[Link] The emotional system (aka Type 1 thinking) might excel at complex decisions
For thousands of years, human beings have looked down on their emotions. We’ve seen them as primitive passions, the unfortunate legacy of our animal past. When we do stupid things – say, eating too much cake, or sleeping with the wrong person, or taking out a subprime mortgage – we usually blame our short-sighted feelings. People commit crimes of passion. There are no crimes of rationality.
This bias against feeling has led people to assume that reason is always best. When faced with a difficult dilemma, most of us believe that it’s best to carefully assess our options and spend a few moments consciously deliberating the information. Then, we should choose the alternative that best fits our preferences. This is how we maximize utility; rationality is our Promethean gift.
[...] it’s only in the last few years that researchers have demonstrated that the emotional system (aka Type 1 thinking) might excel at complex decisions, or those involving lots of variables.
[...]
The latest demonstration of this effect comes from the lab of Michael Pham at Columbia Business School. The study involved asking undergraduates to make predictions about eight different outcomes, from the Democratic presidential primary of 2008 to the finalists of American Idol. They forecast the Dow Jones and picked the winner of the BCS championship game. They even made predictions about the weather.
Here’s the strange part: although these predictions concerned a vast range of events, the results were consistent across every trial: people who were more likely to trust their feelings were also more likely to accurately predict the outcome. [...]
Consider the results from the American Idol quiz: while high-trust-in-feelings subjects correctly predicted the winner 41 percent of the time, those who distrusted their emotions were only right 24 percent of the time. The same lesson applied to the stock market, that classic example of a random walk: those emotional souls made predictions that were 25 percent more accurate than those who aspired to Spock-like cognition.
[...] the unconscious brain is able to process vast amounts of information in parallel, thus allowing it to analyze large data sets without getting overwhelmed. (Human reason, in contrast, has a very strict bottleneck and can only process about four bits of data at any given moment.)
[...] how do we gain access to all this analysis [...]
[...] emotions come in handy. Every feeling is like a summary of data, a quick encapsulation of all the information processing that we don’t have access to. (As Pham puts it, emotions are like a “privileged window” into the subterranean mind.) When it comes to making predictions about complex events, this extra information is often essential. It represents the difference between an informed guess and random chance.
[...] for example, that you’re given lots of information about how twenty different stocks have performed over a period of time.
[...] if you’re asked which stocks trigger the best feelings [...] you will suddenly be able to identify the best stocks [...] your feelings will “reveal a remarkable degree of sensitivity” to the actual performance of all of the different securities.
But this doesn’t meant we can simply rely on every fleeting whim [...] only benefit from the emotional oracle effect when they had some knowledge of the subject. If they weren’t following [...] then their feelings weren’t helpful predictors [...]
[...] our emotions [...] are imperfect oracles [...] a strong emotion is a reminder that, even when we think we know nothing, our brain knows something.
Link: wired.com/wiredscience/2012/03/are-emotions-prophetic/
Study: business.illinois.edu/ba/seminars/2010/pham_paper2.pdf
According to Kanazawa’s Hypothesis, the comparative effectiveness of ‘type 1’ thinking should vary with how long the species has had to adapt to the type of problem being presented. So predicting herd behaviour, or how popular someone else is likely to be in a group, are problems human instincts have had a long time to adapt to. Whereas predicting the solutions to complex problems involving quantum mechanics, or just lots of capacitors and resistors in series and in parallel, are not.
What if you don’t have paper and pencil, though? A messy resistor network has to be solved as a system of linear equations, which involves a lot of pencil on paper action, especially if you want results to be accurate to n decimal figures. With a pretty huge failure rate too. And the failures here can give you results that are orders of magnitude off; very bad thing as far as survival is concerned.
At the same time, if you had a little bit of training via observing computer simulator of resistor networks, and you have the resistances presented in some graphical form (e.g. as lines of different thickness corresponding to conductivity; think painted conductive ink resistors), you may be able to learn to just imagine the current flows and see the approximate answer with not such a bad accuracy. Brain is good at training itself to match some rules. I can do mechanics pretty well by mental imagery (and electronics not too badly).
When you are trying to design a circuit, or to invent something, you need very quick and dirty evaluation method, that you can run backwards when you need a circuit for a task. (Then you need to find the values accurately using paper and pencil).
It seems that almost all of the studied phenomena had outcomes determined by other people’s emotional responses (presidential primary, idol competition, stock market performance, movie success). These would be expected to correlate with the subjects’ emotional responses, as they are likely similar.
This was noted briefly in the paper, but seemed to be largely ignored in the conclusions.
Although the weather study does support the hypothesis, it is a somewhat unfair example, as there is little to go on other than feelings without access to complicated simulation software.
I do believe the fundamental point has validity, but the paper does not seem to support it to anywhere near the level that is implied.
A concrete example of caveats being ignored, from the conclusion:
“The fact that this phenomenon was observed in eight different studies and with a variety of prediction contexts suggests that this emotional oracle effect is a reliable and generalizable phenomenon.”
Well, maybe the people who trust their feelings do so because their feelings work correctly. Who knows what the feelings system does behind the scenes.
With regards to explicitly rational predictions, unless the person in question is doing boatloads of mathematics correctly to arrive at conclusion, it is not a case of rational process.
One thing to keep in mind is that overwhelming majority of people can’t use their ‘rational reasoning’ to think their way out of the Monty Hall problem (not even when facing repeating monty hall problem, when, if they reason that switching does not matter, they could switch half of the time and get a feeling over the time that switching gives more wins—that’s how pigeons and little children solve monty hall correctly).
It is not type 1 reasoning vs type 2 reasoning here. It is type 1 reasoning versus no reasoning at all. People, overwhelmingly, can’t reason explicitly about vast majority of problems they encounter; their explicit reasoning is only usable for producing sequences of symbols for presentation. (i.e. speech)
Nothing to see here, folks, this is the usual ‘system I is cheap and reasonably accurate’ vs ‘system II is expensive and highly accurate’; from http://whywereason.wordpress.com/2012/03/05/why-the-future-of-neuroscience-will-be-emotionless/