Part of the sequence: Rationality and Philosophy

We have already examined two sources of our intuitions: the attribute substitution heuristics and our evolved psychology. Today we look at a third source of our intuitions: unconscious learning

 

Unconscious learning

The 'learning perspective' on intuition is compatible with the heuristics and biases literature and with evolutionary psychology, but adds a deeper understanding of what is going on 'under the hood.' The learning perspective says that many intuitions rely on representations that reflect the entirety of experiences stored in long-term memory. Such intuitions merely reproduce statistical regularities in long-term memory.1

An example will help explain:

Assume you run into a man at the 20th anniversary party of your high school class graduation. You immediately sense a feeling of dislike. To avoid getting into a conversation, you signal and shout some words to a couple of old friends sitting at a distant table. While you are walking toward them, you try to remember the man’s name, which pops into your mind after some time; and suddenly, you also remember that it was he who always did nasty things to you such as taking your secret letters and showing them to the rest of the class. You applaud the product of your intuition (the immediate feeling) that has helped you to make the right decision (avoiding interaction). Recall of prior experiences was not necessary to make this decision. The decision was solely based on a feeling, which reflected prior knowledge without awareness.2

Learning perspective theorists would suggest that your feeling of dislike - your intuition that you shouldn't talk to the man - came from something like an (unconscious) regularities analysis of your experiences with that man that were stored in long-term memory, and those experiences turned out to be mostly negative. As such, your intuition can make use of rapid parallel processing to draw on the whole sum of experiences in long-term memory, rather than using a slower, sequential-processing judgment algorithm.

It is difficult to track the source of any particular intuition (though we can try3), but there is evidence to suggest that unconscious learning is a common source of our intuitions.

 

Stock tickers

In a series of experiments,4 researchers asked subjects to watch a series of advertisements. They warned subjects that a (fictional) stock ticker at the bottom of the screen would be added as a distractor (screenshot), and that they would be quizzed on the advertisements later. After being quizzed on the advertisements, subjects were surprised by a quiz on their attitudes toward the fictional stocks. Post-experiment interviews confirmed that subjects had not intended to form attitudes toward the stocks.

Subjects watched 20 to 40 advertisements while the 'distractor' stock ticker displayed 70 to 140 return values for 4 to 8 shares. As the independent variable, researchers varied the return values (and thus their sum, average, frequency, and peaks).

When given the surprise quiz on their attitudes toward the fictional stocks, researchers found a perfect rank correlation between the subjects' mean evaluation of the shares and the sums of their returns. This was the case even though subjects had no concrete memories of the share returns, and could not remember the sum or average values. Subjects reported they had relied on their 'gut reaction' or 'intuitive feeling.'

Here, it does not seem that subjects were able to arrive at such accurate intuitions by way of a specific evolved intuition or an attribute substitution heuristic. Instead, they seem to have drawn upon their unconscious learning system without knowing that they were doing so.

 

Base rate neglect

Consider this problem:

If a test to detect a disease whose prevalence is 1/1000 has a false positive rate of 5%, what is the chance that a person found to have a positive result actually has the disease, assuming you know nothing about the person's symptoms or signs?5

Among 60 Harvard medical students and staff, almost half judged that the person has the disease with .95 probability, while only 18% got the correct answer: .02. This is an example of base rate neglect. Subjects based their judgment mostly on the evidence from the test, and ignored the strong evidence from the base rate (1/1000).

Base rate sensitivity improves when such problems are framed in terms of frequencies rather than probabilities, but even then base rate neglect occurs in about half of subjects.6

Subjects further improve their statistical judgments when they are allowed learn the distribution of a variable by their own sampling, and become even more sensitive to base rates.7

In a related study,8 researchers had subjects perform several behaviors many times, and then asked them to estimate behavior frequency. Half of the subjects were asked to make spontaneous judgments, and half were asked to deliberate carefully about their judgments. In the deliberation condition, judgments were biased by the availability heuristic. Judgments from the spontaneous judgment condition were more accurate, and seemed to reflect unconscious recall of the totality of behaviors just performed, stored by unconscious learning.

 

Conclusion

These and many others studies9 suggest that sometimes our feelings and intuitive judgments arise from unconscious parallel processing of all (or many) of the experiences relevant to a given judgment stored in our long-term memory.

Later we'll examine how this understanding of intuition (along with the perspectives from attribute substitution heuristics and evolutionary psychology) gives us some clues about how much trust we should put in our intuitions under particular conditions, and how we can train our intuitions to be more accurate.10

 

Next post: When Intuitions Are Useful

Previous post: Your Evolved Intuitions

 

 

Notes

1 Betsch et al. (2004); Betsch & Haberstroh (2005); Betsch (2007); Klein (1999); Hogarth (2001, 2007); Epstein (2007). For an overview of the neuroscience of unconscious learning, see Volz & Cramon (2007). For an overview of the relation between emotion and intuition, see Zeelenberg et al. (2007).

2 Betsch (2007), p. 6.

3 Hamm (2007).

4 Betsch et al. (2001, 2003, 2007).

5 Tversky & Kahneman (1982), p. 154.

6 Gigerenzer & Hoffrage (1995).

7 Betsch et al. (1998); Fiedler et al. (2000).

8 Haberstroh et al. (2006).

9 Plessner et al. (2007); Raab & Johnson (2007); Glöckner (2007). Also see research on the 'sample size effect': Kaufmann & Betsch (2009).

10 Hogarth (2001, 2007); Erev et al. (2007).

 

References

Betsch (2007). The nature of intuition and its neglect in research on judgment and decision making. In Plessner, Betsch, & Betsch (eds.), Intuition in Judgment and Decision Making (pp. 3-22). Psychology Press.

Betsch, Plessner, Schwieren, & Gütig (2001). I like it but I don’t know why: A value-account approach to implicit attitude formation. Personality and Social Psychology Bulletin, 27: 242–253.

Betsch, Hoffmann, Hoffrage, & Plessner (2003). Intuition beyond recognition: When less familiar events are liked more. Experimental Psychology, 50: 49–54.

Betsch, Plessner, & Schallies (2004). The value-account model of attitude formation. In Haddock & Miao (eds.), Contemporary perspectives on the psychology of attitudes (pp. 251-274). Psychology Press.

Betsch & Haberstroh, eds. (2005). The routines of decision making. Psychology Press.

Betsch, Kaufmann, Lindow, Plessner, & Hoffmann (2006). Different principles of information integration in implicit and explicit attitude formation. European Journal of Social Psychology, 36: 887–905.

Betsch, Biel, Eddelbüttel, & Mock (1998). Natural sampling and base-rate neglect. European Journal of Social Psychology, 28: 269–273.

Epstein (2007). Intuition from the perspective of cognitive-experiential self-theory. In Plessner, Betsch, & Betsch (eds.), Intuition in Judgment and Decision Making (pp. 23-37). Psychology Press.

Erav, Shimonowitch, Schurr, & Hertwig (2007). Base rates: How to make the intuitive mind appreciate or neglect them. In Plessner, Betsch, & Betsch (eds.), Intuition in Judgment and Decision Making (pp. 135-148). Psychology Press.

Fiedler, Brinkmann, Betsch, & Wild (2000). A sampling approach to biases in conditional probability judgments: Beyond base-rate neglect and statistical format. Journal of Experimental Psychology, General, 129: 399–418.

Gigerenzer & Hoffrage (1995). How to improve Bayesian reasoning without instruction: Frequency formats. Psychological Review, 102: 684–704.

Glöckner (2007). Does intuition beat fast and frugal heuristics? A systematic empirical analysis. In Plessner, Betsch, & Betsch (eds.), Intuition in Judgment and Decision Making (pp. 309-326). Psychology Press.

Haberstroh, Betsch, & Aarts (2006). When guessing is better than thinking: Multiple bases for frequency judgments. Unpublished manuscript.

Hamm (2007). Cue by hypothesis interactions in descriptive modeling of unconscious use of multiple intuitive judgment strategies. In Plessner, Betsch, & Betsch (eds.), Intuition in Judgment and Decision Making (pp. 55-70). Psychology Press.

Hogarth (2001). Educating Intuition. University of Chicago Press.

Hogarth (2007). On the learning of intuition. In Plessner, Betsch, & Betsch (eds.), Intuition in Judgment and Decision Making (pp. 91-106). Psychology Press.

Klein (1999). Sources of power. How people make decisions. MIT press.

Kaufmann & Betsch (2009). Origins of the sample-size effect in explicit evaluative judgments. Experimental Psychology, 56: 344-353.

Plessner, Betsch, Schallies, & Schwieren (2007). Automatic online formation of implicit attitudes toward politicians as a basis for intuitive voting behavior. In Plessner, Betsch, & Betsch (eds.), Intuition in Judgment and Decision Making (pp. 107-117). Psychology Press.

Raab & Johnson (2007). Implicit learning as a means to intuitive decision making in sports. In Plessner, Betsch, & Betsch (eds.), Intuition in Judgment and Decision Making (pp. 119-133). Psychology Press.

Tversky & Kahneman (1982). Judgment under uncertainty: Heuristics and biases. Cambridge University Press.

Volz & Cramon (2007). Can neuroscience tell a story about intuition? In Plessner, Betsch, & Betsch (eds.), Intuition in Judgment and Decision Making (pp. 71-87). Psychology Press.

Zeelenberg, Nelissen, & Pieters (2007). Emotion, motivation, and decision making: a feeling-is-for-doing approach. In Plessner, Betsch, & Betsch (eds.), Intuition in Judgment and Decision Making (pp. 173-189). Psychology Press.

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10 comments, sorted by Click to highlight new comments since:

Lukeprog, I always enjoy your articles. You are very diligent in keeping your references, which is much appreciated.

While base rate neglect is a really interesting problem, I've always been a bit skeptical of it being at all relevant that doctors get it wrong so often. In real medical contexts, not everyone is getting tested for every disease; one is normally going to get tested if one has symptoms or have some risk factor. So in most circumstances, the actual chance that someone who is tested will have a false positive is lower than one would naively expect.

There are on the other hand other circumstances where this precise problem seems to show up (for example, when some people tried to push for mandatory premarital HIV testing).

[-]Fly80

This occurs all the time.

http://www.psychologicalscience.org/journals/pspi/pspi_8_2_article.pdf

In 2007, 160 gynecologists were provided with the relevant health statistics needed for calculating the chances that a woman with a positive mammogram test actually has cancer. The correct answer was about 10%. The majority of them grossly overestimated the probability of cancer, answering ‘‘90%’’ or ‘‘81%.’’

When most doctors are asked to interpret probabilistic lab results they suck. The doctors just don't think that way. Instead they have learned what to say so that the patient will immediately take the next recommended step, i.e., get a biopsy. From the doctor's perspective missing a cancer is a much worse outcome than needlessly worrying a patient. Their cached answer is "you have a high probability of cancer so a biopsy is needed immediately" which led to their guessing answers in the 80-90% range.

Ooh. I register enthusiastic approval of this topic.

Curious: Which topic? Intuition in general? Intuition for use in philosophy? Unconscious learning?

Intuition in general, especially as treated with something other than derision.

[-][anonymous]50

Yes! Combating cognitive biases by thinking really carefully is all very well, and totally appropriate if you're trying to design a machine that can take over the world, but in everyday life we just can't do everything in manual mode. I've been wondering lately if I wouldn't benefit more from reading a blog called More Right, if such a thing existed.

I've had similar thoughts for quite a while and I realized that "more right" had all kinds of emotional connotations that I wasn't sure were a good idea. I was thinking that something like More Helpful would offer a better framing. Instead of cultivating rationality, it would be cultivating something like "pro-social efficacy".

I like it. I would be in favor of changing the name of the community to Less Wrong and More Helpful.

There have been other online communities with very high standards of rationality, but none that combine it with as much actual desire to help people.

If the false positive rate is 5 percent, 50 out of every one thousand will test false positive. An additional person will test true positive. Therefore 51 will test positive. The probability a positive tester being positive is 1 out of 51. Multiply to 2 out of 102, and it becomes clear .02 overestimates the true value of those who would test positive as 2 hundredths is greater than 2 hundred-and-secondths.