trentmkelly/LessWrong-43k huggingface dataset:
Meetup : Utrecht
by SoerenMind — 2014-04-20T10:14:21.859Z

Discussion article for the meetup : Utrecht

WHEN:
03 May 2014 05:00:00PM (+0200)

WHERE:
Utrecht, Catharijnensingel 49-A

A growing number of rationalists and effective altruists is joining us to share ideas and help each other to be rational, to improve themselves and to make the world a better place as effectively as possible.

Agenda

Amongst other things we will talk about the charity evaluator GiveWell (http://www.givewell.org/). GiveWell is looking for outstanding giving opportunities: where to give in order to do the most good per dollar or euro spent. How could that be possible? How does GiveWell (try to) do that?
If there is another topic you would like to present or discuss with the group, please add the topic here: https://docs.google.com/document/d/16bBtla1iVzkJjie-JK7Ozb9Ao8SbyJ9U924XyaEXTqY/edit .

There is room for your questions, personal discussions, smalltalk, etc.

Everyone is invited, and new people will be warmly welcomed!

We have a new location now. We're meeting at the headquaters of Seats2meet (Cyberdigma), which is in the Trindeborch building at Catharijnesingel 49-55 (7th floor). You can see the entry on this map
https://goo.gl/maps/q027I

If you have trouble finding us, for this time you can reach Jurjen at +31650495866, since I will be abroad.

Discussion article for the meetup : Utrecht
Southern California FAI Workshop
by Scott Garrabrant — 2014-04-20T08:55:19.467Z

This Saturday, April 26th, we will be holding a one day FAI workshop in southern California, modeled after MIRI's FAI workshops. We are a group of individuals who, aside from attending some past MIRI workshops, are in no way affiliated with the MIRI organization. More specifically, we are a subset of the existing Los Angeles Less Wrong meetup group that has decided to start working on FAI research together.

The event will start at 10:00 AM, and the location will be:

USC Institute for Creative Technologies
12015 Waterfront Drive
Playa Vista, CA 90094-2536.

This first workshop will be open to anyone who would like to join us. If you are interested, please let us know in the comments or by private message. We plan to have more of these in the future, so if you are interested but unable to makethis event, please also let us know. You are welcome to decide to join at the last minute. If you do, still comment here, so we can give you necessary phone numbers.

Our hope is to produce results that will be helpful for MIRI, and so we are starting off by going through the MIRI workshop publications. If you will be joining us, it would be nice if you read the papers linked to here, here, here, here, and here before Saturday. Reading all of these papers is not necessary, but it would be nice if you take a look at one or two of them to get an idea of what we will be doing.

Experience in artificial intelligence will not be at all necessary, but experience in mathematics probably is. If you can follow the MIRI publications, you should be fine. Even if you are under-qualified, there is very little risk of holding anyone back or otherwise having a negative impact on the workshop. If you think you would enjoy the experience, go ahead and join us.

This event will be in the spirit of collaboration with MIRI, and will attempt to respect their guidelines on doing research that will decrease, rather than increase, existential risk. As such, practical implementation questions related to making an approximate Bayesian reasoner fast enough to operate in the real world will not be on-topic. Rather, the focus will be on the abstract mathematical design of a system capable of having reflexively consistent goals, preforming naturalistic induction, et cetera.

Food and refreshments will be provided for this event, courtesy of MIRI.
Economics majors and earnings: further exploration
by JonahS — 2014-04-20T03:15:31.868Z

In Earnings of economics majors: general considerations I presented data showing that economics majors make substantially more money (20%-50%+) than majors in other liberal arts. I gave five hypotheses, each of which could partially account for the wage gap. These are possible differences between the majors in:

Human capital acquisition.

Acquisition of a desire to make money.

Pre-existing ability as measured by tests.

Pre-existing desire to make money.

Signaling.

I discussed a priori reasons for believing that they might be significant, and how one might go about testing the hypotheses and the extent to which they explain the wage gap.

Having examined available data, I believe that with the possible exception of #3, based on publicly available information, there's a huge amount of uncertainty as to the roles of these factors in explaining the wage gap. In many cases there is data suggesting the presence of effects, but the data is not robust and the sizes of the effects are entirely unclear. Furthermore, the hypotheses are not exhaustive: other factors (such as those mentioned at the very end of this post) plausibly play a role, making it difficult to reason in the fashion "factors A, B and C play very small roles, therefore factor D must play a large role."

I was originally hoping that there would be a simple, clearcut case for or against majoring in economics increasing earnings (relative to other liberal arts), but resolving the question would seem to be a major research project. Still, I hope that this post can help students who are contemplating majoring in economics or another liberal art get a feel for the "lay of the land," and some of the points therein may be actionable for particular individuals.

I'll address each hypothesis in turn.

This post is very long. If you're short on time or attention, consider scanning over the subtopic headings and reading the sections that look most interesting. As usual, I'd appreciate any relevant thoughts, particularly if you're a former economics major.

#1 Human capital acquisition

I was unable to find systematic research on the role of human capital acquisition in economics majors' greater earning power, and the available data is not robust.

There are major biases that make it difficult to infer the role of human capital acquisition in economics majors' higher earning power

...
Regret, Hindsight Bias and First-Person Experience
by Stabilizer — 2014-04-20T02:10:56.128Z

Here is an experience that I often have: I'm walking down the street, perfectly content and all of a sudden some memory pops into my stream of consciousness. The memory triggers some past circumstance where I did not act completely admirably. Immediately following this, there is often regret. Regret of the form like: "I should've studied harder for that class", "I should've researched my options better before choosing my college", "I should've asked that girl out", "I shouldn't have been such an asshole to her" and so on. So this is regret which is of the kind: "Well, of course, I should've done X. But I did Y. And now here I am."

This is classic hindsight bias. Looking back into the past, it seems clear what my course of action should've been. But it wasn't at all that clear in the past.

So, I've come up with a technique to attenuate this kind of hindsight-bias driven regret.

First of all, tune in to your current experience. What is it like to be here, right here and right now, doing the things you're doing. Start zooming out: think about the future and what you're going to be doing tomorrow, next week, next month, next year, 5 years later. Is it at all clear what choices you should make? Sure, you have some hints: take care of your health, save money, maybe work harder at your job. But nothing very specific. Tune in to the difficulties of carrying out even definitely good things. You told yourself that you'd definitely go running today, but you didn't. In first-person mode, it is really hard to know what do, to know how to do it and to actually do it.

Now, think back to the person you were in the past, when you made the choices that you're regretting. Try to imagine the particular place and time when you made that choice. Try to feel into what it was like. Try to color in the details: the ambient lighting of the room, the clothes you and others were wearing, the sounds and the smells. Try to feel into what was going on in your mind. Usually it turns out that you were confused and pulled in many different directions and, all said and done, you had to make a choice and you made one.

Now realize that back then you were facing exactly the kinds of uncertainties and confusions you are feeling now. In the first-person view there are no certainties; there are only half-baked ideas, hunches, gut feelings, mish-mash theories floating in your head, fragments of thi...
Meetup : Washington DC: Singing
by rocurley — 2014-04-19T16:43:46.786Z

Discussion article for the meetup : Washington DC: Singing

WHEN:
20 April 2014 03:00:00PM (-0400)

WHERE:
National Portrait Gallery, Washington, DC 20001, USA

We'll be meeting up to go singing!

Because this is probably not a good idea in the portrait gallery, we'll meet there, and then head out somewhere (Archives probably) after we've rendezvoused.

Discussion article for the meetup : Washington DC: Singing
[LINK] U.S. Views of Technology and the Future
by Gunnar_Zarncke — 2014-04-18T21:22:52.902Z

I just found this on slashdot:

"U.S. Views of Technology and the Future - Science in the next 50 years" by the Pew Research Center

This report emerges from the Pew Research Center’s efforts to understand public attitudes about a variety of scientific and technological changes being discussed today. The time horizons of these technological advances span from today’s realities—for instance, the growing prevalence of drones—to more speculative matters such as the possibility of human control of the weather.

This is interesting esp. in comparison to the recent posts on forecasting which focussed on expert forecasts.

What I found most notable was the public opinion on their use of future technology:

% who would do the following if possible...

50% ride in a driverless car

26% use brain implant to improve memory or mental capacity

20% eat meat grown in a lab

Don't they know Eutopia is Scary? I'd guess if these technologies really become available and are reliable only the elderly will be inable to overcome their preconceptions. And everybody will eat artificial meat if it is cheaper, more healthy and tastes the same (and the testers say confirm this).
[link] Guide on How to Learn Programming
by Peter Wildeford — 2014-04-18T17:08:36.485Z

I've recently seen a lot of interest in people who are looking to learn programming. So I put together a quick guide with lots of help from other people: http://everydayutilitarian.com/essays/learn-code

Let me know (via comments here or email - peter@peterhurford.com) if you try this guide, so I can get feedback on how it goes for you.

Also, feel free to also reach out to me with comments on how to improve the guide – I’m still relatively new to programming myself and have not yet implemented all these steps personally. I'd cross-post it here, but I want to keep the document up-to-date and it would be much easier to do that in just one place.
Weekly LW Meetups
by FrankAdamek — 2014-04-18T15:53:03.558Z

This meetup summary was posted to LW main on April 11th. The following week's summary is here.

New meetups (or meetups with a hiatus of more than a year) are happening in:

Las Vegas/Henderson, NV: 01 May 2014 06:00PM

Irregularly scheduled Less Wrong meetups are taking place in:

Atlanta: Problems With Friendly AI: A (non-technical) MIRI Book Review: 12 April 2014 07:00PM
Bratislava Meetup XII.: 28 April 2014 06:00PM
Canberra Meetup: Life hacks part 1: 12 April 2014 07:00PM
Frankfurt meetup: 17 April 2014 05:00PM
Hamburg - Report from Berlin: 26 April 2014 05:00PM
Helsinki Meetup: 13 April 2014 03:00PM
Ottawa meetup: 17 April 2014 07:00PM
Phoenix/ASU Less Wrong: 12 April 2014 10:00AM
Sydney Meetup - April: 23 April 2014 07:30PM
Urbana-Champaign Scantily Attended Meetups Rerun: 13 April 2014 12:00PM
Utrecht: Behavioural economics, game theory...: 19 April 2014 05:00PM

The remaining meetups take place in cities with regular scheduling, but involve a change in time or location, special meeting content, or simply a helpful reminder about the meetup:

[Berlin] Community Weekend in Berlin: 11 April 2014 04:00PM
Boston - Schelling Day: 16 April 2014 07:00PM
Brussels - all fun and games: 19 April 2014 12:00PM
[London] Socialising in the Sun, London 13/04: 13 April 2014 02:00PM
Salt Lake City, UT: Schelling Day: 20 April 2014 02:45PM
Washington DC Games meetup: 13 April 2014 03:00PM

Locations with regularly scheduled meetups: Austin, Berkeley, Berlin, Boston, Brussels, Cambridge UK, Canberra, Columbus, London, Madison WI, Melbourne, Mountain View, New York, Philadelphia, Research Triangle NC, Salt Lake City, Seattle, Toronto, Vienna, Washington DC, Waterloo, and West Los Angeles. There's also a 24/7 online study hall for coworking LWers.

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, build community, and have fun!

In addition to the handy sidebar of upcoming meetups, a meetup overview is posted on the front page every Friday. These are an attempt to collect information on all the meetups happening in upcoming weeks. The best way to get your meetup featured is still to use the Add New Meetup feature, but you'll also have the benefit of having your m...
AI risk, new executive summary
by Stuart_Armstrong — 2014-04-18T10:45:59.521Z

AI risk

Bullet points

By all indications, an Artificial Intelligence could someday exceed human intelligence.

Such an AI would likely become extremely intelligent, and thus extremely powerful.

Most AI motivations and goals become dangerous when the AI becomes powerful.

It is very challenging to program an AI with fully safe goals, and an intelligent AI would likely not interpret ambiguous goals in a safe way.

A dangerous AI would be motivated to seem safe in any controlled training setting.

Not enough effort is currently being put into designing safe AIs.

Executive summary

The risks from artificial intelligence (AI) in no way resemble the popular image of the Terminator. That fictional mechanical monster is distinguished by many features – strength, armour, implacability, indestructability – but extreme intelligence isn’t one of them. And it is precisely extreme intelligence that would give an AI its power, and hence make it dangerous.

The human brain is not much bigger than that of a chimpanzee. And yet those extra neurons account for the difference of outcomes between the two species: between a population of a few hundred thousand and basic wooden tools, versus a population of several billion and heavy industry. The human brain has allowed us to spread across the surface of the world, land on the moon, develop nuclear weapons, and coordinate to form effective groups with millions of members. It has granted us such power over the natural world that the survival of many other species is no longer determined by their own efforts, but by preservation decisions made by humans.

In the last sixty years, human intelligence has been further augmented by automation: by computers and programmes of steadily increasing ability. These have taken over tasks formerly performed by the human brain, from multiplication through weather modelling to driving cars. The powers and abilities of our species have increased steadily as computers have extended our intelligence in this way. There are great uncertainties over the timeline, but future AIs could reach human intelligence and beyond. If so, should we expect their power to follow the same trend? When the AI’s intelligence is as beyond us as we are beyond chimpanzees, would it dominate us as thoroughly as we dominate the great apes?

There are more direct reasons to suspect that a true AI would be...
Bostrom versus Transcendence
by Stuart_Armstrong — 2014-04-18T08:31:09.399Z

Nick Bostrom takes on the facts, the fictions and the speculations in the movie Transcendence:

Could you upload Johnny Depp's brain? Oxford Professor on Transcendence

How soon until machine intelligence? Oxford professor on Transcendence

Would you have warning before artificial superintelligence? Oxford professor on Transcendence

Oxford professor on Transcendence: how could you get a machine intelligence?
How long will Alcor be around?
by Froolow — 2014-04-17T15:28:46.763Z

The Drake equation for cryonics is pretty simple: work out all the things that need to happen for cryonics to succeed one day, estimate the probability of each thing occurring independently, then multiply all those numbers together. Here’s one example of the breakdown from Robin Hanson. According to the 2013 LW survey, LW believes the average probability that cryonics will be successful for someone frozen today is 22.8% assuming no major global catastrophe. That seems startlingly high to me – I put the probability at at least two orders of magnitude lower. I decided to unpick some of the assumptions behind that estimate, particularly focussing on assumptions which I could model.

EDIT: This needs a health warning; here be overconfidence dragons. There are psychological biases that can lead you to estimating these numbers badly based on the number of terms you're asked to evaluate, statistical biases that lead to correlated events being evaluated independently by these kind of models and overall this can lead to suicidal overconfidence if you take the nice neat number these equations spit out as gospel.

Every breakdown includes a component for ‘the probability that the company you freeze with goes bankrupt’ for obvious reasons. In fact, the probability of bankruptcy (and global catastrophe) are particularly interesting terms because they are the only terms which are ‘time dependant’ in the usual Drake equation. What I mean by this is that if you know your body will be frozen intact forever, then it doesn’t matter to you when effective unfreezing technology is developed (except to the extent you might have a preference to live in a particular time period). By contrast, if you know safe unfreezing techniques will definitely be developed one day it matters very much to you that it occurs sooner rather than later because if you unfreeze before the development of these techniques then they are totally wasted on you.

The probability of bankruptcy is also very interesting because – I naively assumed last week – we must have excellent historical data on the probability of bankruptcy given the size, age and market penetration of a given company. From this – I foolishly reasoned – we must be able to calculate the actual probability of the ‘bankruptcy’ component in the Cryo-Drake equatio...
Meetup : Urbana-Champaign: Planning and Re-planning
by Manfred — 2014-04-17T05:56:36.094Z

Discussion article for the meetup : Urbana-Champaign: Planning and Re-planning

WHEN:
20 April 2014 12:00:00PM (-0500)

WHERE:
412 W. Elm St, Urbana, IL

When things get complicated enough, you have to plan them in advance or they fail. You need blueprints and logistics before you can build a skyscraper. On a personal level, good plans improve our chances of success at anything we can make a plan for.

One trouble with plans is that once you've made them they're sticky. What kind of life to lead, what to study, when to marry - we inherit plans about these things.from the past and we don't always rethink them when appropriate.

Discussion article for the meetup : Urbana-Champaign: Planning and Re-planning
The usefulness of forecasts and the rationality of forecasters
by VipulNaik — 2014-04-17T03:49:09.378Z

Suppose we have a bunch of (forecasted value, actual value) pairs for a given quantity (with different measured actual values at different times). An example would be GDP growth rate measures in different years. For each year, we have a forecasted value and an actual value. So we have a bunch of (forecasted value, actual value) pairs, one for each year. How do we judge the usefulness of the forecasts at predicting the value. Here, we discuss a few related measures: accuracy, bias, and dependency (specifically, correlation).

Accuracy

The accuracy of a forecast refers to how far, on average, the forecast is from the actual value. Two typical ways of measuring the accuracy are:

Compute the mean absolute error: Take the arithmetic mean (average) of the absolute values of the errors for each forecast.

Compute the root mean square error: Take the square root of the arithmetic mean of the squares of the errors.

The size of the error, measured in either of these ways, is a rough estimate of how accurate the forecasts are in general (the larger the error, the less accurate the forecast). Note that an error of zero represents a perfectly accurate forecast.

Note that this is a global measure of accuracy. But it may be the case that forecasts are more accurate when the actual values are at a particular level, and less accurate when they are at a different level. There are mathematical models to test for this.

Bias

When we ask whether the forecast is biased, we're interested in knowing whether the size of the error in the positive direction systematically exceeds the size of the error in the negative direction. One method for estimating this is to compute the mean signed difference (i.e., take the arithmetic mean of errors for individual forecasts without taking the absolute value). If this comes out as zero, then the forecasting is unbiased. If it comes out as positive, the forecasts are biased in the positive direction, whereas if it comes out as negative, the forecasts are biased in the negative direction.

The above is a start, but it's not good enough. In particular, the error could come out nonzero simply because of random fluctuations rather than bias. We'd need to complicate the model somewhat in order to make probabilistic or quantitative assessments to get a sense of whether or how the forecasts are really biased.

Again, the above is a global measure of bias. But it ...
LINK-Cryonics Institute documentary
by polymathwannabe — 2014-04-16T22:44:41.293Z

"WE WILL LIVE AGAIN looks inside the unusual and extraordinary operations of the Cryonics Institute. The film follows Ben Best and Andy Zawacki, the caretakers of 99 deceased human bodies stored at below freezing temperatures in cryopreservation. The Institute and Cryonics Movement were founded by Robert Ettinger who, in his nineties and long retired from running the facility, still self-publishes books on cryonics, awaiting the end of his life and eagerly anticipating the next."

http://www.iht.com/2014/04/15/we-will-live-again/
Meetup : Ugh Fields
by evand — 2014-04-16T16:32:51.417Z

Discussion article for the meetup : Ugh Fields

WHEN:
17 April 2014 07:00:00PM (-0400)

WHERE:
2411 N Roxboro St 27704

We'll be discussing Ugh Fields: what they are, how they keep you from accomplishing stuff, and how to recognize and reduce them.
As always, RSVPs are appreciated but not required. We encourage you to show up around 7, and we'll start on-topic content at 7:30.
If you're feeling energetic about it, there's a relevant article.
Afterwards, we will probably meander over to Fullsteam and be sociable.

Discussion article for the meetup : Ugh Fields