Editorial text isn't very interesting; they call for descriptive statistics and don't recommend any particular analysis.

'MIRI' works in the search field when electing a charity to get 0.5% of your https://smile.amazon.com purchases.

Has anyone read "How We Reason" by Philip Johnson-Laird? He and others in his field (the "model theory" of psychology/cognitive science) claim that their studies refute the naive claim that human brains often operate in terms of logic or Bayesian reasoning (probablistic logic). I gather they'd say that we are not Jaynes' perfect Bayesian reasoning robot or even something resembling a computationally bounded approximation to it.

I'm intrigued by this recommendation:

 ... formal logic cannot be the basis for human reason. Johnson-Laird reviews evidence to this effect. For example, there are many valid conclusions that we never bother to draw because they are of no practical use to us. We also make systematic errors in reasoning that we would not make using logic. The content of logic problems used in research studies greatly affects their difficulty; it would not if logic were the primary process. We use knowledge to help us imagine possibilities and then evaluate the possibilities for consistency with other evidence.

Constrained by the span of short term memory, the strength of our general intellectual abilities, and our level of expertise, we construct and manipulate mental models of the problems we reason about. "...[F]rom the meanings of sentences in connected discourse, the listener implicitly sets up a much abbreviated and not especially linguistic model of the narrative ... Where the model is incomplete, material may even be unwittingly invented to render the memory more meaningful or more plausible." We can manipulate these models in a number of ways, including updating them with new information, combining two models when appropriate, searching for confirming evidence or information, and using counterexamples to challenge a model's validity.

Mental model theory explains a number of systematic errors human beings make when reasoning. For example, the difficulty of reasoning problems is related to the number of models that must be held simultaneously in memory to work through them. And we exhibit a recurring bias to use a single model to reason about situations that have more possibilities than we can keep track of. We oversimplify. Consistent with model theory, we have difficulty reasoning with information about what is false about a situation.

The real key to human rationality is our ability to recognize and grasp the implications of counterexamples

It seems like an interesting read, but I'd like to know if the research field is a scientific one, i.e. that their stories aren't just pleasing, but can predict, or at least explain real phenomena.

In the Google books preview, I see the author spends some time claiming that we build iconic visual/spatial representations and that a lot of our thinking isn't verbal or available to verbal introspection (fairly uncontroversial to me).

I liked the two related imagination-puzzles:

1. I have thousands and thousands of very thin needles, which I hold in a bundle in my hands. I throw them up into the air, imparting a random force to each of them. They fall to the ground, but, before any of them hits the ground, I stop them by magic in mid-air. Many of the needles are horizontal or nearly so, and many of them are vertical or nearly so. Are there likely to be more needles in the first category, more needles in the second category, or do the two categories have roughly equal numbers?

 [and the same thing but for very thin circular disks - let's assume they're also dense, so the air isn't a factor]

2.  I have thousands and thousands of very thin circular disks, which I hold in a bundle in my hands. I throw them up into the air, imparting a random force to each of them. They fall to the ground, but, before any of them hits the ground, I stop them by magic in mid-air. Many of the disks are horizontal or nearly so, and many of them are vertical or nearly so. Are there likely to be more disks in the first category, more disks in the second category, or do the two categories have roughly equal numbers?

He claims that for spatial propositions where we can imagine a picture that's more or less equivalent ("the cabinet is behind the piano" [as we face the keys]), the negation of that proposition can't be so pictured (in direct correspondence) because ... where would you put the cabinet? You could imagine all the alternative places it could be (presupposing that there is a specific piano and specific cabinet). You could imagine something "not cabinet" behind the piano (a cabinet with a red x, a cabinet repelling field?). He suggests an or(p1,p2,....pn) of images where we imagine the cabinet to be (that aren't behind the piano). I'm not sure what we can conclude from this. We already know that negation is tricky - linguistically, and mentally. Maybe I like to imagine someone telling me "no, you're wrong to say X" - to use a non-visual system.

He explains that inferences about (written) non-spatial visual relations (light/dark clean/dirty) take longer to process than spatial ones, that the spatial and visual word inference word problems had different fMRI hot spots, that congenitally blind people weren't faster on spatial queries (i.e. were slower on average than non-blind, but didn't suffer any additional penalty on the visual ones). I suppose this could be taken as weak evidence that we can perform "logical" inferences with some sort of spatial-relationship processing, and that perhaps non-spatial attributes take longer to translate (even though they refer to visual qualities like light/dark).

I'm leaning toward buying the book, since the writing is pleasant. But I thought first I'd ask if anyone could recommend for the quality of research in this field.

Adam Alter lists some evidence from people who study the effects of "disfluency" (unfamiliarity, or lack of clarity), which somewhat surprisingly leads to greater depth of thought (while you're expending the energy to understand something, you can't help but think about it), and also a willingness to depart further from immediate concrete reality (as in Robin Hanson's Near-Far). Think of the effort given to studying vague, poetic, or just incomprehensible religious materials (sometimes in their original scripts) and the investment this can generate.

Below are some of the linked claims of evidence:

When you give the prompt ... "Think about what it would be like to be fit and to have done a lot of exercise," if you give that prompt in a font that's very difficult to read, in a disfluent font, people tend to think longer about the task, they think more deeply about it, they depart more from reality, and then later on they actually say that they're going to be more willing to do this sort of exercise, and so they become more committed.

When you give them the bill that's been slightly altered [George Washington's portrait faces left], they think they can't purchase quite as much with it. If you say to them, "How many M&Ms can you purchase with this dollar bill," they'll give you a higher number when it's the real bill, and they'll also do that when it's a dollar bill versus a more obscure form of currency, like a dollar coin, or if you give them two $1bills, they think they can buy more with those two $1 bills than they can with a single $2 bill, the Jefferson $2 bill, which is much rarer. It's legal tender, but it's just more rare, and you find that people think they can purchase more with the two $1 bills than with the single $2 bill. That effect is also stronger to the extent that they are unfamiliar with the Jefferson bill. It goes away completely when they're very familiar with the Jefferson bill, but when they haven't seen it as many times, you get this very strong effect that they think that the Jefferson bill is less valuable, can purchase less than two $1 bills.

[about some anonymous confessions website] In the middle of 2008 he decided to change the format, and now the background, instead of being this gray shade that was very similar to the black text, he changed the background to white, and all of a sudden it was much easier to read the information on the site. ... The gravity of the confessions went up. They were much more revealing. Often they revealed crimes and major things that people might not otherwise reveal. A lot of the confessions that people were revealing when the site was disfluent were peccadilloes. They were minor issues. They were revealing really minor trivial things. We have some evidence that disfluency might mitigate some of those issues with over-sharing on the internet

if you ask people about how risky a ride is at an amusement park, if the ride has a very simple name, and it's easy to pronounce, people assume that it's not a very dangerous ride. It's not very risky. If you give them a ride that's much more disfluent, that's got a very complex name, they then think the ride is much more dangerous. They did the same thing with additives for food. They assume that the more complicated and convoluted the additive, and the harder it is to pronounce the additive's name, the more dangerous the additive will probably be.

"How likely do you think it is that this person knows that what you're clapping is Happy Birthday?" People, as they're clapping Happy Birthday, in their heads, they're humming it to themselves, and so they imagine the other person has a lot of that information, that it's totally obvious, and it turns out not to be

When you feel disfluency, it makes you feel a distance from the target. We've shown this effect with lawyers, that lawyers are just judged more harshly. We've shown the effect with politicians as well. If you say to someone, "Here are two politicians. How would you judge these two," you often find that you get more votes for having the simpler name.

When you ask people how well they understand what distinguishes two candidates, this particularly happens when you're dealing at the primary level before the main election, you'll find that people say, "I understand the difference between the candidates pretty well." They have this sense that they know the candidates, they know a little bit about them, and when you ask, "Okay. Can you explain the differences between the candidates to me," that leads them to a point where they can't do that.

If it feels more difficult to remember you'll assume that it happened longer ago, that it's further from where you are today. The same thing is true if you're looking at something, and you're trying to judge its physical distance. If it's fuzzy or difficult to perceive, you might assume that it's farther away.

If you present the questions [“When you add the cost of a bat and a ball together the sum of those two is worth $1.10, and the bat costs a dollar more than the ball, how much does the ball cost?” etc.] in a font that's a little bit more difficult to read, we found that you can increase their accuracy pretty dramatically. They make fewer of those intuitive responses. They take the time to reconsider their initial responses. They assume that the task is more difficult. They have a bit less confidence in their initial response, and so they tend to do a little bit better at the task.

If you look at the codes that are pronounceable, like BRI would be Bri, it's not an English word, but it's pronounceable, whereas BRK would be unpronounceable according to the rules of English grammar. The stocks that are pronounceable tend to do better when they first enter the market.

 If you present the same information in a format that's difficult to read, either because the font that you've chosen is complex, or because you put the font against a background that isn't very highly contrasting, or contrasted against that font, you find that people think that that moral transgression they're reading is worse. By struggling to read the transgression, they basically assume that the transgression is worse.

If you look at lawyers who join law firms they tend to ascend up the legal hierarchy much more quickly when their names are easy to pronounce or process. That's independent of a whole lot of other factors, like how foreign the name is.

(you may wish to skip over a long section speculating about the effects of 'kids these days don't remember phone numbers', since there's no new information in it).

How many people feel despair in imagining a heaven (positive singularity) that they'll miss out on if they don't survive long enough? I don't think about it, but I already have plenty of reasons to like being alive.

In Copenhagen the summer before last, I shared a taxi with a man who thought his chance of dying in an artificial intelligence-related accident was as high as that of heart disease or cancer. No surprise if he’d been the driver, perhaps (never tell a taxi driver that you’re a philosopher!), but this was a man who has spent his career with computers.

NYTimes

Nothing new for LW, but interesting to see some non-sci-fi public discussion of AI risk.

Three Toed Sloth has a nice exposition on the difficulties of optimizing an economy, including the best explanation of convex optimization ever:

If plan A calls for 10,000 diapers and 2,000 towels, and plan B calls for 2,000 diapers and 10,000 towels, we could do half of plan A and half of plan B, make 6,000 diapers and 6,000 towels, and not run up against the constraints.

I laughed: SMBC comic.

Anyone else going? http://blog.daggre.org/

Looks like you can barely get direct roundtrip from LA<->DC for $600 now (probably double that if you wait a week to book).

If you'd like to see some visual representations of conditional independence is neither necessary or sufficient for independence, confounding causes, explaining away, etc. you should be able to view these videos from ai-class.com.

Working the exercises gave me a better understanding than the "I understand this and so don't need to actually apply it" feeling that almost satisfied me.