trentmkelly/LessWrong-43k huggingface dataset:
Mana
by Ziz — 2017-12-20T02:24:52.807Z

(This is a copy-pasted blog post from https://sinceriously.fyi/, I'm checking how much demand here there is for my writing.)

This is theorizing about how mana works and its implications. (Edit: usable link: https://sinceriously.fyi/wp-content/uploads/2017/12/Brent-Dill-So-wacky-RPG-session-from-a-riff-with-Anisha-and..pdf)

Some seemingly large chunks of stuff mana seems to be made of:

Internal agreement. The thing that doles out "willpower".
Ability to not use the dehumanizing perspective in response to a hostile social reality.

I've been witness to and a participant in a fair bit of emotional support in the last year. I seem to get a lot less from it than my friends. (One claims suddenly having a lot more ability to "look into the dark" on suddenly having reliable emotional support for the first time in a while, leading to some significant life changes.) I think high mana is why I get less use. And I think I can explain at a gears level why that is.

Emotional support seems to be about letting the receiver have a non-hostile social reality. This I concluded from my experience with it, without really having checked against common advice for it, based on what seems to happen when I do the things that people seem to call emotional support.

I googled it. If you don't have a felt sense of the mysterious thing called "emotional support" to search and know this to be true, then from some online guides, here are some supporting quotes.

From this:

"Also, letting your partner have the space he or she needs to process feelings is a way of showing that you care."
"Disagree with your partner in a kind and loving way. Never judge or reject your mates ideas or desires without first considering them. If you have a difference of opinion that's fine, as long as you express it with kindness."
"Never ignore your loved one's presence. There is nothing more hurtful than being treated like you don't exist."

From this:

"Walk to a private area."
"Ask questions. You can ask the person about what happened or how she’s feeling. The key here is to assure her that you’re there to listen. It’s important that the person feels like you are truly interested in hearing what she has to say and that you really want to support her."
"Part 2 Validating Emotions"
"Reassure the person that h

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TSR #6: Strength and Weakness
by Hazard — 2017-12-19T22:23:57.473Z

**This is part of a series of posts where I call out some ideas from the latest edition of The Strategic Review (written by Sebastian Marshall), and give some prompts and questions that I think people might find useful to answer. I include a summary of the most recent edition, but it's not a replacement for reading the actual article. Sebastian is an excellent writer, and your life will be full of sadness if you don't read his piece. The link is below.

Background Ops #6: Strength and Weakness

SUMMARY

Soviet Marshal Zhukov had his work cut out for him, and did a pretty stellar job.
Having a clear understanding of your strengths and weakness gives insight into how to design your ops.
Ways ops (operations) typically fail:

They aren’t playing to your strengths
Don’t acknowledge/mitigate weakness
Not understanding your s and w
You created a “platonic” ops that “should” work but doesn’t

“A commander must not be afraid of fighting under unfavourable circumstances.”
When looking to develop and install operations successfully, things typically don’t change quickly, but they do change. You should periodically re-assess where you’re at, so you don’t fail to capitalize on gains or mitigate emerging weaknesses.
Things have to actually work, so make sure you’re dealing with the non ideal aspects of your current situation.

It’s really useful to see examples of someone using principles in action. Reading about General Zhukov expertly navigating the strengths and weaknesses of the Soviets and Nazis is a great way to learn. Similarly, I really like Yudkowsky's coming of age story in the sequences. Observing the steps of someone’s mind as they make mistakes or do things well is very informative.

I like the points Sebastian has made about reasons operations often fail, and I think it gives a decent guide on how to kick off a post mortem on plans and ops that you’ve made which haven't worked out.

Most often, my ops fail because I don’t sufficiently break down the task I’m trying to operationalize. I’ve noticed that the more granular an ops is, the easier it is to not give into resistance in the moment. It’s easier for me to “take off the covers, swing my legs down, turn off the alarm that is set to ring at the same time everyday without me having to reset it” than it is to “wake up on time”. This sort of failure mode seems to be subset of “platonic ops that can’t handle...
CFAR 2017 Retrospective
by Valentine — 2017-12-19T19:38:35.516Z

As we approach the end of the year, we’d like to offer everyone a summary of what CFAR has been up to in 2017.

Sprint & Instructor Training

The first half of the year focused on improving and stress testing our main intro workshops. We ran a “sprint” of five workshops from February through May. This had a couple of main aims:

We wanted to see if we could do it. One model of CFAR has us running one to two workshops every month, so it was important to see what challenges we’d face and how capable we are, and need to become, in order to deal with running that many in a row.
A group of twelve alumni had just gone through our new experimental instructor training program, so the sprint gave them an opportunity to test and hone their skills in the field. This also helped us see how well the training program had worked and how we might need to modify it later.

The crop of new instructors then ran a “leaving the nest” workshop in Seattle in June. They ran everything: outreach, logistics, curriculum design, teaching, operations, and anything else that came up. Anna Salamon and I attended as participants, both because we wanted to see how the group ran the workshop, but also because at that point we were the only people at CFAR who hadn’t experienced the workshop as participants. We can now honestly (if a little tongue-in-cheek) say that CFAR is staffed entirely by alumni!

Overall we were pretty pleased with the results here. We learned a lot from the sprint, and we now have a crew of alumni we can call on who can lend both support and new perspective for teaching at workshops.

(Pete Michaud, our Executive Director, gives a more detailed breakdown of what we did during the first half of the year in a pair of CFAR newsletters. You can find the second one here which links to the first.),

Curriculum Development

Shortly after the Seattle workshop, CFAR and some of the alumni instructors spent a few days at a “curriculum reforging”. The goal was to refactor the curriculum and possibly rebuild the main CFAR workshop content from the ground up. We were responding to an opportunity rather than a problem: we could tell we had more insights and promising ideas than we’d managed to fit in the main workshops, so we wanted to see if we could do better.

Very little about the main workshops changed as a result of that, but we did start running a “Tier II” workshop. The idea was to pick ...
Philosophy of Numbers (part 2)
by Charlie Steiner — 2017-12-19T13:57:19.155Z

A post in a series of things I think would be fun to discuss on LW. Part one is here.

I

As it turns out, I asked my leading questions in precisely the reverse order I'd like to answer them in. I'll start with a simple picture of how we evaluate the truth of mathematical statements, then defend that this makes sense in terms of how we understand "truth," and only last mention existence.

Back to the comparison between "There exists a city larger than Paris" and "There exists a number greater than 17." When we evaluate the statement about Paris we check our map of the world, find that Paris doesn't seem extremely big, and maybe think of some larger cities.

We can use exactly the same thought process on the statement about 17: check our map, quickly recognize that 17 isn't very big, and maybe think of some bigger numbers or the stored principle that there is no largest integer. A large chunk of our issue now collapses into the question "Why does the map containing 17 seem so similar to the map containing Paris?"

<Digression>

We use the metaphor of map and territory a lot, but let's take a moment to delve a little deeper. My "map" is really more like a huge collection of names, images, memories, scents, impressions, etcetera, all associated with each other in a big web. When I see the word "Paris" I can very quickly figure out how strongly that thing is associated with "city size," and by thinking about "city size" I can tell you some city names that seem more closely-associated with that than "Paris."

"17" is a little trickier, because to explain how I can have associations with "17" in my big web of association, I also need to explain why I don't need a planet-sized brain to hold my impressions of all possible numbers you could have shown me.

The answer is that there's not really a separate token in my head for "17," and not for "Paris" either. My brain doesn't keep a discrete label for everything, instead it stores and manipulates mental representations that are the collective pattern of lots of neurons, and therefore inhabit some high-dimensional space. For example, 17 and 18 might have mental representations that are close together in representation-space. And I can easily represent 87438 desp

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Thinking as the Crow Flies: Part 3 - Tokens, Syntax, and Expressions
by Anthony Hart — 2017-12-18T23:38:52.106Z

Preamble

In my last post, I discussed some basic logical connectives. Before moving on to more advanced topics, I want to discuss formal syntax. I think many people will find this post dry and boring, but I think it's neccessary to cover at some poin

Up till this point, I've been assuming an understanding which bears dwelling on. I've previously stated that a judgment is a series of mental tokens which one may declare. While I've technically adhered to that, it's obvious that I'm assuming more structure. Furthermore, I've made usage of variable binding and substitution, which have not been properly accounted for.

This short post is intended to specify the nature of syntax as used in this series. It will mostly be a recount of abstract syntax and binding according to the first chapter of Practical Foundations for Programming Languages, but with retrospect from the account of meaning explanations given earlier.

Abstract Syntax Trees

Any given form of logic specifies various sorts of phrases which may be combined to form judgments. We'll distinguish between two different types of syntax, an informal "surface" syntax which is human readable, and a formal abstract syntax which is more well-defined. We'll be concerning ourselves with this abstract syntax in this post, treating the surface syntax as a mere readable short-hand for the abstract syntax.

In defining abstract syntax, we concern ourselves primarily with the rules by which we may combine phrases with each other. Since we already have an understanding of meaning explanation under our belt, we may use this to express the rules for correct syntax formation. At first, our phrases will be in the form of trees, called abstract syntax trees, or ASTs.

ASTs are made up of two main kinds of things, variables and operators. The variables may be placed at the leaves of an AST, while the operators make up the nodes. For the sake of restricting how syntax may be combined, we give every operator a sort. This sort will dictate the role of an operator by restricting how it may be combined with other operators.

Each operator comes equipped with a list of sorts, s1, ... sn, which tell us what sorts of ASTs can be plugged into the operator. In addition, each operator has an intrinsic sort s. When ASTs of the proper sorts are plugged into this operator, we obtain an AST of sort s...
Bay Solstice 2017: Thoughts
by PDV — 2017-12-18T10:04:03.754Z

To me, this year's Solstice was a flop. While it's still somewhat fresh in my mind, I would like to say why.

(A few of these thoughts are ones I shared with others and found basic agreement. The rest were not discussed and may be entirely idiosyncratic.)

At the design level, it was almost exactly the same as last year. I think two songs changed in the choral parts, two speeches definitely were dropped (my I Have Seen The Tops of Clouds and Brienne's Invincible Summer from last year), and I think one was added (something from the Sequences I already forget, delivered as a dialogue). That left >80% unchanged. Perhaps the organizers thought it was in a good state and didn't need any big tweaks to the arc or main beats; if so I very much disagree.

Also at the prep level, it was significantly smaller than last year, admission was limited to smaller even than 2015 at Humanist Hall, and yet was not at Humanist Hall. Leaving Humanist Hall meant giving up the candle ritual, which I still consider the most important expression of the arc of Solstice. We outgrew it in 2016, and so we regrettably had to move. With the event limited by new rules of the 2016 space to be half the size of 2015, there was no longer a positive to balance that negative.

In terms of the execution, I think the speeches delivered were less polished and less emotional this year. I'd prefer not to go into detail as several people I call friends were on stage over the course of the night.

Further diluting the weight and emotional impact of the speeches was the applause. Every transition in the emotional beats of the arc, speech to song or song to speech, was disrupted by a round of applause. When the dominant theme is solemn, this felt extremely disrespectful, as blatantly inappropriate as a polka during Yom Kippur services or clapping along to the beat of Handel's Messiah. (This doesn't apply to the sing-alongs. My dislike for the clapping there is entirely personal distaste; it offends my inner drummer.)

While I'm mentioning the songs: They were good last year and were good this year. Though I can't claim to be at all objective on that front, my closest friends are all in the choir. IMO, Lean On Me in particular improved this year, but I couldn't put my finger on what I thought was better.

On 'Mixed Success' notes:

The half-Tarot card scheme. ...
Books I read 2017 - Part 1. Relationships, Learning
by Elo — 2017-12-18T09:38:43.505Z

Original post: http://bearlamp.com.au/books-i-read-2017-part-1-relationships-learning/ warning LW seems to have made this post less readable by removing some formatting marks. Possibly better read on bearlamp.com.au

This year I read 79 or so books. Also there are 24 more books that I put down without finishing. That's a lot to summarise. I have already spent more than 15 hours and restarted the process of summarising twice. This is attempt number 3.

Here they are:

Relationships & Communication

Having Difficult Conversations - Douglass stone
Crucial Confrontations -Kerry Patterson
Emotional intelligence - Daniel Goleman
reread: How to Win Friends and Influence People, circa 2007 - Dale Carnegie
More Than Two - Franklin Veaux
Nonviolent Communication - Marshall Rosenberg
Living Non-Violent Communication - Marshall Rosenberg
Daring Greatly - Brene brown
On Apology - Aaron Lazare
Circling Handbook - Marc Beneteau
7 Principles for Making Marriage Work - John Gottman
Feeling Good Together - David D Burns
Getting Past The Pain Between Us - Marshall Rosenberg
Graduating From Guilt - Holly Michelle Eckert
The Surprising Purpose of Anger - Marshall Rosenberg
Come as You Are - Emily Nagoski
Books I didn't finish
Jono Bacon - The Art of the Community
Games People Play
The Stories we tell Ourselves
Sex at Dawn - ewww evopsych

Learning

The Inner Game Of Tennis - Timothy Gallway
The Art of Learning - Josh Waitzkin
Peak: Secrets from the New Science of Expertises
Moonwalking With Einstein - Joshua Foer
Mastery - Robert Greene
The Talent Code - Daniel Coyle
A Mind For Numbers - Barbara Oakley

Psychology/Thinking

Rethinking Positive Thinking - Gabrielle Oettingen
The Man Who Mistook His Wife For a Hat - Oliver Sacks
Quiet - Susan Cain
A Whole New Mind - Daniel Pink
Flourish - Martin Seligman
The Essential Difference - Simon Baron-cohen
Flow - Mihaly Csikszentmihalyi
Superforecasters - Philip Tetlock
The Discerning Heart - Robert Kegan
Grit - Angela Duckworth
Immunity To Change - Robert Kegan
Succeed - Heidi Grant Halvorson
Rethinking Narcissism - Dr. Craig Malkin
Taking Charge of Adult ADHD - Russel Barkley
No One Understands You And What To Do About It - Heidi Halverston
Not Finished:
Mindset - Carol Dweck
The Origin Of Consciousness in the Breakdown of the Bicameral Mind - Julian Jaynes
Thinking, Fast and Slow - Daniel Kahneman

Management/self work

The One Thing - Gary Keller
The Checklist Manifesto - Atul

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Value learning subproblem: learning goals of simple agents
by AlexMennen — 2017-12-18T02:05:15.000Z

A potential problem with inverse reinforcement learning as a way for an AI to learn human values is that human actions might not contain enough information to infer human values from accurately enough. If this is the case, then it might be necessary to figure out how to get information about a human's preferences by actually looking inside their brain. This is a very hard problem, so I suggest starting with the toy problem of figuring out how to determine the goals of simple AI/ML systems, and then subsequently trying to scale up these techniques to try to make them work on human brains.

There are several directions you could go with this idea. For instance, you could try creating a machine learning system that takes in neural networks as input, and learning the concepts that these neural networks have been trained to recognize. So this system should be able to learn the alphabet by looking at a neural network that's been trained to recognize and distinguish between letters, and learn what cats are by looking at a neural network that's been trained to recognize cats. A trivial solution to this is to create a copy of the neural network you've seen, and then apply it to object-level inputs, thus demonstrating that you can perfectly reproduce the neural network's behavior. This is an unsatisfying solution, and its analog scaled up to humans would be to create a copy of the human, and ask the copy whenever it wants to know what humans want, which might not be practical for questions too complicated for the human to evaluate. Instead, we would want to learn a representation of a neural net's concepts such that it is possible to identify instances of the concept more accurately or more efficiently than the neural net does.

Another more precise potential toy problem is to look at code for a game-playing agent, and determine the rules of the game (in particular, the win conditions). Doing this correctly would inevitably end up with a representation of the goal that could be optimized for more effectively or efficiently. Subsequently playing the game it has learned well would just be an AI capabilities problem.

There are a few different things that “learning an agent's goals” could mean, and we would want to be careful about which one to learn. For instance, we could learn what the agent's designers intended for the agent to do. This has a possible failure mode when sca

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Longview Anarchism: Transcending the Existential  Threat of Freedom
by abbeybee — 2017-12-17T22:30:44.340Z

https://c4ss.org/content/50066

Piece about game theoretic coordination, existential risk, and the maximization of freedom. Full-text copied below:

Longview Anarchism: Transcending the Existential Threat of Freedom

Emmi Bevensee | Support this author on Patreon | September 28th, 2017

Skin as Thick as Bark

As asinine, cultish leaders fascistically toy with the notion of nuclear warfare, we are reminded yet again of the fragility of human life. That humans have advanced as far as we have is remarkable. It reminds me of the feeling of awe I have when realizing that we limited humans drive hurtling boxes of steel around and don’t kill each more often than we do. Really, brava humanity. And yet, on a long time scale, we are less than a blink. After all, dinosaurs roamed the earth for 165 million years, and humans have only been around for about 6 million. Although dinosaurs did not reach the level of existential responsibility and consciousness that humans have, they were still wiped out by natural phenomena. Many pessimists see our extinction as an inevitability and almost usher it in, giving it a seat in their home with a misanthropic accelerationist’s glee. It’s wiser to recognize the exponentially harrowing conundrums that we do and will continue to face with an eye of hope. At the very least we should act in accordance with a path that hope might suggest. The game theoretic dilemmas of technological advancement present threats, but they also offer opportunities for freedom. The alternative can only be devastation and the void, so gambling on a future is, however unlikely to succeed, a sound bet. A longview anarchism represents both a determinism, and an infinite array of possibility.

The Fear of Knowledge

Each new existential threat to humanity increases both the rewards of coordination and the risks of defection. With the invention of firearms came the genocide of indigenous peoples the world over, but, like the boomerang of advancement, in time, those guns gave rise to fighting forces that overthrew the very same colonial despots. With nuclear weapons have come both the horrific attacks on Hiroshima and Nagasaki as well as clean nuclear reactors capable of supplying unprecedented levels of more sustainable energy. The more easily we can destroy ourselves, the more meaningful becomes our responsibility not to do so.

Currently most of the largest human controlled exi...