of reviews and strength of memory. The PC explosion was a boon to Spaced Repetition since storing and showing flashcards as well as physically calculating their frequencies were delegated to the computer. The program Anki, for instance, permits the user to generate flashcard decks, specify study session length and frequency, specify how many new cards are introduced per session and specify the frequency of the cards based on the user's input. Hard material is sh...