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> It is Kepecs' thesis that statistics - generated by the objective processing of sensory and other data - is the ultimate language of the brain. Every time I

> It is Kepecs' thesis that statistics - generated by the objective processing of sensory and other data - is the ultimate language of the brain. Every time I read stuff like this, I lose more confidence that the scientific method as currently applied, funded, and published is capable of truly conquering complex systems like the brain or nutrition. I read article after article like this one, where a prominent researcher conducts some experiment that shows some result. But listening to that person talk about their work, it becomes clear that this has become their pet theory that they want to be capable of explaining everything. As if everything we know about some system will someday be shown to be reducible to one clean, beautiful idea. Here are a few quick reasons why I find this idea to be highly implausible: - There are a dizzying number of documented cognitive biases in humans. If statistics is the ultimate language of the brain, our software is pretty thoroughly buggy: https://en.wikipedia.org/wiki/List_of_cognitive_biases https://en.wikipedia.org/wiki/List_of_cognitive_biases - Belief motivates people to do things that have absolutely no statistical justification. For example, the time that the prophecy of a teenage girl convinced a tribe of people in present-day South Africa to kill 300,000 - 400,000 of their own cattle, leading to the starvation and death of 20,000 - 40,000 people. How does a brain built on statistics decide that this is the most rational course of action? http://persistentfrontiers.com/xhosacattlekilling/ http://persistentfrontiers.com/xhosacattlekilling/ EDIT: Several people are replying with some form of: "your examples can still show that the mind is inherently built on statistics if you think about it in way X." Let's do a quick experiment to see if this theory is actually falsifiable. What experiment/result would convince you that statistics is not "the ultimate language of the brain?"

Lxr 11y ago
> How does a brain built on statistics decide that this is the most rational course of action? The article suggests that humans have an innate means of determining confidence in a particular hypothesis based on evidence. Why does this imply they act rationally?
- haberman 11y ago
  > The article suggests that humans have an innate means of determining confidence in a particular hypothesis based on evidence. Yes. In my example, the hypothesis is "killing all of our cattle will make the spirits of our ancestors come to our aid." The evidence supporting this hypothesis was nonexistent. And yet the people expressed extreme confidence in this hypothesis by killing all of their cattle.
  - gph 11y ago
    >The evidence supporting this hypothesis was nonexistent The rational evidence was nonexistent. I don't think this theory is necessarily built on the idea that humans evaluate evidence rationally.
  - everly 11y ago
    I think you're using a definition of 'evidence' that is too narrow or perhaps too logical, although I agree with pretty much everything you're saying. I think that the statistical theory is possible but certainly couldn't be objective (one big reason being the cognitive biases you mentioned). Meaning a person will do the necessary mental gymnastics to assign the necessary value to the variable 'evidence' that their brain uses. In your example, I think some combination of religious belief, regret avoidance, and herd thinking all added up to equal the requisite 'evidence' needed to express confidence in the cattle killing hypothesis.
  - dperfect 11y ago
    Perhaps it would be more accurate to say "humans have an innate means of determining confidence in a particular hypothesis based on perceived evidence". From an objective standpoint, evidence is either black or white. But for our brains, beliefs and biases may be given equal weight with objective truth. Whether or not those beliefs are rooted in truth is a question ultimately controlled by each person's worldview and their understanding of scientific reasoning. The underlying algorithms may still be based on statistics, albeit statistics with unreliable data. Or, in the example provided, perhaps the tribe's statistical models were warped enough by cultural/religious/conventional wisdom (unreliable data) that they really did express a high level of confidence in an otherwise outlandish idea - a confidence based on statistically sound evaluation, only fed with bad data.
webaba 11y ago
You're so right, actually there is nothing new in this idea. Kalman filters (so basically belief propagation based on gaussian observations) were already used by DL Kleinman in 1970 to model aircraft pilots behavior. We are way past this simplistic hypothesis. Actually, quantum dynamics (yeah why not, it's just a model) seem to better describe human decision making than classical stochastic models (Quantum dynamics of human decision-making - http://www.sciencedirect.com/science/article/pii/S002224960600006X http://www.sciencedirect.com/science/article/pii/S0022249606...)
Bartweiss 11y ago
While I agree that this seems like "scientist has pet theory, does study to prove it", I don't think the bias/irrationality claims disprove much. The way to reconcile those claims is to say that many of our statistical/estimation patterns are very bad. Mostly, they were good once, but are completely unequipped to deal with the modern world. I know "we're optimized for the savannah" is a laugh-line at this point, but it doesn't seem absurd to claim that we're using statistical techniques that are easy but inflexible. Flawless Bayesian updating is basically unachievable, and a lot of our biases seem like once-useful heuristics that screw us a lot in the modern world. Tetlock's Superforcasting seems like a good reference here: it's a study of people who are uncommonly good at estimating future probabilities. These are people who estimate near-future events to better than half a percent (as in, rounding from .1% to .5% reliably lowers their accuracy). Most of them claim to use a lot of numerical probability estimates, which suggests that they might be employing an existing system consciously to get the bugs out. None of this means I buy the study, but I'm not willing to reject the hypothesis, either. Given that we're running on neural nets, I wouldn't be surprised if we deal in actually probabilities and are just exceedingly bad at it.
- haberman 11y ago
  > The way to reconcile those claims is to say that many of our statistical/estimation patterns are very bad. If studies like this one are taken as evidence of a statistical mind, then non-statistical behavior has to be taken as evidence of a non-statistical mind. Otherwise we have a non-falsifiable theory. Experiment shows mind behaving statistically: "mind is statistical." Experiment shows mind behaving non-statistically: "mind is statistical, but this scenario exceeds its capabilities." > which suggests that they might be employing an existing system consciously to get the bugs out. I should clarify -- I have nothing against the idea that our minds employ statistical methods. In fact I'm sure they must. I'm opposed to taking that kernel of truth and pushing a reductionist understanding of something extremely complex (the brain).
  - taeric 11y ago
    Don't confuse non-statistical with non-rational. In particular, people that come to a different conclusion than you could just have different priors in their Bayesian model, but still be statistical in their intake of information. Though... I think I agree that this weakens the claim sufficiently to not be a notable claim anymore.
steego 11y ago
> For example, the time that the prophecy of a teenage girl convinced a tribe of people in present-day South Africa to kill 300,000 - 400,000 of their own cattle, leading to the starvation and death of 20,000 - 40,000 people. How does a brain built on statistics decide that this is the most rational course of action? That's actually a really good example of statistics deciding a course of action. Ask yourself this? Why did they believe it? It's most likely that group of people were repeatedly told stories that belongs to a larger framework of belief. What you might not understand is good literature has a tendency to fire parts of the brain related to sight, sound and touch in an fMRI. For so many people, a good story creates a parallel quasi-reality, and I wouldn't be surprised their brain is basically chalking up those stories as real experiences. I was just listening to a story on This American Life about some kids whose prom was interrupted by a tornado. What shocked me was how many of these kids created internal narratives that they somehow caused the storm, or the storm was manifested as a personal lesson for them. If you think about the garbage plot lines and religious upbringing people absorb, this sort of narcissistic outlook makes a tremendous amount of sense. I'll add this one point. Modern public relations and politics feeds on the principle that you can manufacture reality by constantly bombarding people with the same shallow message. It doesn't matter what you say as much as how loud and frequent you're saying it.
- haberman 11y ago
  > What shocked me was how many of these kids created internal narratives that they somehow caused the storm, or the storm was manifested as a personal lesson for them. Exactly. I would argue that internal narratives like this are inherently anti-statistical. They attempt to give greater meaning to something than the direct observations support. What experiment would convince you that statistics is not "the ultimate language of the brain?"
  - steego 11y ago
    I'm not necessarily convinced statistics is the ultimate language of the brain. Like you, I imagine there are a number of legacy systems in the brain that coordinate in interesting ad-hoc ways. What do you think I should read?
Maken 11y ago
I think you are also applying a biased viewpoint. Your are assuming rational decision making always leads to "correct" decisions. Statistics and rationality merely work by measuring current events against your previous experiences and inferring the most probable outcome of your possible actions. That means that your previous life experiences and how you have interpreted and classified them are key in what your brain is going to expect from future events and in consequence how you are going to react to them. In your example you are assuming these people are acting "irrationally" because they aren't taking the "correct" decision by your own judgment. The reality is that likely they are acting based on very different premises from your own, extracted from their own life experiences and those of their ancestors. Given the outcome, they were clearly wrong on their conclusions, but that only means that rationality and statistics are useless if you are basing your reasonings on wrong premises and there is no mechanism to stop you from feeding them the wrong data, not that these seemly absurd actions didn't have a somewhat rational justification. About cognitive biases, well, your brain makes decisions based on the data it has available, and whenever it is insufficient it can't simply delay decision making until its confidence level is acceptable, hence it needs some heuristics to guarantee it gets a result whenever enough previous experience is lacking.
- haberman 11y ago
  > Your are assuming rational decision making always leads to "correct" decisions. I didn't say anything of the sort. > The reality is that likely they are acting based on very different premises from your own, extracted from their own life experiences and those of their ancestors. That is true. That doesn't imply however that their beliefs draw solid statistical conclusion from those experiences. For example, take rituals like rainmaking that are intended to change the weather. These were performed over many years and generations, and yet (we presume) never brought about any actual statistical improvement over not performing them. Those people would have experienced that (lack of) improvement directly. And yet they continued to believe it.
  - nickpsecurity 11y ago
    "For example, take rituals like rainmaking that are intended to change the weather. These were performed over many years and generations, and yet (we presume) never brought about any actual statistical improvement over not performing them. Those people would have experienced that (lack of) improvement directly. And yet they continued to believe i" That's a great example given it is long-term, repetitive, and even non-experts should understand it. I'm going to try to remember it.
duaneb 11y ago
Hah, I agree with the disillusionment with the process but only because I see that statistics is OBVIOUSLY the ultimate language of the brain—how else would you explain neural networks, inductive logic, and linguistic disambiguation?
jlgray 11y ago
To quote wikipedia's article on statistics: Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. Isn't that more or less what human brains do? A neural network is just a curve fitting algorithm optimized to fit a bunch of data, that is, a statistical method. NNs are, to the best of my knowledge, a fairly good analogy for what the physical computation process of the brain. NNs are also very easy to fool. Mislabel the humans in your robot training data as 'kill', and your network will make bad decisions. Garbage in, garbage out. If you make a probabilistic model and attach a very high confidence to the things that spirits tell little girls down by the river, then sometimes your model will suggest some terrible ideas. Humans are also notoriously bad at sampling data, but that doesn't mean it isn't what they're doing. Your edit raises a good question, though! I can't say I have a good answer, but would be interested to hear a good idea for such an experiment. I want to use the phenomenon the inner monologue and the act of convincing oneself of something as a counter example, but on the other hand, language is very easily generated by statistical methods, and the brain apparently will make decisions and then come up with justifications afterward. http://pss.sagepub.com/content/early/2016/04/27/0956797616641943.abstract http://pss.sagepub.com/content/early/2016/04/27/095679761664...
- haberman 11y ago
  > Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. Isn't that more or less what human brains do? I think you have expanded the meaning of statistics beyond what is understood in the article. The originally understood meaning is "numerically/theoretically justifiable inferences given a set of input data." Now you're taking it to mean "any data-processing pipeline." By this large and more abstract definition, here are some more things that are based on statistics: - tabloid newspapers - religious sermons - sundials - televisions
- twinkletwinkle 11y ago
  >Isn't that more or less what human brains do? Sure but now what are you demonstrating. "The human brain collects and interprets data". Great paper, thanks for the contribution to science.
yummyfajitas 11y ago
Ultimately to prove that statistics is not fundamentally the language of the brain, you'd need to find behaviors that are fundamentally incompatible with statistics. Luckily the conjunction fallacy qualifies: https://en.wikipedia.org/wiki/Conjunction_fallacy https://en.wikipedia.org/wiki/Conjunction_fallacy
eric_h 11y ago
If I may riff on this rather unscientifically from my own anecdotal observations of how my own brain works: I do not agree with TFAs assertion that "The feeling ultimately relies on the same statistical computations a computer would make". I would agree, however, that one factor (of an undetermined number of factors) of decision making is something that roughly resembles statistical computation. The key difference is that our input data for these "computations" is absolute crap, and heavily influenced by any number of things, including confirmation bias, small sample size, selective memory, etc. Let me draw an example of my many years and thousands of hours of play in a game that is dominated by statistics, pool (billiards): Beginners at the game develop all sorts of incorrect assumptions about how likely a given shot is to succeed, informed by their insufficient sample size. "I made that shot three times in a row last night, why would I miss it this time?" This is, of course, the equivalent of "I hit 13 on the roulette wheel 3 times in a row last night, why would I miss it this time". As you build experience, you start to get a more correct intuitive understanding of the actual statistical likelihood of a given shot going in, but it is still affected by selection bias, and a number of other factors. The way (well, some) professional and semi-professional pool players have attempted to eliminate this bias is by actually taking notes on the types of shots they take and actually collecting the true statistics. Even then, after collecting this data for months/years, when confronted with a shot that, statistically, they are more likely to miss than to make, they will still assign an incorrect confidence level to their decision, particularly when they are in, say, the finals of a tournament with a big payday (adrenaline is bad for rational thought, though it can occasionally help you operate at the right edge of the bell curve of your "normal" ability, hence, poorly computed bias). I don't think that we can boil the decision making process of the brain down to something as simple as a NN, or bayesian inference or whatever. I do, however, think that the brain does attempt a flawed statistical inference as one of many factors in making decisions. (Note: i'm not anywhere near a professional pool player, nor will I ever be or desire to be, but I've brushed shoulders with some of the best in the world, so I believe I've got a modicum of observational authority on the matter. I also think it's a pretty good example of our brain trying and failing to properly infer the statistical likelihood of a given outcome; chance based gambling is another good one)
cortesoft 11y ago
You can't take any single act, where something goes wrong, and conclude that they obviously made the irrational choice. Sometimes, you can make the correct decision and still have a bad outcome. If someone offers you even money that they can roll double sixes on a pair of dice, the rational and logical decision is to take the bet. The rationality of the decision doesn't change if they happen to roll double sixes, it just means you got unlucky.
- haberman 11y ago
  > You can't take any single act, where something goes wrong, and conclude that they obviously made the irrational choice. Sure you can. If you flip a coin 1M times and it always comes up heads or tails, and then you bet $100 that the next flip will come up daisies, you can conclude that I obviously made the irrational choice. Because there is no evidence to support the idea that this will happen. Also, in your own example, we can say that it's irrational not to take the bet (if you can afford to lose the money), because statistically your expected value is strongly positive for taking the bet.
  - cortesoft 11y ago
    I think you are misinterpreting what I am saying. I am not saying that you can't judge a single action as being irrational, I am saying that you can make the rational decision and still lose. Therefore, the mere fact that some action lead to a bad result is not sufficient to show that the decision was irrational.
tgflynn 11y ago
Saying that "statistics is the ultimate language of the brain" doesn't imply that the brain always performs statistical calculations correctly. In fact finding the true correct Bayesian answer is probably computationally infeasible for all but the simplest problems. We already have this problem with artificial neural networks, which are still much simpler than the networks in the brain. ANN's have recently achieved significant successes and approach or exceed human performance on some tasks. They still however make mistakes and no one is claiming that they represent the optimal Bayesian solution, they are just the best solutions that we have so far been able to find. I think the same thing happens in the human brain but can lead to behavior that is much more extremely erroneous due to the greater complexity of the brain as well as that of the domains to which it finds itself applied. But that doesn't mean that the brain isn't based on statistical models anymore than the fact that ANN's aren't perfect means that they are not statistical models. They are statistical models but they are heuristic models, not perfect models.
hathawsh 11y ago
Consider hypnosis. If we could find a way to hypnotize people from many different backgrounds into believing some specific wild assertion, regardless of how much that assertion conflicts with their beliefs, that would be strong evidence against the hypothesis that statistics is the ultimate language of the brain. The results would suggest that a lower-level language exists and that hypnosis somehow taps into that language. People get concerned about hypnosis precisely because they believe it may access a lower level of their brain that they can't control very well. People want to believe that their thinking is in fact rooted in statistical modeling rather than things they can't control. I tend to believe our thinking is influenced by many things, including things we aren't in control of, but when we discover elements of our thoughts that we don't control, we can slowly take control of them. For example, we can slowly overcome habits and addictions.
nerdponx 11y ago
The bug here is not that humans calculate expected payoffs incorrectly, it's that they have wildly inaccurate estimates of tpayoffs and their probabilities. Subtle but important difference
Balgair 11y ago
> What experiment/result would convince you that statistics is not "the ultimate language of the brain?" Reflexes, like in your knee. Your spinal cord is very much part of your brain and the pateller tendon reflex is nearly 100% with 'healthy' people. Perhaps the statistical nature of the brain comes from measuring many people to get the right sampling power for the experiment. Genetics and the stochastic behavior of life then influence these brains to behave in statistical ways compared to each other. Twins studies should bear that out as true or false.
powera 11y ago
What the heck does "ultimate language of the brain" even mean? I literally can't even speculate what it's supposed to mean.
nl 11y ago
The theory isn't that "statistics are the ultimate language of the brain". That's just a summary designed for popular consumption. Unfortunately the links to the source article don't work, but from careful reading it appears that the real theory is that the brain tracks confidence in its measurement of data, and uses this confidence when making decisions. This is a Bayesian approach, and it has been widely speculated that the brain does this. This theory is falsifiable, because you can ask people their confidence in the original measurements, their confidence in a decision depending on that, and then use Bayes' rule to see if those confidences have propagated. Quote: In experiments with human subjects, Kepecs and colleagues therefore tried to control for different factors that can vary from person to person. The aim was to establish what evidence contributed to each decision. In this way they could compare people's reports of confidence with the optimal statistical answer. "If we can quantify the evidence that informs a person's decision, then we can ask how well a statistical algorithm performs on the same evidence" They go on to describe a video game experiment. I suspect that the description is incomplete, and there is a decision making component to the game that depends on how frequently the person thinks they are hearing the clicks. If that is the case then that answers your question about how to falsify it.
- haberman 11y ago
  > The theory isn't that "statistics are the ultimate language of the brain". That's not the theory of this specific paper, but the says that this researcher considers this paper a "first step" towards this more general theory. > This theory is falsifiable, because you can ask people their confidence in the original measurements, their confidence in a decision depending on that, and then use Bayes' rule to see if those confidences have propagated. If your standard is that humans will apply Bayes' theorem correctly, completely intuitively, as more evidence becomes available, I think it will be very easy to falsify that.
  - nl 11y ago
    If your standard is that humans will apply Bayes' theorem correctly, completely intuitively, as more evidence becomes available, I think it will be very easy to falsify that. Yes. And there is increasing evidence that this is correct. See[1]. If you can find a copy, I think [2] will address many of your concerns about seemingly irrational behavior being supported by statistical reasoning. [1] https://en.wikipedia.org/wiki/Bayesian_approaches_to_brain_function https://en.wikipedia.org/wiki/Bayesian_approaches_to_brain_f... [2] http://www.ncbi.nlm.nih.gov/pubmed/19477333 http://www.ncbi.nlm.nih.gov/pubmed/19477333
cel1ne 11y ago
What I find very peculiar is that everybody talks about AI but no one mentions how the brain is comprised of many different areas that work differently and regulate each other. It's not all the prefrontal cortex detecting patterns. The kind of signal the amygdala fires because of a change in body temperature is different than a "pixel" changing in your visual cortex.
Houshalter 11y ago
Human brains do statistics at a low level. This is what the experiment tested. An example experiment would be if you gave someone a rewards with different probabilities after some random event like clicking, and the brain would learn to estimate the probability that a sequence of clicks would lead to a reward. On a high level this obviously breaks down. The brain doesn't have thousands of examples of slaughtering cows leading to starvation. Cognitive biases all operate at a high level of reasoning, and involve verbal arguments and stuff. But on a low level, the brain is absolutely statistically based.
- webaba 11y ago
  This is actually completely incorrect. Many cognitive biases occur at low levels of cognition without involving language, take professional pilots and confirmation biases despite of a ton of training data.
  - Houshalter 11y ago
    I think professional pilots are still making mistakes at a higher level. By "low level" I mean things your brain does in a split second without thinking about.
darkxanthos 11y ago
A better example is the Monty Hall problem. Very few people find this intuitive.

Lxr 11y ago

> How does a brain built on statistics decide that this is the most rational course of action? The article suggests that humans have an innate means of determining confidence in a particular hypothesis based on evidence. Why does this imply they act rationally?

haberman 11y ago
> The article suggests that humans have an innate means of determining confidence in a particular hypothesis based on evidence. Yes. In my example, the hypothesis is "killing all of our cattle will make the spirits of our ancestors come to our aid." The evidence supporting this hypothesis was nonexistent. And yet the people expressed extreme confidence in this hypothesis by killing all of their cattle.
- gph 11y ago
  >The evidence supporting this hypothesis was nonexistent The rational evidence was nonexistent. I don't think this theory is necessarily built on the idea that humans evaluate evidence rationally.
- everly 11y ago
  I think you're using a definition of 'evidence' that is too narrow or perhaps too logical, although I agree with pretty much everything you're saying. I think that the statistical theory is possible but certainly couldn't be objective (one big reason being the cognitive biases you mentioned). Meaning a person will do the necessary mental gymnastics to assign the necessary value to the variable 'evidence' that their brain uses. In your example, I think some combination of religious belief, regret avoidance, and herd thinking all added up to equal the requisite 'evidence' needed to express confidence in the cattle killing hypothesis.
- dperfect 11y ago
  Perhaps it would be more accurate to say "humans have an innate means of determining confidence in a particular hypothesis based on perceived evidence". From an objective standpoint, evidence is either black or white. But for our brains, beliefs and biases may be given equal weight with objective truth. Whether or not those beliefs are rooted in truth is a question ultimately controlled by each person's worldview and their understanding of scientific reasoning. The underlying algorithms may still be based on statistics, albeit statistics with unreliable data. Or, in the example provided, perhaps the tribe's statistical models were warped enough by cultural/religious/conventional wisdom (unreliable data) that they really did express a high level of confidence in an otherwise outlandish idea - a confidence based on statistically sound evaluation, only fed with bad data.

webaba 11y ago

You're so right, actually there is nothing new in this idea. Kalman filters (so basically belief propagation based on gaussian observations) were already used by DL Kleinman in 1970 to model aircraft pilots behavior. We are way past this simplistic hypothesis. Actually, quantum dynamics (yeah why not, it's just a model) seem to better describe human decision making than classical stochastic models (Quantum dynamics of human decision-making - http://www.sciencedirect.com/science/article/pii/S002224960600006X http://www.sciencedirect.com/science/article/pii/S0022249606...)

Bartweiss 11y ago

While I agree that this seems like "scientist has pet theory, does study to prove it", I don't think the bias/irrationality claims disprove much. The way to reconcile those claims is to say that many of our statistical/estimation patterns are very bad. Mostly, they were good once, but are completely unequipped to deal with the modern world. I know "we're optimized for the savannah" is a laugh-line at this point, but it doesn't seem absurd to claim that we're using statistical techniques that are easy but inflexible. Flawless Bayesian updating is basically unachievable, and a lot of our biases seem like once-useful heuristics that screw us a lot in the modern world. Tetlock's Superforcasting seems like a good reference here: it's a study of people who are uncommonly good at estimating future probabilities. These are people who estimate near-future events to better than half a percent (as in, rounding from .1% to .5% reliably lowers their accuracy). Most of them claim to use a lot of numerical probability estimates, which suggests that they might be employing an existing system consciously to get the bugs out. None of this means I buy the study, but I'm not willing to reject the hypothesis, either. Given that we're running on neural nets, I wouldn't be surprised if we deal in actually probabilities and are just exceedingly bad at it.

haberman 11y ago
> The way to reconcile those claims is to say that many of our statistical/estimation patterns are very bad. If studies like this one are taken as evidence of a statistical mind, then non-statistical behavior has to be taken as evidence of a non-statistical mind. Otherwise we have a non-falsifiable theory. Experiment shows mind behaving statistically: "mind is statistical." Experiment shows mind behaving non-statistically: "mind is statistical, but this scenario exceeds its capabilities." > which suggests that they might be employing an existing system consciously to get the bugs out. I should clarify -- I have nothing against the idea that our minds employ statistical methods. In fact I'm sure they must. I'm opposed to taking that kernel of truth and pushing a reductionist understanding of something extremely complex (the brain).
- taeric 11y ago
  Don't confuse non-statistical with non-rational. In particular, people that come to a different conclusion than you could just have different priors in their Bayesian model, but still be statistical in their intake of information. Though... I think I agree that this weakens the claim sufficiently to not be a notable claim anymore.

steego 11y ago

> For example, the time that the prophecy of a teenage girl convinced a tribe of people in present-day South Africa to kill 300,000 - 400,000 of their own cattle, leading to the starvation and death of 20,000 - 40,000 people. How does a brain built on statistics decide that this is the most rational course of action? That's actually a really good example of statistics deciding a course of action. Ask yourself this? Why did they believe it? It's most likely that group of people were repeatedly told stories that belongs to a larger framework of belief. What you might not understand is good literature has a tendency to fire parts of the brain related to sight, sound and touch in an fMRI. For so many people, a good story creates a parallel quasi-reality, and I wouldn't be surprised their brain is basically chalking up those stories as real experiences. I was just listening to a story on This American Life about some kids whose prom was interrupted by a tornado. What shocked me was how many of these kids created internal narratives that they somehow caused the storm, or the storm was manifested as a personal lesson for them. If you think about the garbage plot lines and religious upbringing people absorb, this sort of narcissistic outlook makes a tremendous amount of sense. I'll add this one point. Modern public relations and politics feeds on the principle that you can manufacture reality by constantly bombarding people with the same shallow message. It doesn't matter what you say as much as how loud and frequent you're saying it.

haberman 11y ago
> What shocked me was how many of these kids created internal narratives that they somehow caused the storm, or the storm was manifested as a personal lesson for them. Exactly. I would argue that internal narratives like this are inherently anti-statistical. They attempt to give greater meaning to something than the direct observations support. What experiment would convince you that statistics is not "the ultimate language of the brain?"
- steego 11y ago
  I'm not necessarily convinced statistics is the ultimate language of the brain. Like you, I imagine there are a number of legacy systems in the brain that coordinate in interesting ad-hoc ways. What do you think I should read?

Maken 11y ago

I think you are also applying a biased viewpoint. Your are assuming rational decision making always leads to "correct" decisions. Statistics and rationality merely work by measuring current events against your previous experiences and inferring the most probable outcome of your possible actions. That means that your previous life experiences and how you have interpreted and classified them are key in what your brain is going to expect from future events and in consequence how you are going to react to them. In your example you are assuming these people are acting "irrationally" because they aren't taking the "correct" decision by your own judgment. The reality is that likely they are acting based on very different premises from your own, extracted from their own life experiences and those of their ancestors. Given the outcome, they were clearly wrong on their conclusions, but that only means that rationality and statistics are useless if you are basing your reasonings on wrong premises and there is no mechanism to stop you from feeding them the wrong data, not that these seemly absurd actions didn't have a somewhat rational justification. About cognitive biases, well, your brain makes decisions based on the data it has available, and whenever it is insufficient it can't simply delay decision making until its confidence level is acceptable, hence it needs some heuristics to guarantee it gets a result whenever enough previous experience is lacking.

haberman 11y ago
> Your are assuming rational decision making always leads to "correct" decisions. I didn't say anything of the sort. > The reality is that likely they are acting based on very different premises from your own, extracted from their own life experiences and those of their ancestors. That is true. That doesn't imply however that their beliefs draw solid statistical conclusion from those experiences. For example, take rituals like rainmaking that are intended to change the weather. These were performed over many years and generations, and yet (we presume) never brought about any actual statistical improvement over not performing them. Those people would have experienced that (lack of) improvement directly. And yet they continued to believe it.
- nickpsecurity 11y ago
  "For example, take rituals like rainmaking that are intended to change the weather. These were performed over many years and generations, and yet (we presume) never brought about any actual statistical improvement over not performing them. Those people would have experienced that (lack of) improvement directly. And yet they continued to believe i" That's a great example given it is long-term, repetitive, and even non-experts should understand it. I'm going to try to remember it.

duaneb 11y ago

Hah, I agree with the disillusionment with the process but only because I see that statistics is OBVIOUSLY the ultimate language of the brain—how else would you explain neural networks, inductive logic, and linguistic disambiguation?

jlgray 11y ago

To quote wikipedia's article on statistics: Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. Isn't that more or less what human brains do? A neural network is just a curve fitting algorithm optimized to fit a bunch of data, that is, a statistical method. NNs are, to the best of my knowledge, a fairly good analogy for what the physical computation process of the brain. NNs are also very easy to fool. Mislabel the humans in your robot training data as 'kill', and your network will make bad decisions. Garbage in, garbage out. If you make a probabilistic model and attach a very high confidence to the things that spirits tell little girls down by the river, then sometimes your model will suggest some terrible ideas. Humans are also notoriously bad at sampling data, but that doesn't mean it isn't what they're doing. Your edit raises a good question, though! I can't say I have a good answer, but would be interested to hear a good idea for such an experiment. I want to use the phenomenon the inner monologue and the act of convincing oneself of something as a counter example, but on the other hand, language is very easily generated by statistical methods, and the brain apparently will make decisions and then come up with justifications afterward. http://pss.sagepub.com/content/early/2016/04/27/0956797616641943.abstract http://pss.sagepub.com/content/early/2016/04/27/095679761664...

haberman 11y ago
> Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. Isn't that more or less what human brains do? I think you have expanded the meaning of statistics beyond what is understood in the article. The originally understood meaning is "numerically/theoretically justifiable inferences given a set of input data." Now you're taking it to mean "any data-processing pipeline." By this large and more abstract definition, here are some more things that are based on statistics: - tabloid newspapers - religious sermons - sundials - televisions
twinkletwinkle 11y ago
>Isn't that more or less what human brains do? Sure but now what are you demonstrating. "The human brain collects and interprets data". Great paper, thanks for the contribution to science.

yummyfajitas 11y ago

Ultimately to prove that statistics is not fundamentally the language of the brain, you'd need to find behaviors that are fundamentally incompatible with statistics. Luckily the conjunction fallacy qualifies: https://en.wikipedia.org/wiki/Conjunction_fallacy https://en.wikipedia.org/wiki/Conjunction_fallacy

eric_h 11y ago

If I may riff on this rather unscientifically from my own anecdotal observations of how my own brain works: I do not agree with TFAs assertion that "The feeling ultimately relies on the same statistical computations a computer would make". I would agree, however, that one factor (of an undetermined number of factors) of decision making is something that roughly resembles statistical computation. The key difference is that our input data for these "computations" is absolute crap, and heavily influenced by any number of things, including confirmation bias, small sample size, selective memory, etc. Let me draw an example of my many years and thousands of hours of play in a game that is dominated by statistics, pool (billiards): Beginners at the game develop all sorts of incorrect assumptions about how likely a given shot is to succeed, informed by their insufficient sample size. "I made that shot three times in a row last night, why would I miss it this time?" This is, of course, the equivalent of "I hit 13 on the roulette wheel 3 times in a row last night, why would I miss it this time". As you build experience, you start to get a more correct intuitive understanding of the actual statistical likelihood of a given shot going in, but it is still affected by selection bias, and a number of other factors. The way (well, some) professional and semi-professional pool players have attempted to eliminate this bias is by actually taking notes on the types of shots they take and actually collecting the true statistics. Even then, after collecting this data for months/years, when confronted with a shot that, statistically, they are more likely to miss than to make, they will still assign an incorrect confidence level to their decision, particularly when they are in, say, the finals of a tournament with a big payday (adrenaline is bad for rational thought, though it can occasionally help you operate at the right edge of the bell curve of your "normal" ability, hence, poorly computed bias). I don't think that we can boil the decision making process of the brain down to something as simple as a NN, or bayesian inference or whatever. I do, however, think that the brain does attempt a flawed statistical inference as one of many factors in making decisions. (Note: i'm not anywhere near a professional pool player, nor will I ever be or desire to be, but I've brushed shoulders with some of the best in the world, so I believe I've got a modicum of observational authority on the matter. I also think it's a pretty good example of our brain trying and failing to properly infer the statistical likelihood of a given outcome; chance based gambling is another good one)

cortesoft 11y ago

You can't take any single act, where something goes wrong, and conclude that they obviously made the irrational choice. Sometimes, you can make the correct decision and still have a bad outcome. If someone offers you even money that they can roll double sixes on a pair of dice, the rational and logical decision is to take the bet. The rationality of the decision doesn't change if they happen to roll double sixes, it just means you got unlucky.

haberman 11y ago
> You can't take any single act, where something goes wrong, and conclude that they obviously made the irrational choice. Sure you can. If you flip a coin 1M times and it always comes up heads or tails, and then you bet $100 that the next flip will come up daisies, you can conclude that I obviously made the irrational choice. Because there is no evidence to support the idea that this will happen. Also, in your own example, we can say that it's irrational not to take the bet (if you can afford to lose the money), because statistically your expected value is strongly positive for taking the bet.
- cortesoft 11y ago
  I think you are misinterpreting what I am saying. I am not saying that you can't judge a single action as being irrational, I am saying that you can make the rational decision and still lose. Therefore, the mere fact that some action lead to a bad result is not sufficient to show that the decision was irrational.

tgflynn 11y ago

Saying that "statistics is the ultimate language of the brain" doesn't imply that the brain always performs statistical calculations correctly. In fact finding the true correct Bayesian answer is probably computationally infeasible for all but the simplest problems. We already have this problem with artificial neural networks, which are still much simpler than the networks in the brain. ANN's have recently achieved significant successes and approach or exceed human performance on some tasks. They still however make mistakes and no one is claiming that they represent the optimal Bayesian solution, they are just the best solutions that we have so far been able to find. I think the same thing happens in the human brain but can lead to behavior that is much more extremely erroneous due to the greater complexity of the brain as well as that of the domains to which it finds itself applied. But that doesn't mean that the brain isn't based on statistical models anymore than the fact that ANN's aren't perfect means that they are not statistical models. They are statistical models but they are heuristic models, not perfect models.

hathawsh 11y ago

Consider hypnosis. If we could find a way to hypnotize people from many different backgrounds into believing some specific wild assertion, regardless of how much that assertion conflicts with their beliefs, that would be strong evidence against the hypothesis that statistics is the ultimate language of the brain. The results would suggest that a lower-level language exists and that hypnosis somehow taps into that language. People get concerned about hypnosis precisely because they believe it may access a lower level of their brain that they can't control very well. People want to believe that their thinking is in fact rooted in statistical modeling rather than things they can't control. I tend to believe our thinking is influenced by many things, including things we aren't in control of, but when we discover elements of our thoughts that we don't control, we can slowly take control of them. For example, we can slowly overcome habits and addictions.

nerdponx 11y ago

The bug here is not that humans calculate expected payoffs incorrectly, it's that they have wildly inaccurate estimates of tpayoffs and their probabilities. Subtle but important difference

Balgair 11y ago

> What experiment/result would convince you that statistics is not "the ultimate language of the brain?" Reflexes, like in your knee. Your spinal cord is very much part of your brain and the pateller tendon reflex is nearly 100% with 'healthy' people. Perhaps the statistical nature of the brain comes from measuring many people to get the right sampling power for the experiment. Genetics and the stochastic behavior of life then influence these brains to behave in statistical ways compared to each other. Twins studies should bear that out as true or false.

powera 11y ago

What the heck does "ultimate language of the brain" even mean? I literally can't even speculate what it's supposed to mean.

nl 11y ago

The theory isn't that "statistics are the ultimate language of the brain". That's just a summary designed for popular consumption. Unfortunately the links to the source article don't work, but from careful reading it appears that the real theory is that the brain tracks confidence in its measurement of data, and uses this confidence when making decisions. This is a Bayesian approach, and it has been widely speculated that the brain does this. This theory is falsifiable, because you can ask people their confidence in the original measurements, their confidence in a decision depending on that, and then use Bayes' rule to see if those confidences have propagated. Quote: In experiments with human subjects, Kepecs and colleagues therefore tried to control for different factors that can vary from person to person. The aim was to establish what evidence contributed to each decision. In this way they could compare people's reports of confidence with the optimal statistical answer. "If we can quantify the evidence that informs a person's decision, then we can ask how well a statistical algorithm performs on the same evidence" They go on to describe a video game experiment. I suspect that the description is incomplete, and there is a decision making component to the game that depends on how frequently the person thinks they are hearing the clicks. If that is the case then that answers your question about how to falsify it.

haberman 11y ago
> The theory isn't that "statistics are the ultimate language of the brain". That's not the theory of this specific paper, but the says that this researcher considers this paper a "first step" towards this more general theory. > This theory is falsifiable, because you can ask people their confidence in the original measurements, their confidence in a decision depending on that, and then use Bayes' rule to see if those confidences have propagated. If your standard is that humans will apply Bayes' theorem correctly, completely intuitively, as more evidence becomes available, I think it will be very easy to falsify that.
- nl 11y ago
  If your standard is that humans will apply Bayes' theorem correctly, completely intuitively, as more evidence becomes available, I think it will be very easy to falsify that. Yes. And there is increasing evidence that this is correct. See[1]. If you can find a copy, I think [2] will address many of your concerns about seemingly irrational behavior being supported by statistical reasoning. [1] https://en.wikipedia.org/wiki/Bayesian_approaches_to_brain_function https://en.wikipedia.org/wiki/Bayesian_approaches_to_brain_f... [2] http://www.ncbi.nlm.nih.gov/pubmed/19477333 http://www.ncbi.nlm.nih.gov/pubmed/19477333

cel1ne 11y ago

What I find very peculiar is that everybody talks about AI but no one mentions how the brain is comprised of many different areas that work differently and regulate each other. It's not all the prefrontal cortex detecting patterns. The kind of signal the amygdala fires because of a change in body temperature is different than a "pixel" changing in your visual cortex.

Houshalter 11y ago

Human brains do statistics at a low level. This is what the experiment tested. An example experiment would be if you gave someone a rewards with different probabilities after some random event like clicking, and the brain would learn to estimate the probability that a sequence of clicks would lead to a reward. On a high level this obviously breaks down. The brain doesn't have thousands of examples of slaughtering cows leading to starvation. Cognitive biases all operate at a high level of reasoning, and involve verbal arguments and stuff. But on a low level, the brain is absolutely statistically based.

webaba 11y ago
This is actually completely incorrect. Many cognitive biases occur at low levels of cognition without involving language, take professional pilots and confirmation biases despite of a ton of training data.
- Houshalter 11y ago
  I think professional pilots are still making mistakes at a higher level. By "low level" I mean things your brain does in a split second without thinking about.

darkxanthos 11y ago

A better example is the Monty Hall problem. Very few people find this intuitive.