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Heuristics and Biases 1A- Representativeness and Availability

01/08/2014

Introduction

The intro looks at the how the heuristics and biases research tradition fits into related science as a whole, and answers some common scientific objections, and answers them all in turn in ways that makes it unsurprising that the research tradition has become so fruitful and influential. The answers seem to mimic Stanovich’s in his Chapter on the “Great Rationality Debate.”

The core idea of the heuristics and biases program is that judgment under uncertainty is often based on a limited number of simplifying heuristics rather than more formal and extensive algorithmic processing (306).

The “We Cannot Be That Dumb” Critique. The most common critique of the research on heuristics and biases is that it offers an overly pessimistic assessment of the average person’s ability to make sound and effective judgments (496).

The “It’s All Parlor Games” Critique. Another common critique of the heuristics and biases tradition has been to dismiss the reported findings as mere laboratory curiosities – as demonstrations that people cannot readily solve tricky “word problems” (574).

The “It’s Not an Error” Critique. Another common accusation against the heuristics and biases tradition is that researchers hold experimental participants to an inappropriately high or even misguided standard of rationality (616)

The “Frequencies, Good; Probabilities, Bad” Critique. Given the controversy surrounding the normative status of frequencies and subjective probabilities, it is not surprising that those who favor an evolutionary defense of rationality (“ecological rationality”) should throw in their lot with the frequentists (650).

1. Emotional vs. Intuitive Reasoning: The Conjunction Fallacy in Probability Judgment

An overview of the conjunction fallacy (A & B is rated as more likely than A, when this is logically impossible). Many, many studies are cited that work to defend the existence of the conjunction fallacy against some of the sorts of objections listed in the intro. Almost every objection is countered by a study that investigates whether the objection is valid, or whether the conjunction fallacy remains. For example, some claim that the questions are ambiguous in ways that allow for reasonably different answers that aren’t fallacious. Yet further tests show that the interpretation by the participants does in fact mirror how the tasks are meant to be interpreted, and that even the participants realize their error.

In contrast to formal theories of beliefs, intuitive judgments of probability are generally not extensional. People do not normally analyze daily events into exhaustive lists of possibilities or evaluate compound probabilities by aggregating elementary ones. Instead, they commonly use a limited number of heuristics, such as representativeness and availability (778)

Modern research on categorization of objects and events (Mervis & Rosch, 1981; Rosch, 1978; Smith & Medin, 1981) has shown that information is commonly stored and processed in relation to mental models, such as prototypes and schemata. It is therefore natural and economical for the probability of an event to be evaluated by the degree to which that event is representative of an appropriate mental model (828).

Argument 1. Linda is more likely to be a bank teller than she is to be a feminist bank teller, because every feminist bank teller is a bank teller, but some women bank tellers are not feminists, and Linda could be one of them. Argument 2. Linda is more likely to be a feminist bank teller than she is likely to be a bank teller, because she resembles an active feminist more than she resembles a bank teller. The majority of subjects (65%, n = 58) chose the invalid resemblance argument (Argument 2) over the valid extensional argument (Argument 1). Thus, a deliberate attempt to induce a reflective attitude did not eliminate the appeal of the representativeness heuristic (947).

Note: An objectively bad argument that is rated as more convincing.

We found, however, that sophisticated and naive respondents answered the Linda problem similarly in indirect tests and only parted company in the most transparent versions of the problem. These observations suggest that statistical sophistication did not alter intuitions of representativeness, although it enabled the respondents to recognize in direct tests the decisive force of the extension rule (1358).

2. Representativeness Revisited: Attribute Substitution in Intuitive Judgment

Probability judgments are intuitively made by matching how closely the item in question represents or resembles a stereotypical prototype of a class of items. For example, how likely Bob is to be a librarian is judged by how similar Bob is to a stereotypical librarian, neglecting base rates. Similarity is substituted for likelihood.

Similarly, how much one is willing to pay to alleviate an environmental problem is judged by imagining a single instance of that problem, and looking at one’s emotional reaction, to the exclusion of the extent of the problem. For example how much one would pay to prevent all the forest fires in Canada is done by considering one’s reaction to a single forest fire in Canada. People make similar “willingness to pay” judgments whether it’s all forest fires in Canada, or ten forest fires in Canada.

The first section introduces a distinction between two families of cognitive operations, called System 1 and System 2. The second section presents an attribute-substitution model of heuristic judgment, which elaborates and extends earlier treatments of the topic (Kahneman & Tversky, 1982; Tversky & Kahneman, 1974, 1983). The third section introduces a research design for studying attribute substitution. The fourth section discusses the controversy over the representativeness heuristic. The last section situates representativeness within a broad family of prototype heuristics, in which properties of a prototypical exemplar dominate global judgments concerning an entire set (1504).

3. How Alike is It? versus How Likely Is it? A Disjunction Fallacy in Probability Judgments

While the conjunction fallacy looks at examples of people judging P(A&B) > P(A), the disjunction fallacy looks at people judging P(A) > P(A or B). In other words, people judge something to be more likely to be a particular instance of a class, than to be any member of the class itself. Like saying that an animal described as furry with claws and a mane as more likely to be a lion than a mammal. This is a fallacy because mammals include lions, as well as many other animals.

This fallacy occurs when the described item is seem as more representative of the instance than the family. A person who loves the outdoors and mountains may be judged as more likely to be studying geosciences than the overarching natural sciences, because she is “more like” a geoscience major.

My question for this and the conjunction fallacy is when exactly does this error occur in the real world? Are there gambling tasks or business decisions that are susceptible to this?

4.  Imagining Can Heighten or Lower the Perceived Likelihood of Contracting a Disease: The Mediating Effect of Ease of Imagery

If an event is easy to imagine, imagining it makes it seem more likely. If it is hard to imagine, imagining it makes it seem less likely. When other effects are put forward to explain the difficulty or ease of imagining, then the ease of imagining loses it’s importance, and the content of what is imagined becomes important for people to judge likelihood.

This is important because it adds nuance to storytelling or suggestions to imagine. Such attempts can backfire and make arguments less compelling if what is to be imagined is difficult to imagine. It also underscores the importance of useful imagery, Cosmos style, to help people understand and believe complex topics.

5. The Availability Heuristic Revisited: Ease of Recall and Content of Recall as Distinct Sources of Information

According to Tversky and Kahneman’s (1973, p. 208) availability heuristic, individuals estimate the frequency of an event or the likelihood of its occurrence “by the ease with which instances or associations come to mind.” Although this heuristic has stimulated an enormous amount of research (see Sherman & Corty, 1984; Taylor, 1982, for reviews), the classic studies on the issue are ambiguous with regard to the underlying process (2591).

Are participants’ judgments indeed based on the phenomenal experience of ease or difficulty of recall, as Tversky and Kahneman’s description of the availability heuristic suggests, or are their judgments based on the content of recall, with famous names being overrepresented in the recalled sample? (2613).

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