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Heuristics and Biases 2C- Alternative Perspectives on Heuristics


28. The Use of Statistical Heuristics in Everyday Inductive Reasoning

Contrary to the Panglossians, human beings do fail to reason statistically when it is appropriate. They neglect regression to the mean, small sample sizes, and the role of randomness. Still, there are some situations where it is intuitive to think statistically, as when one is surprised that a woman has 9 boys in a row, but not 3 (rule of large numbers). People are also capable of improving their statistical reasoning, and those who have training in statistics tend to perform better in tasks that require good statistical reasoning, suggesting that it is not just tricky questions that are tripping up a few people, but a lack of statistical understanding.

In this chapter, we first summarize the work establishing failures to reason statistically. We then review anecdotal and experimental evidence indicating that people do sometimes reason statistically. Next we present original experimental work indicating some of the factors that influence statistical reasoning. Then we summarize research suggesting that people’s ability to reason statistically about everyday life problems is affected by training in formal statistics. Finally, we speculate on the normative implications of people’s ability and trainability for statistical reasoning (11590).

29. Feelings as Information: Moods Influence Judgements and Processing Strategies

Emotions have a varied affect on judgment and reasoning. Being sad is leads to more analytic thinking than being happy. Different emotions also have different effects on judgments and preferences. Anger decreases analytic thinking. Sad people are more likely to prefer high risk rewards, and anxious people tend towards lower risk.

Emotions bias our evaluations of things as well. Being sad leads to lower evaluations of objects, situations or people. When a reason for the emotion is provided, the effect disappears, suggesting that the emotion is no longer being used as data.

One’s mood affects how persuasive arguments are. Happy people don’t elaborate on arguments as much as sad people, so they are less critical. Other weird but not emotional effects like pushing or pulling affects whether people used a heuristic or analytic processing style.

In general, individuals in a sad mood are more likely to use a systematic, data-driven strategy of information processing, with considerable attention to detail. In contrast, individuals in a happy mood are more likely to rely on preexisting general knowledge structures, using a top-down, heuristic strategy of information processing, with less attention to detail (12281).
Importantly, mood effects on processing style are eliminated when the informational value of the mood is undermined (12292).
being in a good mood has been found to increase stereotyping consistently (e.g., Bodenhausen, Kramer, & Süsser, 1994), unless the target person is clearly inconsistent with the stereotype, thus undermining the applicability of the general knowledge structure (e.g. Bless, Schwarz, & Wieland, 1996). In contrast, being in a sad mood reliably decreases stereotyping and increases the use of individuating information (12301).
sad individuals are strongly influenced by compelling arguments and not influenced by weak arguments, whereas happy individuals are moderately, but equally, influenced by both (12316).

30. Automated Choice Heuristics

The “choosing by liking” heuristic involves deciding between alternatives by using one’s subjective affect. This can be an effective strategy when there is a reality based link between the affect and the judgment (person’s personality is nice, therefore you befriend him). It is not as effective when there is a mismatch (haven’t eaten breakfast, therefore you don’t like a person).

The heuristic approach may be superior to a more involved analytic approach to preferences, since the analytic approach may lead to overvaluing less attributes less important to overall preferences. This approach does have some shortcomings (see quoted text below).

Second is the “choice by default” heuristic, e.g. going with the status quo or with some conspicuous focus point (split the difference) without evaluation.

Although affective impressions may be often an accurate proxy for the overall quality of an option, and superior to clumsy attempts at multiattribute utility analysis, several properties of affect render it an imperfect and, sometimes, markedly deficient basis for choice: (1) it is insufficiently sensitive to quantitative detail; (2) it is unduly influenced by transient contextual cues; (3) it is excessively affected by familiarity (12495).
some choice procedures may bypass the evaluation stage altogether, deferring instead to a default option. Defaults may be established via historical precedent, perceptual salience, conspicuousness, or some other feature that qualitatively distinguishes one option from the rest (12587).

31. How Good are Fast and Frugal Heuristics?

In a surprising variety of situations, simple decision making heuristics (take the best) perform about as well, or even better than more complex (multiple regression analysis) methods of prediction.

The major results summarized in this chapter are as follows: First, across 20 real-world environments, the fast and frugal Take the Best outperformed multiple regression in situations with learning (test set ≠ training set), and even the simpler Minimalist came within 2 percentage points. Second, we specified which characteristics of information in real-world environments enable Take the Best to match or outperform linear models. Third, we showed that sophisticated Bayesian networks were only slightly more accurate than Take the Best (13120).

32. Intuitive Politicians, Theologians, and Prosecutors: Exploring the Empirical Implications of Deviant Functionalist Metaphors

Many of the “biases” discussed in the book may seem less irrational, or not irrational at all when looked at from certain narrative perspectives. Pretty interesting, but of special note was some research on where self-accountability can decrease, or even in some cases increase certain biases.

The SCM predicts that decision makers will resort to one of the trio of decision-evasion tactics – buck-passing, procrastination, and obfuscation – when they are accountable to audiences that not only hold conflicting views but also hold each other in contempt (13268).

Within the intuitive-politician framework, a key function of private thought is preparation for public performances. Thought frequently takes the form of internalized dialogs in which people gauge the relative justifiability of alternative courses of action by imagining conversations with others in which accounts are exchanged, debated, revised, and evaluated (13306).

Accountability should be an effective debiasing manipulation to the degree it induces research participants to (1) consider a wider range of relevant cues or arguments; (2) pay more attention to the cues that they do use; (3) anticipate plausible counterarguments, evaluate their strengths relatively impartially, and factor those that pass some threshold of plausibility into their overall assessment. In cases in which accountability amplifies bias, scholars have made a good prima facie case that the biases result from trying too hard to integrate irrelevant considerations into one’s mental representation of the problem (13390).

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