trentmkelly/LessWrong-43k huggingface dataset:
Please Take the 2018 Effective Altruism Survey!
by Peter Wildeford — 2018-05-02T07:58:29.016Z

This year, the EA Survey volunteer team is proud to announce the launch of the 2018 Effective Altruism Survey.

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PLEASE TAKE THIS SURVEY NOW BY CLICKING HERE :)

(If you want to share the survey with others, please use this fancy share link with referral tracking:

https://www.surveymonkey.com/r/3HYW9MW)

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What is this?

This is the fourth EA survey we've done, coming hot off the heels of the 2017 EA Survey (announcement here, analysis here), the 2015 EA Survey (announcement here, analysis here), and the 2014 EA Survey (announcement here, analysis here).

We hope this survey will produce very useful data on the growth and changing attitudes of the EA Community. In addition to capturing a snapshot of what EA looks like now, we also intend to do longitudinal analysis to see how our snapshot has been changing.

We're also using this as a way to build up the online EA community, such as featuring people on a global map of EAs and with a list of EA Profiles. This way more people can learn about the EA community. We will ask you in the survey if you would like to join us, but you do not have to opt-in and you will be opted-out by default.

Who should take this survey?

Anyone who is reading this should take this survey, even if you don't identify as an "effective altruist".

How does the survey work?

All questions are optional (apart from one important question to verify that your answers should be counted). Most are multiple choice and the survey takes around 10-20 minutes.

At the end of the survey there is an 'Extra Credit' section with some more informal questions and opportunities for comment - definitely feel free to skip these questions.

All results will be aggregated, anonymized, and made available to members of the EA community, so we can better share useful knowledge among each other. Within the survey, you’ll have the option to publicly share selected information about yourself in several EA venues, if you opt in.

Who is behind this?

The annual EA Survey is conducted by

Rethink Charity

, with support and assistance from several EA community organizations intending to help the community better understand our actions, values, demographics, and ideas.
Brief comment on frontpage/personal distinction
by Ben Pace — 2018-05-01T18:53:19.250Z

I recently moved a post back from frontpage to personal blog, a decision which was followed by confusion and had some pushback. Rather than have discussion on the post about the site (i.e. about not-the-post), I've copied my comment here instead.

A short background on this particular guideline (not having meta/community discussion on frontpage) and its purpose:

The purpose of the rule is to make sure we have a clear, well-defined space that users can go to and not expect to discover internal discussion or political discussion.

To contrast, my facebook wall often has interesting discussion followed by AGH ANGSTY TRIBAL CONFLICT, and if you think of Frontpage as analogous to how academic physics has journals where the best work goes in, it would be bad to also have internal / political discussion in those.

And to clarify, this isn't at all a question of quality. Resolving tribal conflict is an important part of rationality. But there are many many many many excellent posts that do not belong in Frontpage.

With that common knowledge, I read the structure of this post as being

Observation about the community
Laying out model of what's going on
Suggesting a different solution for the community

Which is a fine and good post. But I think it addresses a problem that many communities don't have, and so is fairly this-community-specific.

To give further information: a solution that would be totally fine-and-dandy would be to take the model of communities, status and reinforcement and write it as its own post on the Frontpage, then separately write a personal blog post on using to analyse this community. That way it could contribute to the ongoing building of knowledge while not being very context heavy (e.g. someone else could build on the theory alone), and also discuss the important community aspects.

People will naturally tend to read the social stuff a lot. I think this rule pushes against the direction of entropy where this is everything on LessWrong, rather than a thing that happens on LessWrong but not the point of LessWrong.
Eight political demands that I hope we can agree on
by ChristianKl — 2018-05-01T16:59:09.865Z

Scott Alexander wrote in Book Review: History of the Fabian Society about how the Fabian society had eight political thesis that they agreed on.

I want to propose eight points that I think we can agree as a rationality movement about:

1. We want public policy that's backed up by empiric evidence. We want a government that runs controlled trials to find out what policies work.

2. We want that government bureaucrats who make predictions about the future makes them in a way where the accuracy of their predictions gets measured.

3. We want a policy that funds AI safety research and that's a bit cautious about AI.

4. We want government money to go into anti-aging research of the kind that SENS does.

5. We want less bureaucracy around running scientific studies so that nightmares don't have to happen

6. We want the right not to have to endure what amounts to torture at end of our lives

7. We want to end the War on Drugs

8. We want that the FDA switching from using p-values to using better statistical models

Do you think one of those points isn't consensus in our community? Do you think there are other political demands where we have consensus?

(Please avoid talking about political issues where you don't think there's consensus in our community in this thread)
Open Thread May 2018
by Elo — 2018-05-01T06:23:37.468Z

If it’s worth saying, but not worth its own post, then it goes here.

Notes for future OT posters:

Check if there is an active Open Thread before posting a new one (use search for Open Thread ).

Monthly open threads seem to get lost and maybe we should switch to fortnightly.

what accomplishments are you celebrating from the last month?
Ikaxas' Hammertime Final Exam
by Vaughn Papenhausen — 2018-05-01T03:30:11.668Z

Here are my answers to Alkjash's Hammertime Final Exam. I have selected the difficulty level Steel Cudgel of the Lion.

1. Rationality Technique: Ass-in-Gear Mode

This might also be called "buckling-down mode." It's the feeling you get when there is a Yoda Timer running. It's the feeling of being completely focused on the task at hand, and wasting no mental effort on other thoughts. I find this mode easiest to engage when there is a Yoda Timer running, or there is some deadline pressure, but it is possible to engage it when these conditions do not apply, by noticing what it feels like when a Yoda Timer is running and then bringing yourself into that cognitive state at some other time. I'm very productive in this mode, but it's taxing to keep up for long periods. I definitely don't claim credit for this idea, but I claim that the main benefit of Yoda Timers is to make it easier to reach this cognitive state.

3. Cognitive defect, bias, or blind spot: Settled Opinions

I have long felt a strong desire to have settled opinions on things, by which I mean opinions that I have considered carefully, that I can then cache and not have to think about again. I suspect I'm not alone in this (though I'm wary of claiming that it is a universal desire). I think it's close to a truism in this community that impulse should be fought (see the How to Actually Change Your Mind sequence). However, I think there may be a reason why it's actually desirable to have settled opinions (though I don't think this reason yet convinces me that it's a good idea to have settled opinions): having settled opinions allows for temporal coordination between different versions of oneself. If one's views are in constant flux, then it's difficult to plan for the future, since by the time the future arrives, one's values might be radically different. This is analogous to Sunk Cost Faith. So while I currently think it's a good idea to keep one's views open for revision, I think there's a chance that doing so might be knocking down Chesterton's fence, and that it's a good idea to aim for settled beliefs.
Thoughts on the REACH Patreon
by Raemon — 2018-04-30T20:51:11.407Z

Note: My views have updated since this post, but I haven't yet written them up.

I moved from NY to the Bay several months ago.

In many senses, the Berkeley community is much bigger than NYC. There's a few hundred members instead of around 30. I had several friends in the Bay before moving here, and have made more since arriving.

But, it didn't actually feel like home to me until a couple weeks ago, at one of the weekly meetups at the new community center.

These are my thoughts about the REACH (Rationality and Effective Altruism Community Hub) space, and what considerations I think are relevant for funding it. It has a Patreon which is currently hitting the "juuust enough money that it might possibly work so long as other things go right" threshold. But it doesn't really have enough funding to reliably break even, let alone thrive.

tldr: I think there are lot of reasons you might want to help fund REACH, both from an effective altruism perspective, and from a "just buy some nice things for yourself" perspective.

...

Epistemic Status: I'm pretty biased in favor of REACH, and much of my reasoning was at least a bit motivated. I expect to make a lot of use of the infrastructure there, so my thoughts here are a bit self-serving.

I’ve attempted to account for this in my writing of this, and am still fairly confident that there’s something important going on here.

...

Table of Contents

Ray’s Opinionated Conception of Meetups
Mechanics of Berkeley Meetup Brain Drain
Enter REACH
Frameworks of Funding

Buying Nice Things vs Effective Altruism
Nice Things and Homemade Prices
Okay, but is this the right nice thing?
The Case for Impact

Measuring Intangibles

Agency Ladder
Water Coolers and Campuses

Matching Funds
In Closing...

Ray’s Opinionated Conception of Meetups

In NYC, meetup means "someone runs an hour long presentation, moderated discussion or workshop." Every week, you can show up to a public meetup. There will be content to learn or practice, and people you can hangout with. It's structured such that if you're shy, or if not as many good conversationalists show up that week, or if you just prefer structure, there's something to learn and engage you.

Meanwhile, if you care more about hanging out with the regulars than listening to a talk, you're free to just arrive later in the evening....
Prediction Contest 2018
by jbeshir — 2018-04-30T18:26:32.104Z

Summary: Make predictions on all the listed predictions before the end of June 2018, and if your predictions are the best you'll win $200 after they all settle in January.

About

This is happening! Motivations discussed in the earlier post here, I'm running a prediction contest for the rationalist and EA communities. There are 20 predictions- seven about world politics over the next year, five about technology, six about the upcoming year for EA organisations, and two about rationalist websites, for a mix of topics with a lean towards things it would be helpful to know about. They were inspired by a variety of suggested sources- particularly Socratic Form Microblogging's world politics predictions, Slate Star Codex's predictions for the year and the SSC community's reddit thread for predictions, and a handful of EA organisation blog posts about the past and their future plans.

How to Enter

Each entry in the list below goes to a prediction on PredictionBook. Using a new or existing PredictionBook account, assign probability to each of them sometime before the end of June (12:00 midday 1st July UTC being the enforced deadline, to accommodate variation in timezone). Then submit a contact email and your PredictionBook account name through this form, and you're done!

You can assign probability more than once, and I'll take whichever probability was made most recently before the deadline, so you can feel safe to make predictions early and just update them later if new information arrives (both will impact on your PredictionBook calibration calculation, but that doesn't feed into the contest). In particular, you can do this even after submitting to the form- I won't go collect assigned probabilities until after the deadline.

Tip: If predictions are daunting, you don't need to do it all in one go- you can make a handful of predictions now and then throughout the two months and they'll all be done by the end. Maybe just do one and see after if you feel like doing more.

When It Ends

All the predictions settle by the 1st of January 2019. At some point prior to the end of January 2019, I'll ensure all the predictions are settled accurately, calculate the log score for each entrant, make a new post announcing the results and listing the scores and ranks of the entrants (by their PredictionBook account- contact email rema...
Internalizing Internal Double Crux
by TurnTrout — 2018-04-30T18:23:14.653Z

In sciences such as psychology and sociology, internalization involves the integration of attitudes, values, standards and the opinions of others into one's own identity or sense of self.

Internal Double Crux is one of the most important skills I've ever learned. In the last two weeks, I've solved some serious, long-standing problems with IDC (permanently, as far as I can tell, and often in less than 5 minutes), a small sample of which includes:

Belief that I have intrinsically less worth than others
Belief that others are intrinsically less likely to want to talk to me
Belief that attendance at events I host is directly tied to my worth
Disproportionately negative reaction to being stood up
Long-standing phobia of bees and flies

I feel great, and I love it. Actually, most of the time I don't feel amazingly confident - I just feel not bad in lots of situations. Apparently this level of success with IDC across such a wide range of problems is unusual. Some advice, and then an example.

The emotional texture of the dialogue is of paramount importance. There should be a warm feeling between the two sides, as if they were two best friends who are upset with each other, but also secretly appreciate each other and want to make things right.

Each response should start with a sincere and emotional validation of some aspect of the other side's concern. In my experience, this feels like emotional ping pong.
For me, resolution of the issue is accompanied by a warm feeling that rises to my throat in a bubble-ish way. My heart also feels full. This is similar to (but distinct from) the 'aww' feeling you may experience when you see cute animals.

Focusing is an important (and probably necessary) sub-skill.
Don't interrupt or otherwise obstruct one of your voices because it's "stupid" or "talked long enough" - be respectful. The outcome should not feel pre-ordained - you should be having two of your sub-agents / identities sharing their emotional and mental models to come to a fixed point of harmonious agreement.
Some beliefs aren't explicitly advocated by any part of you, and are instead propped up by certain memories. You can use Focusing to hone in on the memories, and then employ IDC to resolve your ongoing reaction to it.
Most importantly, the arguments being made should be emotionally salient and not just detach

...
A Few Tips on How to Generally Feel Better (and Avoid Headaches)
by moridinamael — 2018-04-30T16:02:24.144Z

Meta: A recent post asking whether strenuous thinking can cause headaches prompted me to polish off and publish this long-incubating draft. These are some of my learnings from my multi-year ongoing headache/migraine/chronic pain journey. For every thing I suggest below, there are nine things that I tried and judged to be ineffective or marginally effective. Consider this my attempted distillation of many books, much medical instruction, and years of personal experimentation. I am not a doctor, this is not medical advice, just a list of things that work for me and things that I pay attention to.

Here are some simple, powerful things to try if you wish you had fewer headaches, or just suspect that you ought to generally feel better and have more energy than you do.

Sleep

You should be sleeping on your back, with a single pillow which provides good stability and support for your neck. Sleeping on your side can be acceptable but I would avoid it. If you have trouble sleeping on your back, try putting a pillow under your knees for a while to keep your body in place while you sleep.

Why: If you sleep wrong, your nervous system does whatever it can to protect your spinal cord and brainstem. This may include ramping up the tension in your neck muscles to the point of exhaustion, restricting blood flow, causing inflammation of local tissues, and irritating the cranial nerves. If this tension becomes chronic, the muscles will form knots, or trigger points, which perpetuate the pain on their own. Sleeping on your stomach does all of that and also actively puts tension on the deep muscles and tendons which leads them to change shape and ruin your neck curvature. Then your problem becomes chronic.

You should be sleeping enough. My litmus test is that if I'm sleeping enough then I will not nod off while meditating, and I will be able to readily get out of bed in the morning. Consider that you may be so chronically mildly sleep deprived that it feels normal to you, and experiment with going to bed an hour earlier.

Why: Not sleeping enough increases all-cause mortality and reduces mental and physical functioning. Chronic mild sleep deprivation shaves several years off your life. It also directly leads to poor modulation of blood sugar and lazy posture and thus neck pain. Studies show that humans are very poor at knowing if we're sleeping enough.

Blood Sugar

Reduce or elim...
The Alignment Newsletter #4: 04/30/18
by Rohin Shah — 2018-04-30T16:00:13.425Z

Highlights

Reptile: A Scalable Meta-Learning Algorithm

(Alex Nichol et al): I somehow forgot to include this in past emails, so I'm including it now. Reptile is an algorithm for meta-learning, and in this paper is applied to few-shot classification, where given a few examples of different classes, you must learn a good classification algorithm for those classes. The authors show using a Taylor expansion that

MAML

and Reptile have very similar gradients to first order in alpha, the step size. Their evaluation shows that for the few-shot classification case, Reptile and MAML perform similarly (though they do not evaluate on reinforcement learning tasks, as in the MAML paper).

My opinion: This seems like an important advance in meta-learning, as it is much more computationally efficient than MAML while still achieving similar levels of performance.

Read more:

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Technical AI alignment

Technical agendas and prioritization

Inverse Reinforcement Learning and Inferring Human Preference with Dylan Hadfield-Menell

(Lucas Perry and Dylan Hadfield-Menell): A few weeks ago, Lucas Perry interviewed Dylan Hadfield-Menell on the FLI podcast about his research (which includes papers like

Cooperative Inverse Reinforcement Learning

,

The Off-Switch Game

, and

Inverse Reward Design

). They discussed a variety of topics including the motivations behind Dylan's research, future directions, thoughts on hard problems such as corrigibility and preference aggregation, etc.

My opinion: This is probably most useful for understanding the motivations behind many of Dylan's papers and how they all tie into each other, which can be hard to glean just from reading the papers. There were also a lot of framings of problems that felt useful to me that I haven't seen elsewhere.

Learning human intent

Zero-Shot Visual Imitation

(Deepak Pathak, Parsa Mahmoudieh et al)

Reward learning theory

Reward function learning: the value function

and

Reward function learning: the learning process

(Stuart Armstrong): These posts introduce a theoretical framework for reward learning, where a reward learning algorithm is modeled as something that produces a probability distribution over reward functions given a history and current policy. With such a general notion of reward learning, it becomes hard to define the value function -- while we st...
Beginning Machine Learning
by crybx — 2018-04-30T15:54:06.360Z

I recently finished the Machine Learning course on Coursera that is recommended by MIRI's research guide for developing a practical familiarity with machine learning.

This post contains my thoughts about the course and tries to convey the updates my mental models went through as the eleven week course progressed.

I started the course with the perspective of an experienced, employed software developer with an engineering degree who had never focused on machine learning before, so I'm sure there's some background knowledge I take for granted, as well as some things I should have realized long before taking this course.

What is machine learning?

A definition introduced early in the lectures defines machine learning as the field of study that gives computers the ability to learn without being explicitly programmed.

I knew that much before this class.

What I didn't know were the nuts, bolts, and gears of how to start writing actual code that uses machine learning algorithms.

Prior to the course, I briefly tried to imagine how an application of machine learning might work (e.g. a program learning to play a game). What I came up with was a complex set of rules and loops where other complex rules somehow tweaked the original rules based on whatever results were used to represent desired outcomes.

What those rules should even be was vague, and I thought the whole system I imagined would be a fragile, error prone, maintenance nightmare.

That didn't square with the robust uses of machine learning by tons of profitable companies, or with the fact that I knew neural nets are increasingly popular and useful. I had a rough conceptual sketch of neural nets being nodes connected in layers with weights and outputs but not how to represent that in code.

I was eager for this class to tell me what I was missing.

Machine learning is math.

March 6, 2018 - As of today, I'm in the middle of week 5, and my initial reaction to the course has been: I'm basically writing programs to do statistics.

Before this course, calculating a linear regression or using the normal equation wouldn't have struck me as tasks of "machine learning." I may have thought of these as tools data scientists use, but they seemed too basic for the hype around machine learning.

In reality, the lines between artificial intelligence, data science, and machine learning are blu...