trentmkelly/LessWrong-43k huggingface dataset:
A framework for speed reading
by limerott — 2019-09-16T18:52:02.722Z
Link: https://limerott.com/a-framework-for-speed-reading/

Chances are you've heard about speed reading. A magical technique that allows you to glance at a page of text and immediately extract all of its meaning. But after digging deeper and trying the techniques yourself, you realized that it does not seem to work for you. You may even feel guilty about not being able to read fast enough. After all, if there is a way to read 10,000 words per minute, are you not wasting a lot of time? I was in a similar position myself not too long ago.

Eventually, I decided to build my own framework for reading. I collected some bits and pieces from various sources, added my own insights to it -- and voilà! You can read the result here.

The good news is: Once you understand some basic facts and have the right terminology, the mystery around it fades away. What is left are a few practical and useful techniques that help you optimize your reading.

The basics

A fixation point is a point that your eyes fixate on. Every time you look at something intently, you are placing your eyes on an imaginary point. It could be on the lamp on your desk, on the nose of your conversation partner or on the title of a book lying in front of you.

The fixation area is the area around a fixation point that you can still see and extract information from -- without directly focusing on it. In other words, it is everything that you can see without moving your eyes. It can be approximated by a round shape. This should not be confused with peripheral vision, which refers to the outmost parts of your entire field of view. The fixation area only refers to the periphery of a single fixation point.

A saccade is a single atomic eye movement, going from one fixation point to another. Of course, the fixation area is also changed through that movement. We tend to believe that our eyes move continuously, when in fact, they make short and discrete movements.

Now, let's apply these basic concepts to reading.

Of course, it is impossible to read a word or sentence without ever having seen it [1]. Therefore, to read something in full, each word must have appeared in a fixation area at least once. Since each additional fixation point takes time, we look for a method that minimizes them while still covering the entire text. If we also assume that we read from left to right and leave no gaps, there aren't many options left.

We end up with the following standard reading method:

Read

...
[AN #64]: Using Deep RL and Reward Uncertainty to Incentivize Preference Learning
by Rohin Shah — 2019-09-16T17:10:02.103Z

Find all Alignment Newsletter resources

here

. In particular, you can

sign up

, or look through this

spreadsheet

of all summaries that have ever been in the newsletter. I'm always happy to hear feedback; you can send it to me by replying to this email.

Audio version

here

(may not be up yet).

Highlights

Learning to Interactively Learn and Assist

(Mark Woodward et al) (summarized by Zachary Robertson):

Cooperative Inverse Reinforcement Learning

proposed a model in which an AI assistant would help a human principal, where only the principal knows the task reward. This paper explores this idea in the context of deep reinforcement learning. In their grid-world environment, two agents move around and pick up lemons or plums. The principal is penalized for moving, but is the only one who knows whether plums or lemons should be picked up. The authors hypothesize that simply by jointly training the two agents to maximize rewards, they will automatically learn to interact in order for the assistant to learn the task, rather than requiring an explicit mechanism like comparisons or demonstrations.

Recurrent Q-networks are used for the agents, which are then trained via deep Q-learning. The authors run several experiments that show emergent interaction. In the first experiment, when the principal is penalized for moving it learns to demonstrate the task to the assistant, and then let the assistant finish the job. In the second experiment, when the assistant has a restricted field of view, it learns to follow the principal to see what it does, until it can infer whether the principal wants plums or lemons. In the third, they tell the assistant the task 50% of the time, and so the principal is initially unsure whether the agent needs any direction (and due to the motion cost, the principal would rather not do anything). When the agent knows the task, it performs it. When the agent doesn't know the task, it moves closer to the principal, in effect "asking" what the reward is, and the principal moves until it can see the object, and then "answers" by either moving towards the object (if it should be collected) or doing nothing (if not). Finally, the authors run an experiment using pixels as input. While they had to switch to dueling DQNs instead of vanilla DQNs, they show that the joint reward is competitive with the grid approach. They also run an e...
The strategy-stealing assumption
by paulfchristiano — 2019-09-16T15:23:25.339Z

Suppose that 1% of the world’s resources are controlled by unaligned AI, and 99% of the world’s resources are controlled by humans. We might hope that at least 99% of the universe’s resources end up being used for stuff-humans-like (in expectation).

Jessica Taylor argued for this conclusion in Strategies for Coalitions in Unit-Sum Games: if the humans divide into 99 groups each of which acquires influence as effectively as the unaligned AI, then by symmetry each group should end, up with as much influence as the AI, i.e. they should end up with 99% of the influence.

This argument rests on what I’ll call the strategy-stealing assumption: for any strategy an unaligned AI could use to influence the long-run future, there is an analogous strategy that a similarly-sized group of humans can use in order to capture a similar amount of flexible influence over the future. By “flexible” I mean that humans can decide later what to do with that influence — which is important since humans don’t yet know what we want in the long run.

Why might the strategy-stealing assumption be true?

Today there are a bunch of humans, with different preferences and different kinds of influence. Crudely speaking, the long-term outcome seems to be determined by some combination of {which preferences have how much influence?} and {what is the space of realizable outcomes?}.

I expect this to become more true over time — I expect groups of agents with diverse preferences to eventually approach efficient outcomes, since otherwise there are changes that every agent would prefer (though this is not obvious, especially in light of bargaining failures). Then the question is just about which of these efficient outcomes we pick.

I think that our actions don’t effect the space of realizable outcomes, because long-term realizability is mostly determined by facts about distant stars that we can’t yet influence. The obvious exception is that if we colonize space faster, we will have access more resources. But quantitatively this doesn’t seem like a big consideration, because astronomical events occur over millions of millennia while our decisions only change colonization timelines by decades.

So I think our decisions mostly affect long-term outcomes by changing the relative weights of different possible preferences (or by causing extinction).

Today, one of the main ways that preferences have weight is because a...
Exercises for Overcoming Akrasia and Procrastination
by Matt Goldenberg — 2019-09-16T11:53:10.362Z

In order to enter the "Rationality Exercises" competition, I've decided to create this cliffnotes version of my upcoming sequence on overcoming akrasia and procrastination.

Please enter any meta comments, or comments not pertaining to a particular exercise here.

The structure of the sequence is a set of exercises and mental models that help you notice

Triggers that lead to Akrasia,

Mental Moves (a series of mental steps) you can do with those triggers to get yourself an a more intentional state..

Together these Triggers and mental movements make up **Mental Reflexes. **These mental reflexes then combine together into Cognitive Strategies, which are groups of mental reflexes that help you with different areas of Akrasia.

Each cognitive strategy is its' own comment, so they can be voted on and discussed separately.

The epistemic status of all these exercises is still highly experimental. I am confident that some of them will help some people, but expect them to evolve significantly over time. I also won't be giving sources, motivation, or inspiration for these techniques in the post, so if you notice something that feels like it came from somewhere else, just know that in the eventual sequence I'll do my best to make my sources clear.

I'm also skipping over all the prerequisite material on how to notice triggers, cognitively rehearse items, etc.

The proper thing to choose what exercises will help you is to look at the Symptoms for each cognitive strategy. Find the symptoms that seem to match your symptoms for Akrasia, and then go through the exercises for that strategy.

I had originally planned to include all 10 cognitive strategies in this post, but then my computer died and I got accepted last minute to a 10 day silent retreat, so I'm publishing as is with only 3 of the cognitive strategies complete. I'll likely update this post with new strategies as the sequence gets published, and may add a couple more over the coming days before the deadline.
Divergence on Evidence Due to Differing Priors - A Political Case Study
by Davidmanheim — 2019-09-16T11:01:11.341Z

(This uses a politically charged topic as an example, but I'm hoping that people are willing to try to understand the points made despite that. Politics is Hard Mode, and I'm hoping to stay at a lower difficulty level for now, so I've asked that comments not discuss the object level politics.)

Last week on twitter, I saw two very different takes on how the United States reacted to 9/11, and the consequences. They both reflected an update to people's views based on the data since that time, but the conclusions radically diverged. E.T. Jaynes posited that this can happen, but this is the first time I recognized it in practice so clearly, and thought it was worth noting simply as an example. Beyond that, I wanted to point out how it can be to some extent avoided.

The first was Don Moynihan, who said: "It is important to remember 9/11 and the lives that were lost. Its also important to remember that period of American history fully, to understand that a terrorist attack triggered a series of catastrophic judgments by US politicians that led to the loss of more innocent lives."

The second was David French, who said: " If you had told us on that day that we wouldn't endure another mass-scale attack on American soil for at least 18 more years, we would have thought you were wildly optimistic. The achievement of our military and security establishment should never be underestimated."

First, I want to note that the two views are based on different counterfactuals. Moynihan presumably assumes that the counterfactual rate of terrorist attacks had the US not gone to war in Afghanistan and Iraq to be at least relatively low. He therefore updates based on the fact that there have been very few credible attempts to mount large attacks on the US homeland, to conclude that they would be foiled by standard US intelligence sources and policing. French explicitly calls out the fact that the commonly held prior for the number of attacks that would be mounted in the wake of 9/11 was high, and asserts that this was correct but-for the military interventions the US waged. He therefore updates based on the fact that there have been very few credible attempts to mount large attacks on the US homeland, to conclude that the military interventions were successful.

Clearly, it is not the case that either person is ignoring the evidence. In this cas...
Decision-Making for Impact: A Guide
by Ian David Moss — 2019-09-16T05:12:01.000Z

The most important decision is how to decide.

Photo by Ian Schneider on Unsplash

For about a decade now, I’ve been geeking out hard on decision-making. To be fair, my fascination comes from an honest place: I’m a walking stereotype of a reluctant decision-maker. Back when I was a teenager, I was paralyzed by challenges as mundane as what topics to choose for my high school English papers. Even now, I drive my wife and other dinner companions crazy whenever we’re at a restaurant, as I’ll study the menu, ask the server for a recommendation, ignore that recommendation, then call them over a minute later and change my order again. (Seriously, this exact sequence happens like 40% of the time.)

The self-help literature these days may be littered with guides on how to give yourself productivity superpowers — use power poses to harness your grit so that that you can enjoy a four-hour work week and retire early! — but personally, I’m more interested in how to give myself the superpower of making consistently wise decisions. Because it doesn’t matter how fast you blow through your task list if it’s full of mindless busywork.

And when it comes to social sector leaders, I’m doubly interested. Because your decisions carry a profound moral weight. They matter. The decisions of government officials, donors, and nonprofit executives have shaped my life in too many ways to count, both for better and for worse. And if you pause to think about your own life, I imagine you’ll conclude the same.

To be honest, I think that’s why we all got into this work in the first place: to make a difference in people’s lives. But it took me a while to realize that the difference we make and the decisions we make are one and the same. Better decisions foster a legacy we can be proud of.

So how can we get better? Lots of ways! Decision-making is an exciting frontier in social impact precisely because there is so much untapped potential to improve how we do things. For decades now, scholars and practitioners have been pioneering methodologies for analyzing and making decisions that have seen barely any adoption in philanthropy, government, or impact investing. Drawing from that body of work, I’ve developed my own process to help myself and my collaborators make critical decisions with intention and focus. Here, I’m sharing the key elements of that process so that you can benefit from them in your own ...
Realism and Rationality
by bmgarfinkel — 2019-09-16T03:09:45.499Z

Format warning: This post has somehow ended up consisting primarily of substantive endnotes. It should be fine to read just the (short) main body without looking at any of the endnotes, though. The endnotes elaborate on various claims and distinctions and also include a much longer discussion of decision theory.

Thank you to Pablo Stafforini, Phil Trammell, Johannes Treutlein, and Max Daniel for comments on an initial draft. I have also slightly edited the post since I first published it, to try to make a few points clearer.

When discussing normative questions, it is not uncommon for members of the rationalist community to identify as anti-realists. But normative anti-realism seems to me to be in tension with some of the community's core interests, positions, and research activities. In this post I suggest that the cost of rejecting realism may be larger than is sometimes recognized. [1]

1. Realism and Anti-Realism

Everyone is, at least sometimes, inclined to ask: “What should I do?”

We ask this question when we're making a decision and it seems like there are different considerations to be weighed up. You might be considering taking a new job in a new city, for example, and find yourself wondering how to balance your preferences with those of your significant other. You might also find yourself thinking about whether you have any obligation to do impactful work, about whether it’s better to play it safe or take risks, about whether it's better to be happy in the moment or to be able to look back with satisfaction, and so on. It’s almost inevitable that in a situation like this you will find yourself asking “What should I do?” and reasoning about it as though the question has an answer you can approach through a certain kind of directed thought.[2]

But it’s also conceivable that this sort of question doesn’t actually have an answer. Very roughly, at least to certain philosophers, realism is a name for the view that there are some things that we should do or think. Anti-realism is a name for the view that there are not.[3][4][5][6]

2. Anti-Realism and the Rationality Community

In discussions of normative issues, it seems not uncommon for members of the rationalist community to identify as “anti-realists." Since people in different communities can obviously use the same words to mean different things, I don't know what fraction of rationalists have the same thing in m

...
The Power to Be Emotionally Mature
by Liron — 2019-09-16T02:41:37.604Z

This is Part VII of the Specificity Sequence

When Steve unknowingly lacks an understanding of what his claim that "Uber exploits its drivers" means, we can say that he's being intellectually immature. Similarly, when someone unknowingly lacks an understanding of the cause of an emotion they're expressing, we can say they're being emotionally immature.

Imagine a 7-year-old boy playing with his sister in the park at dusk, who doesn't realize that he's currently tired and cranky. Sis gives him a soft punch on the arm, and suddenly he bursts into tears, runs to his mom and complains that his sister was being mean to him.

Boy: Sis was mean to me!

Mom: What specifically did she do?

Boy: She punched me!

Mom: Was it a hard punch or just a mean punch?

Boy: It was just a mean punch!

This is the emotional equivalent of:

Steve: Uber exploits its drivers!

Liron: What specifically do they do?

Steve: They pay them too little!

Liron: Is Uber paying a typical driver less than that driver would earn if Uber didn't exist, or just too little to be non-exploitative?

Steve: Just too little to be non-exploitative!

If you want to be emotionally mature, there's a mental operation you can do which we'll call grounding your emotions because it's analogous to grounding your terms.

Recall that grounding a term requires you to describe a specific stimulus that you'd mentally classify within that term, like when we grounded the concept of “red” by saying it's something you call a traffic light when traffic is stopped. Similarly, to ground an emotionally-loaded claim, you give an example of a specific situation that you'd mentally classify within that claim.

Let’s look at a couple examples of people introspecting on the specific causes of their emotions.

A "Disgusting Slob" Roommate (h/t Eliezer)

Tim feels strongly that his roommate Rob is a disgusting slob, so he says, “Hey Rob, can you stop being such a slob?” and Rob says “I’m not a slob, you’re a neat freak!” And they start to hate each other.

Let’s see how Tim can do better by activating his specificity powers!

In general, when you activate your specificity powers on an emotional claim you've made, you might end up instantly demolishing the claim, like a boy who's made to realize that there's nothing inherently "mean" about his sister giving him a soft punch on the arm. But if you find that your emotion can be coherently grounded in the specific sti...
Non-anthropically, what makes us think human-level intelligence is possible?
by Grue_Slinky — 2019-09-15T23:30:28.288Z

The basic question I'm asking is the following:

Suppose you didn't know humans exist. Could you still deduce that general intelligence is possible, and if so how?

This may be a weird hypothetical to imagine, so here's my best attempt to give a story to aid the counterfactual imagination:

At some point, you gain the ability to observe an alternate universe, which you eventually call the "Earth-universe". The fundamental laws of physics are very different here, and you get to work studying it. At first it feels very weird and you have almost no way of making sense of the raw sensory data. Eventually you learn that there are these things "galaxies" and "stars", and it takes you thousands of years to derive Newtonian mechanics. At this point, you've finally gotten your bearings, your intuitions aren't so horrible anymore, and you can go on to develop general relativity, quantum mechanics, etc. But this is still slow [you're approximately as smart as humans].

However, there aren't any humans in this universe, or any intelligent life. You just focused your sensors on this planet "Earth", where there are some really interesting chemical reactions that perpetuate themselves. You've figured out a lot about paleontology and evolution by natural selection and can see the progression of complicated life forms that have evolved on this planet. Apparently, there used to be these things called dinosaurs, but--just your luck--they died out a couple million years ago, but it's interesting to see how the remaining life's been evolving into the new niches...

Something you wonder to yourself:

Is intelligent life possible in this universe? Not necessarily on this planet, but in general? Like, if it's going to show up anywhere, it would probably be here on Earth (at least of the places I've looked at). But even if it doesn't show up here, that could just be a contingent fact about how things have played out. Does the physics/chemistry of this universe allow for some mind to be intelligent, i.e. to have a similar ability to "figure out" its surroundings much in the way I've been figuring out this universe and my own.

Of course you trivially know that intelligence is possible in your own universe, but you figured out a long time ago that nothing you knew about your universe was at all useful for deducing anything about this one. You tried using your old intuitions, you tried for the first...
Are there technical/object-level fields that make sense to recruit to LessWrong?
by Raemon — 2019-09-15T21:53:36.272Z

LessWrong is about learning rationality, and applying rationality to interesting problems.

An issue is that solving interesting problems often requires fairly deep technical knowledge of a field. To use rationality to help solving problems (especially as a group), you need both people who have skills in probability/meta-cognition/other-rationality skills, as well as the actual skills directly applicable to whatever problem is under discussion.

But if you show up on LW and post something technical (or even just "specialized") in a field that isn't already well represented on the forum, it'll be hard to have meaningful conversations about it.

Elsewhere on the internet there are probably forums focused on whatever-your-specialization is, but those places won't necessarily have people who know how to integrate evidence and think probabilistically in confusing domains.

So far the LW userbase has a cluster of skills related to AI alignment, some cognitive science, decision theory, etc. If a technical post isn't in one of those fields, you'll probably get better reception if it's somehow "generalist technical" (i.e. in some field that's relevant to a bunch of other fields), or if it somehow starts one inferential unit away from the overall LW userbase.

A plausibly good strategy is to try to recruit a number of people from a given field at once, to try to increase the surface area of "serious" conversations that can happen here.

It might make most sense to recruit from fields that are close enough to the existing vaguely-defined-LW memeplex that they can also get value from existing conversations here.

Anyone have ideas on where to do outreach in this vein? (Separately, perhaps: how to do outreach in this vein?). Or, alternately, anyone have a vague-feeling-of-doom about this entire approach and have alternate suggestions or reasons not to try?