The Representativeness Heuristic

The Representativeness Heuristic

The Representativeness Heuristic is defined by Tversky and Kahneman as “the degree to which an event (i) is similar to essential characteristics to its parent population, and (ii) reflects the salient features of the process by which it is generated”. Simply put by Kahneman it is the shortcut of focusing on the similarities of an event/item and its stereotype, often at the cost of other useful information. The Representativeness heuristic (mental shortcut) comes into play with probability questions such as; What is the probability that object A belongs to class B? What is the probability that event A originates from process B? What is the probability that process B will generate event A?

This heuristic was confirmed with a famous experiment from Tversky and Kahneman named Tom W’s Specialty. The Tow W experiment started with a simple puzzle;

Tow W is a graduate student at the main university in your state. Please rank the following nine fields of graduate specialisation in order of the likelihood that Tow W is now a student in each of these fields. Use 1 for the most likely, 9 for the least likely:

Business administration

Computer science

Engineering

Humanities and education

Law

Medicine

Library science

Physical and life sciences

Social science and social work

 

The puzzle is designed so that to answer accurately we need to think about the likelihood that Tom W is a graduate in one of the fields. With no other information, we need to think about what the most popular field of study with the highest enrolment and graduates is. In this case, we would most likely guess humanities and education. Computer Science, Library science, medicine and law might be quite low. This was the base rate condition of Tom W.

The second task gave a vignette on Tom W;

Tom W is of high intelligence, although lacking in true creativity. He has a need for order and clarity, and for neat and tidy systems in which every detail finds its appropriate place. His writing is rather dull and mechanical, occasionally enlivened by somewhat corny puns and flashes of imagination of the sci-fi type. He has a strong drive for competence. He seems to have little feel and sympathy for other people, and does not enjoy interacting with others, he nonetheless has a deep moral sense.

Now please rank the nine fields of specialisation listed above by how similar the description of Tom W is to the typical graduate student in each of the fields.

Now this task is set up, so you evaluate the similarities of Tom’s characteristics to the stereotypes of students studying in different fields. This is Representativeness as we see Tom’s characteristics represent a stereotype, in this case, most likely computer sciences or engineering. This was the similar to the stereotype condition (Representativeness).   

The final task was given to graduate psychology students. They were provided with the list of occupations and the description of Tom W and they were then asked;

Rank the fields of specialisation in order of the likelihood that Tom W is now a graduate student in each of these fields

You can see that this question is practically the same as the first task and therefore to make a logical prediction it would be prudent to rely again on the base rates of each specialisation to inform our prediction of the probability of Tom being a graduate. However, of the 119 graduate students that completed the task, their rankings of the nine speciality fields by probability, did not differ to similarity to the stereotype. Tversky and Kahneman had shown the Representativeness heuristic at work.   

The Representativeness heuristic is helpful in many ways as it produces a quick intuition that is normally better that a blind guess. However, it also is open to error especially during emotionally charged topics where we can then disregard base rate information, focus on a specific individually and event and make a quick intuition that will be inaccurate.  

Reference

Kahneman, D. (2015). Thinking, fast and slow. New York: Farrar, Straus and Giroux