trentmkelly/LessWrong-43k huggingface dataset:
Worked example of a mnemonic Memory technique
by Elo — 2017-02-07T10:22:21.566Z

Original post: http://bearlamp.com.au/worked-example-of-a-mnemonic-memory-technique/

In 2015 I wrote a list of techniques to help you remember names.

Today I was working through trying to remember a specific theory and I noticed a pattern I have been using for a few days now. When trying to remember theories or ideas. The inspiration for this concept came to me because I have been using an app called FBreader, and a Text-to-speech plugin. Using the two I now listen to ebooks in robot-voice while I drive or concentrate on other tasks. The trouble is that sometimes a book will present (verbally because it's being read out to me) some model or list of ideas that I need to hold in my head for the book to make any sense over the next few minutes or pages. So I needed a way to generate a picture (possibly a system 1 visceral image) of the ideas so that I could play around with them as the chapter continued or also just; as I needed to recall the information a few days later.

I hope this post describes what it feels like from the inside to be performing this skill.

The process

This is what I have been doing in my head:

0. (regular check on the trigger: this seems like useful information/this list seems important) Do I feel like I will remember it? If yes, end here. (if unknown - practice via trial and error, intuitively knowing what you are likely to forget is powerful and useful information to hold)

1. Think about the concept and how I am going to remember it.

2. Build a visual/spatial/sensory model that feels right to me about the model.

What does it sound like? (words sound like other words)

What does it remind me of? (other theories or systems that are similar)

Do I have any memories of experiences that seem to relate? (people who acted in ways that fit the model)

What does it line up to? (if it's a list of 9 items, maybe 3 of them line up to some of the 9 circles of hell, which is convenient)

Can I play with it a bit in my head?

3. double check that it feels right, hone it till it does. (Maybe it only has 5 pieces but 3 of them are already circles of hell. Can I make a new version of hell for my purposes of remembering these details - and why not?)

Examples

example 1: reading models of therapy around extramarital affairs. (from the paper - an intergrative intervention for promoting rec...
Request for collaborators - Survey on AI risk priorities
by  — 2017-02-06T20:14:04.161Z

After some conversations here I thought I would try and find out what the community of people who care about AI risk think are the priorities for research.

To represent peoples opinions fairly I wanted to get input from people who care about the future of intelligence. Also I figure that other people will have more experience designing and analyzing surveys than me and getting their help or advice would be a good plan.

Planning document

Here is the planning document, give me a shout if you want edit rights. I'll be filling in the areas for research over the next week or so.

I'll set up a trello if I get a few people interested.
Selective social policing
by KatjaGrace — 2017-02-06T19:00:12.000Z

Suppose you really want to punish people who were born on a Tuesday, because you have an irrational loathing of them. Happily you rule the country. But sadly, you only rule it because the voting populace thinks you are kind and just and not at all vindictive and arbitrary. What do you do? One well known solution is to ban stealing IP or jaywalking and then only have the police resources to deal with, er, about a seventh of cases.

I don’t know how often selective policing happens with actual police forces, but my impression is that it is not the main thing going on there. However I sometimes wonder if it is often the main thing going on in amateur social policing. By amateur social policing, I mean for instance a group deciding that Bob is too much of a leach, and shouldn’t be invited to things. Or smaller status fines distributed via private judgmental gossip, such as ‘Eh, I don’t really like Mary. She is always trying to draw attention to herself.’ or ’I can’t believe I dated him. He makes every conflict into an opportunity to talk at length about his own stupid insecurities, and it’s so boring.’

I claim that in many cases if each person enjoyed having Bob around, his apparently being a leach wouldn’t seem like an urgent priority to avoid. And if the speaker got on with Mary, her sometimes attention-seeking behavior wouldn’t be a deal breaker. He might instead feel a little unhappy about the situation on her behalf, and wonder in a friendly way how to stop her embarrassing herself again. And if a woman said she had found a fantastic partner who was a serious candidate as soulmate, and her friend said that she actually knows him, and must warn her: if they ever get in a conflict, he will talk too much about his insecurities(!), this would seem like a laughably meek warning. Yet it feels like a fine complaint at the end.

I suspect often in such cases, real invisible reasons behind the scenes drive demand for criticism, and then any of the numerous blatantly obvious flaws that a given person has are brought up to satisfy the need.

I sort of believed something like this abstractly—that there are often different standards for different people, for reasons that most people would find unfair. Which at least means policing depends on the apparent crime and also some less legitimate factor. But lately I have wondered if it is almost entirely the latter.

If I am jud...
True understanding comes from passing exams
by Stuart_Armstrong — 2017-02-06T11:51:58.871Z

Crossposted at the Intelligent Agent Forum

I'll try to clarify what I was doing with the AI truth setup in a previous post. First I'll explain the nature of the challenge, and then how the setup tries to solve it.

The nature of the challenge is to have an AI give genuine understanding to a human. Getting the truth out of an AI or Oracle is not that hard, conceptually: you get the AI to report some formal property of its model. The problem is that that truth can be completely misleading, or, more likely, incomprehensible.

For misleading you have old staples like "If you implement this strategy, the incidence of cancer will go down" (neglecting to mention that this will be because everyone will be dead). For incomprehensible, there are statements like "ratios of FtsZ to Pikachurin plus C3-convertase to Von Willebrand Factor will rise in proportion to the average electronegativity in the Earth's orbit". That might be true, but is incomprehensible to a layman and not much better to an expert.

In fact, the AI's answer might be a confusing mix of misleading and incomprehensible. If we've managed to find a good formal definition of "humans have cancer" but not of "humans are still alive", then we'll confront that mix: we'll know this will solve cancer, but we can't figure out whether humanity will survive or not.

Then there's the omnipresent risks from human biases. Confirmation bias, backfire effects, optimism, or pessimism bias... Should the AI take these in account, and present us with inaccurate information that nonetheless ends up with us having a more accurate impression at the end? And how are we going to measure that "accurate impression" anyway?

Measuring true understanding with an exam

Ignore the second AI in the setup for the moment, and focus simply on the first. One mark of true understanding in a human, is if they are capable of accurately answering questions about what they've just learnt. This suggests an exam as a true measure of understanding. And thus the goal for the first AI: it must prep its human to successfully pass the exam.

Now, many have argued that exams are not the be all and end all of understanding. But it does seem that passing exams is a necessary component of true understanding. If you understand something better but can't answer anything new about it, I'd be very curious as to what your understanding consists of.

Now, if there are ...
True understanding comes from passing exams
by Stuart_Armstrong — 2017-02-06T11:45:23.000Z

I'll try to clarify what I was doing with the AI truth setup in a previous post. First I'll explain the nature of the challenge, and then how the setup tries to solve it.

The nature of the challenge is to have an AI give genuine understanding to a human. Getting the truth out of an AI or Oracle is not that hard, conceptually: you get the AI to report some formal property of its model. The problem is that that truth can be completely misleading, or, more likely, incomprehensible.

For misleading you have old staples like "If you implement this strategy, the incidence of cancer will go down" (neglecting to mention that this will be because everyone will be dead). For incomprehensible, there are statements like "ratios of FtsZ to Pikachurin plus C3-convertase to Von Willebrand Factor will rise in proportion to the average electronegativity in the Earth's orbit". That might be true, but is incomprehensible to a layman and not much better to an expert.

In fact, the AI's answer might be a confusing mix of misleading and incomprehensible. If we've managed to find a good formal definition of "humans have cancer" but not of "humans are still alive", then we'll confront that mix: we'll know this will solve cancer, but we can't figure out whether humanity will survive or not.

Then there's the omnipresent risks from human biases. Confirmation bias, backfire effects, optimism, or pessimism bias... Should the AI take these in account, and present us with inaccurate information that nonetheless ends up with us having a more accurate impression at the end? And how are we going to measure that "accurate impression" anyway?

Measuring true understanding with an exam

Ignore the second AI in the setup for the moment, and focus simply on the first. One mark of true understanding in a human, is if they are capable of accurately answering questions about what they've just learnt. This suggests an exam as a true measure of understanding. And thus the goal for the first AI: it must prep its human to successfully pass the exam.

Now, many have argued that exams are not the be all and end all of understanding. But it does seem that passing exams is a necessary component of true understanding. If you understand something better but can't answer anything new about it, I'd be very curious as to what your understanding consists of.

Now, if there are only a few questions in the exam, the first AI

...
Meetup : Sydney Rationality Dojo - March 2017
by luminosity — 2017-02-06T09:51:59.180Z

Discussion article for the meetup : Sydney Rationality Dojo - March 2017

WHEN:
05 March 2017 04:00:00PM (+1100)

WHERE:
10 Shepherd Street, Chippendale

Join us from 4 - 6 to sharpen your planning, motivation and other rationality skills. Afterwards there'll be a social dinner for those who want to stick around.

Discussion article for the meetup : Sydney Rationality Dojo - March 2017
Open thread, Feb. 06 - Feb. 12, 2017
by MrMind — 2017-02-06T08:34:23.758Z

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

Notes for future OT posters:

1. Please add the 'open_thread' tag.

2. Check if there is an active Open Thread before posting a new one. (Immediately before; refresh the list-of-threads page before posting.)

3. Open Threads should start on Monday, and end on Sunday.

4. Unflag the two options "Notify me of new top level comments on this article" and "Make this post available under..." before submitting.
Are we running out of new music/movies/art from a metaphysical perspective?
by stephen_s — 2017-02-05T17:49:48.860Z

It is difficult to judge at first, but it appears that some music genres (classical and jazz especially) have seen a radically slowed or non-existent output of significant works in recent decades. By significant, I mean works that would be seen in league with the most acclaimed artists in the genre (eg Beethoven, John Coltrane). In a similar way, there is a building popular consensus that Hollywood is not pursuing original ideas as much anymore and is relying on rebooting old stories and franchises. But is this because of a fault of the Hollywood system, or is it because there are few significant movie story ideas left that have not been done?

It seems to me that there are limited possibilities in art (or any field) of what we can discover or create. It appears that the matter and rules of the universe (in concert with human nature) manifests itself into these limited possibilities. When we develop a field or genre, we learn and create at an increasing rate but then eventually "complete" the field (in a boom and bust pattern).

I wrote a brief article called The Big Niche to try and explain this concept.

The relevant questions seem to be:

Do you agree that from experience and observation, we can tell that certain genres or fields appear to become completed?

Does this concept or another concept best explain what is happening?

I'm interested if any of you agree with this line of thinking or have other possible explanations of this phenomena.
Why I'm working on satisficing intelligence augmentation (and not blogging about it much)
by  — 2017-02-05T17:40:54.985Z

Paradigm shifting seems necessary for general intelligence.

It seems likely that to be able to perform paradigm shifts you need to change your internal language. This seems incompatible with having a fixed goal within a language.

So a maximising agi seem like incompatible requirements.

Having the system satisficing some abstract notion of good and bad seems compatible with paradigm shifiting and with humans

In order to push the system to improve its function you need some method that can change what is good as the system that achieves that level of development.

It makes sense to make individual humans be what controls what is good and also have them teach the systems the meanings of words and how to behave.

In essence make the system be part of the not have their own verbalised goals apart from those given from the human (and the human would have taught the system the meaning of the words, so less chance of)

It also makes sense to have lots of them in case that something goes wrong with any individual.

Because of paradigm shifting I do not expect any one augmented intelligence to dominate.

This means I've got to care about a whole bunch of other problems that the AI singleton people don't have to worry about.

I realize I should unpack all these, But blogging is not the answer. To know what sort of satisficing system will work in the real world with real people we need to experiment (and maybe paradigm shift ourselves a few times). Only then can we figure out how it will evolve over time,

Having a proof of concept will also focus people's attention, more than writing a bunch of words.

If you want to work with me, know someone who might want to, or to point out some flaws in my reasoning such that there is a simpler way forward within the kind of world I think it is, I am contactable at wil (one l) . my surname @gmail.com. But i think I done with LW for now. Good luck with the revamp.
Does UDT *really* get counter-factually mugged?
by IAFF-User-111 — 2017-02-04T21:46:27.000Z

I'm hoping someone can clear this up for me; I'd be much obliged.

On LessWrong, I think someone made a good point regarding UDT's propensity (or lack there-of) to be counter-factually mugged, see: http://lesswrong.com/lw/3l/counterfactual_mugging/dm3r
Learning Impact in RL
by IAFF-User-111 — 2017-02-04T21:42:15.000Z

I present a simple Deep-RL flavour idea for learning an agent's impact that I'm thinking of trying out.
I don't, ATM, think it's very satisfying from a safety point of view, but I think it's at least a bit relevant, so I'm posting here for feedback, iyi.

IDEA:
Instead of learning

P(st+1|st,at)

with a single network, instead, learn it as:

P(st+1|st,at)=I(st+1|st,at)⨁T(st+1|st).

The ⨁ could mean mixing the distributions, adding the preactivations, or adding the samples from T and I. I think adding the samples probably makes the most sense in most cases.

Now, I is trained to capture the agent's impact, and T should learn the "passive dynamics". Apparently things like this have been tried before (not using DL, AFAIK, though), e.g.https://papers.nips.cc/paper/3002-linearly-solvable-markov-decision-problems.pdf

If we do a good job of disentangling an agent's impact from the passive dynamics, then we can do reduced-impact in a natural way.

This idea was inspired by internal discussions at MILA/RLLAB and the Advantage-function formulation of value-based RL.
Effective diversity
by KatjaGrace — 2017-02-03T23:10:12.000Z

1. Two diversity problems

Here are two concerns sometimes raised in Effective Altruist circles:

Effective Altruists are not very diverse—they are disproportionately male, white, technically minded, technically employed, located in a small number of rich places, young, smart, educated, idealistic, inexperienced. Furthermore, because of this lack of diversity, the community as a whole will fail to know about many problems in the world. For instance, problems that are mostly salient if you have spent many years in the world outside of college, if you live in India, if you work in manufacturing, if you have normal human attitudes and norms.

When new people join the Effective Altruism community and want to dedicate a lot of their efforts to effectively doing good, there is not a streamlined process to help them move from any of a wide range of previous activities to an especially effectively altruistic project, even if they really want to. And it gets harder the further away the person begins from the common EA backgrounds: a young San Franciscan math PhD working in tech and playing on the internet can move into research or advocacy or a new startup more easily than an experienced high school principal with a family in Germany can, plus it’s not even clear that the usual activities are a good use of that person’s skills. So less good is done, and furthermore less respect is accorded to such people than they arguably deserve, and so more forbearance is required on their part to stick around (possibly leading to problem 1).

2. Two divergent evaluations of diversity

These concerns are kind of opposite. Which suggests that if they ran into each other they might explode and disappear, at least a bit.

The first concern is based on a picture where people doing different things from the rest of the EA community are an extremely valuable asset, worthy of being a priority to pursue (with effort that could go to figuring out how to stop AI, or paying for malaria nets, or pursuing collaborators from easy-to-pursue demographics).

The second concern is based on a picture where people who are doing different things from the rest of the EA community are worthy mostly as labor that might be redirected to doing something similar to the rest of us. Which is to say that on this picture, the fact that they are doing different things from the rest of us is an active down...
Weekly LW Meetups
by FrankAdamek — 2017-02-03T16:53:25.982Z

This summary was posted to LW Main on February 3rd. The following week's summary is here.

The following 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:

Baltimore / UMBC Meetup - trying something new!: 05 February 2017 11:00AM
[Berlin] Sequences Reading Group: 23 February 2017 07:15PM
Berlin: 01 January 2019 01:30PM
Chicago Rationality Reading Group: 05 February 2017 01:00PM
Denver Area LW February Meetup: 07 February 2017 07:00PM
Moscow LW meetup in "Nauchka" library: 03 February 2017 08:00PM
San Francisco Meetup: Stories: 06 February 2017 06:15PM
Sydney Rationality Dojo - February 2017: 05 February 2017 04:00PM
Washington, D.C.: Typical Mind Fallacy: 05 February 2017 03:30PM

Locations with regularly scheduled meetups: Ann Arbor, Austin, Baltimore, Berlin, Boston, Brussels, Buffalo, Canberra, Chicago, Cologne, Columbus, Denver, Kraków, London, Madison WI, Melbourne, Moscow, Netherlands, New Hampshire, New York, Philadelphia, Prague, Research Triangle NC, San Francisco Bay Area, Seattle, St. Petersburg, Sydney, Tel Aviv, Toronto, Vienna, Washington DC, and West Los Angeles. There's also a 24/7 online study hall for coworking LWers and a Slack channel for daily discussion and online meetups on Sunday night US time.

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 meetup mentioned in a weekly overview. These overview posts are moved to the discussion section when the new post goes up.

Please note that for your meetup to appear in the weekly meetups feature, you need to post 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: At...
Why is the surprisingly popular answer correct?
by Stuart_Armstrong — 2017-02-03T16:24:58.545Z

In Nature, there's been a recent publication arguing that the best way of gauging the truth of a question is to get people to report their views on the truth of the matter, and their estimate of the proportion of people who would agree with them.

Then, it's claimed, the surprisingly popular answer is likely to be the correct one.

In this post, I'll attempt to sketch a justification as to why this is the case, as far as I understand it.

First, an example of the system working well:

Capital City

Canberra is the capital of Australia, but many people think the actual capital is Sydney. Suppose only a minority knows that fact, and people are polled on the question:

Is Canberra the capital of Australia?

Then those who think that Sydney is the capital will think the question is trivially false, and will generally not see any reason why anyone would believe it true. They will answer "no" and put high proportion of people answering "no".

The minority who know the true capital of Australia will answer "yes". But most of them will likely know a lot of people who are mistaken, so they won't put a high proportion on people answering "yes". Even if they do, there are few of them, so the population estimate for the population estimate of "yes", will still be low.

Thus "yes", the correct answer, will be surprisingly popular.

A quick sanity check: if we asked instead "Is Alice Springs the capital of Australia?", then those who believe Sydney is the capital will still answer "no" and claim that most people would do the same. Those who believe the capital is in Canberra will answer similarly. And there will be no large cache of people believing in Alice Springs being the capital, so "yes" will not be surprisingly popular.

What is important here is that adding true information to the population, will tend to move the proportion of people believing in the truth, more than that moves people's estimate of that proportion.

No differential information:

Let's see how that setup could fail. First, it could fail in a trivial fashion: the Australian Parliament and the Queen secretly conspire to move the capital to Melbourne. As long as they aren't included in the sample, nobody knows about the change. In fact, nobody can distinguish a world in which that was vetoed from one where where it passed. So the proportion of people who know the truth - that being those few deluded souls who...