This is really just pointing out that IQ tests are time based and so people who think faster do better at them. Measures of intelligence that are not time based might not show the same difference.
I often found in school / college that I could answer all the questions on tests and exams but not in the time given. It always felt a little unfair that others who were actually less capable sometimes got higher scores simply because they were faster at those parts they could do.
Intelligence is speed, but not in the linear way we think of it. When people think faster, they can put slightly more time into examining each possible solution branch, which allows them to discard the ones that resolve as "bad." This, then, culls those branches from their memory, allowing them to process the rest of the solution tree even faster. Someone who knows a little more CS than I do could actually give a definite answer to just how much faster it makes someone, assuming, just for the sake of argument, that solution trees are binary.
Anyway, there are certain problems that require a "minimum mental speed" to accomplish; Mensa test questions are basically designed so that your working memory capacity will be exhausted by extraneous branches unless your mind can cull them as quickly as it can think of them.
> Anyway, there are certain problems that require a "minimum mental speed" to accomplish; Mensa test questions are basically designed so that your working memory capacity will be exhausted by extraneous branches unless your mind can cull them as quickly as it can think of them.
What about people who have a larger or longer-lasting working memory capacity? Or those who have better culling algorithms? They may be able to solve classes of problems that 'faster' thinkers could never solve. They might do well at the Mensa test but on a simpler speed-based test they could do poorly.
You missed the symmetry of the equality. If you have "better culling algorithms", each branch gets culled away faster, so, on an EEG or a similar device, you appear to be thinking faster.
The reason I didn't mention the possible variation in working memory capacity was a single word that I left out, leaving it, like I said, to the Computer Scientist: "exponential." Every time your have an additional binary choice to make, your possible solution-space doubles. It doesn't matter how large your working memory is; as long as it's a fixed, finite size, an exponential growth in memory consumption will consume it with relative ease. The culling algorithm needs to be of a certain minimum efficiency to keep you from "blowing your stack" and losing your place repeatedly, and this is what is perceived as "speed."
I think you misinterpreted, though, that I meant that intelligence is the speed at which you solve macro-level problems. It certainly isn't. Intelligence is the speed at which you prune decisions; external to the mind, this affects the confidence you can take in your assertions, not the speed at which you reach them.
The more confident you are in lemma 1, the more quickly you can consciously decide to move onto lemma 2, and so on, but this requires some internal message passing that's much slower than the complete decision-branch path-finding "system call" in your mind. Your macro "problem-solving speed" is much more affected by the speed of the IRQ handler (the neocortex, I think), but if the system calls keep returning a low confidence interval, you have to keep consciously pulling apart intuitions into graphs of semantic knowledge, and passing each node to the path-finder in turn, until you feel sure enough of your decision to become aware of it. If your culling algorithm is more efficient (as directly measured by your score, not your time, on an IQ test) then you will become aware of things that others never will, because their minds are caught in loops that return false-negative confidences.
Sleep, then, gives your culling algorithm a larger fixed-bound on its runtime before it must return a confidence; this is why sleeping on something will let you make decisions that you felt involved too much complexity the day before. (Of course, sleeping does other things as well, like transferring things between short- and long- term memory (where they're stored--if they are stored--with a much lower path cost), and shutting off the neocortex so the mind doesn't constantly have to context-switch to ring 3 while it's trying to process things.)
I think you are focusing heavily on one particular model of an 'intelligence algorithm'. The model you are assuming sounds a lot like the type used for chess program. I played along with the 'culling algorithm' bit for the sake of convenience. But I'm not sure there is good enough evidence to assume that as the underlying model.
The definition of speed I am using is analogous to the clock speed or memory retrieval speed in a computer and it does seem at one level to be the way you are thinking of it as well. I think this fits in with what the researchers are measuring.
> The reason I didn't mention the possible variation in working memory capacity was a single word that I left out, leaving it, like I said, to the Computer Scientist: "exponential."
The memory requirements of a particular algorithm don't necessarily grow exponentially with the solution space or the input data. As with time complexity common space complexity relationships to the input size are n (you need to store at least the input), nlog(n), n^k and k^n. Most tractable problems would be nlog(n) or at worst n^k where k was small. The implication of this is that often small differences in memory can make a huge difference. Possibly you are forgetting that every extra bit of memory 'exponentially' increases the number of options it that can represent.
One of the first things you learn in CS algorithms is that the an efficient (let's say nlog(n)) algorithm running on a very slow computer will beat an inefficient one (say n^2) on a much faster computer. Sometimes resources such as memory will make the difference between being able to use an nlog(n) rather then a n^2 algorithm. To me this is a good analogue to apply to intelligence. For particular classes of problems (the harder ones) the better algorithm will trump a faster processor. Having a store of 'right algorithms' probably has a lot more to do with intelligence than raw thought speed.
Your view seems to be that the fundamental thinking algorithm is a fixed tree-pruning-like one. If it was then yes speed would be the main differentiating factor. I think this is the crux of our disagreement.
That's an interesting theory, but wrong. Having a larger short term memory makes you better at specific tests regardless of how fast you prune your decision tree. g relates to all useful mental process and is separate from how well you score on a specific IQ test.
EX: It's not part of most IQ test, but some people are really good at remembering what happened 3 flash cards ago others suck at it.
So what happens when each node in the decision tree has probability attached to it. Worse still, what happens when you do not know the true probabilities of these nodes. Now imagine you have to deal problems all day with uncertain characteristics, i.e., decision trees have nodes with unknown probabilities. You will be stuck, unable to make decision.
This also reminds of the study in which a person's emotional part of the brain was removed (forgot name of the part, its the one that uses hueristics). So, he would have to make every decision completely rationally. That caused him to take a very long time to make even the simplest decisions, like which pencil to choose amongst a set pencils to write with.
The more practice you have done, the faster you can finish your questions. So, I dont really think that they are just smarter. They may be just more hardworking.
And Thompson notes that our brains, unlike our bodies, peak relatively late in life.
"The wires between the brain cells, the connections, are the things that you can modify throughout life," he says. "They change and they improve through your 40s and 50s and 60s."
I haven't taken an IQ test, so I don't know exactly what that is like, but I've taken PSAT/ACT/GRE/GMAT tests, and it seems obvious to me that your performance on those tests is greatly influenced by how fast you can think.
If the IQ tests are anything like the other standardized tests, it is of absolutely no surprise to me that quick thinkers have higher IQs and I don't understand why it should come as a surprise to anyone else. Furthermore, assuming that IQ score depends on quick thinking, I'm not at all convinced that being smarter implies that you think faster.
"it is of absolutely no surprise to me that quick thinkers have higher IQs and I don't understand why it should come as a surprise to anyone else."
It's surprising to me because I do fairly well on IQ tests (top 2%), and yet I think more slowly than most people, and I have friends who are at least as intelligent as I (it seems to me) who are even slower than I am at figuring things out, but they do eventually get there, and often surpass me. It takes me longer to find the correct answer than many other people around me in almost any situation where they do find the correct answer. The difference seems more like finding the correct answer more often, rather than more quickly. While quickness of thought can provide the illusion of higher intelligence, I don't think it can have much to do with it in the long run; it doesn't matter how much you speed up a dog, he'll never figure out lots of things a chimpanzee can figure out -- intelligence seems almost orthogonal to speed to me.
It's possible though that this is analogous with running. An IQ test could be seem as a relative sprint whereas the business of solving genuinely complex problems might be a marathon.
A 'sprinting test' may actually provide a rough gauge of general fitness and physical ability - and in so doing be a rough predictor of marathon performance in the general populace. But at the higher levels those with fast twitch muscles are actually at a disadvantage in a marathon against those with slow twitch muscles. Extrapolating the sprint result to the marathon only works at the very crudest level.
Of course I'm not saying this is actually the case with intelligence but in certainly could be.
I think you may be able to hold the accomplishments/time ratio constant while varying the quickness of thought. However, the quickness of thought that I'm talking about may be different than what the article is addressing.
For example, in a math class it may take me a while to comprehend each step that the teacher is taking which makes me lag behind the rest of the class, but given enough time to fully understand everything, I can outperform the average without too much trouble. So it can be in the way that I attack problems. I slowly and methodically learn about all of its parts until I finally comprehend it all and then conquer it relatively quickly, whereas others may quickly learn about something but have to repeat the process a few more times to get it to sink in.
Maybe this kind of slowness has nothing to do with the speed at which nerve impulses travel, but it sure doesn't help with job interviews.
I've always thought of myself as really slow mentally. It always baffles me when I see and hear people in an oral discussion come up with interesting thoughts while they are talking. For me it always takes a couple of days of silent contemplation to see the interesting implications of something.
When people talk to me I sometimes just can't hear what they're saying, but whatever it is I stash the sound of it somewhere in my head so I can focus on processing it once they stop talking. The problem is of course that often people don't stop talking and the stack gets higher and higher until the bottom falls out and I stop paying attention completely. And if there's a TV in the room, it'll suck me in before anyone even says a word, and they'll have to yell and wave to get me back.
But when it does work out, I can recall their entire monologue word for word. I can still recall some of the things people have told me as much as 15 years ago, word for word. (My memory is a total sieve for other things though.)
Regardless, I'm pretty capable of thinking "big thoughts", say a recurring closure and how it affects/relates to the scope chain, the call stack, the namespace chain (Ruby is weird this way), and maybe a couple other complicating dimensions. It just takes a while to think big thoughts (though I've developed a gut feel for navigating scopes and such by now and it's pretty much instant).
All that said, I'm pretty sure it works this way for more people.
Don't fret, some believe Da Vinci and Einstein were the same way.
It's people like you that come up with the most worthwhile and well thought out ideas.
People like me (rapid prototyping/speedy hashers of ideas) are mostly useless. It's beyond words difficult for me to put feet to floor and completely formulate, systematize, and write out a philosophical idea.
I come up with neat ideas, but they die just as quickly.
I systematized the entirety of order and chaos once, connected it with primitive human origins, and have mostly let it lie and do nothing for example.
If this is true, then it seems plausible to optimize for response cycle speed and iteration to evaluate solutions to problems, regardless of one's raw intelligence (whatever that means).
This measure does, however, tend to lean towards problem-solving speed as the primary indicator of intelligence and that's probably not the most accurate way of measuring it.
The argument against this I've heard is that if a dog could think 1000x faster, it would still only have dog thoughts but a 1000x more of them.
There must be something more to intelligence than just speed. Perhaps working memory is very important? Perhaps it's just having the right software in your head i.e., knowing how to solve problems and frame things?
This research seems to be suggesting that auditory-sequential (AS) learners are more intelligent, i.e., have higher IQ, than visual spatial (VS) learners.
If IQ is the measure of intelligence, then certainly, AS would be regarded as more intelligent. That is why AS learners do better at every single test that is timed or requires quickness of thought, be it SAT/GRE, mensa or job interviews at microsoft/google or a wall street bank or hedge fund.
Ai. Once more a journalistic report that confuses having a high IQ with being smart. This is not the current thinking among the best researchers on human intelligence.
As the current researchers put it, you can be "intelligent" (= score high on IQ tests) without being "rational" (above reference) or wise (below reference).
But this idea goes back a lot further, all the way to the beginning of IQ testing. Lewis Terman himself wrote, "There are, however, certain characteristics of age scores with which the reader should be familiar. For one thing, it is necessary to bear in mind that the true mental age as we have used it refers to the mental age on a particular intelligence test. A subject's mental age in this sense may not coincide with the age score he would make in tests of musical ability, mechanical ability, social adjustment, etc. A subject has, strictly speaking, a number of mental ages; we are here concerned only with that which depends on the abilities tested by the new Stanford-Binet scales." (Terman & Merrill 1937, p. 25)
Ian Deary has very trenchant comments on how poorly understood "ability to think quickly" is in his book Looking Down on Human Intelligence: From Psychometrics to the Brain
But, really, the obligatory link for any discussion of a report on a research result like that is the article by Peter Norvig, director of research at Google, on how to interpret scientific research.
"Just because intelligence is strongly genetic, that doesn't mean it cannot be improved. 'It's just the opposite,' says Richard Haier, of the University of California, Irvine, who works with Thompson. 'If it's genetic, it's biochemical, and we have all kinds of ways of influencing biochemistry.'"
Smart people tend to be good ping pong players too, if they try, because you have to process so much information in such a short time, and then act on it.
If you think while playing then you cant play well. I play reasonable good ping pong, and many times I am also watching me play.I do not know what I will do because I did not decide consciously.
I often found in school / college that I could answer all the questions on tests and exams but not in the time given. It always felt a little unfair that others who were actually less capable sometimes got higher scores simply because they were faster at those parts they could do.