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Simple models of people’s decision making

In this step, we want to show you how decision processes can be modelled without using utilities and weights. This is called heuristics.
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In this step, we want to show you how decision processes can be modelled without using utilities and weights. The models presented below are known in the literature as heuristics. You can think of them as algorithms, instructions, or procedures allowing us to make certain decisions. They consist of a series of steps to be executed one after the other and can easily be turned into computer programs.

One of the most prominent advocates of this approach to studying human decision making is Gerd Gigerenzer. He proposes to study what heuristics people use, when these heuristics work, and when they lead to mistakes. If you are interested in these topics, we encourage you to watch this video.

We will introduce two simple examples and invite you to try to think of your own simple decision procedures.

MEDICAL DECISION EXAMPLE

The first example is from the medical domain. Julian Marewski and Gerd Gigerenzer tell the following story:

“Accompanied by his anxious wife, a middle-aged male patient arrives at a rural Michigan hospital. He suffers from serious chest pain. The physician in charge, a compassionate-looking woman, suspects acute ischemic heart disease, but is not entirely sure. Should she assign the patient to a regular nursing bed for monitoring? If it really is acute ischemic heart disease, however, the patient needs to be rushed immediately to the coronary care unit. On the other hand, unwarrantedly sending the patient to the care unit is not only expensive, but can also decrease the quality of care for those patients who need it, while those who do not are exposed to the risk of catching a potentially harmful, hospital-transmitted infection.”

The authors continue to propose (after Green and Mare) the following diagram (called fast and frugal decision tree) to make this type of decision.

decision tree

The decision process described by this tree is as follows.

  1. If a certain anomaly in the patient’s electrocardiogram (so called ST-segment) is found, the patient is sent to the coronary care unit. No other information is considered.
  2. If there is no anomaly, the doctor considers whether the patient’s primary complaint is chest pain. If not, the patient is assigned to a regular nursing bed. Again, no additional information is considered.
  3. If the answer is yes, a third and final question is asked to classify the patient.

The full description of this example can be found in this article.

Satisfycing

The second example comes from Herbert Simon himself. It is a heuristic called satisficing (combining the words satisfy and suffice). Simon proposed this approach for problems and environments characterised by high uncertainty, little structure, and little preceding knowledge. Especially problems in which options tend to appear one after another rather than at the same time. Examples of such problems can be seeking a first job, seeking a mate, or seeking a flat to rent in a new city. What one could do in this situation is described by the following procedure:

  1. Explore the options for some time.
  2. On the basis of this experience, formulate an expectation of how good a solution you can reasonably achieve.
  3. Choose the first option that meets your expectations.

Using this procedure does not guarantee that the chosen option will be optimal. But it will be good enough and the decision will be made in a reasonable time.

For example, Diana is looking for a flat to rent. First, she is visiting apartments to rent for two weeks to see what the market is like. Based on this experience, she decides that she can afford a flat that has about 40 m2 and is about 25 minutes from her new work place. She finds a 39 m2 flat 15 minutes away and immediately signs the papers.

What if she cannot find this apartment? In this case, Simon says, she can adjust her expectations. For example, after 2 weeks of unsuccessful search she can decide she has to consider smaller flats – about 30 m2 big. In this way, she remains responsive to the conditions in which she makes her decision.

Sources:

Green, L., & Mehr, D. R. (1997). What alters physicians’ decisions to admit to the coronary care unit?. Journal of Family Practice, 45(3), 219-226. Marewski, J. N., & Gigerenzer, G. (2012). Heuristic decision making in medicine. Dialogues in clinical neuroscience, 14(1), 77.

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Decision Making in a Complex World: Using Computer Simulations to Understand Human Behaviour

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