Support-Sensitivity in Probability Judgments
This study examined how judged probability of guilt relates to assessed suspiciousness in criminal cases, finding that a suspect twice as suspicious is judged less than twice as likely to be guilty, indicating a sublinear mapping from support to probability.
THE IDEA
Study 4: Crime Stories
This study was designed to investigate the relation between judged probability and assessed support in a very different context and to explore the enhancement effect. To this end, we adapted a task introduced by Teigen (1983) and Robinson and Hastie (1985) and presented subjects with two criminal cases. The first was an embezzlement at a computer-parts manufacturing company involving four suspects (a manager, a buyer, an accountant, and a seller). The second case was a murder that also involved four suspects (an activist, an artist, a scientist, and a writer). In both cases, subjects were informed that exactly one suspect was guilty. In the low-information condition, the four suspects in each case were introduced with a short description of their role and possible motive. In the high-information condition, the motive of each suspect was strengthened. In a manner resembling the typical mystery novel, we constructed each case so that all the suspects seemed generally more suspicious as more evidence was revealed.
Subjects evaluated the suspects after reading the low-information material and again after reading the high-information material. Some subjects (N = 60) judged the probability that a given suspect was guilty. Each of these subjects made two elementary judgments (that a particular suspect was guilty) and three binary judgments (that Suspect A rather than Suspect B was guilty) in each case. Other subjects (N = 55) rated the suspiciousness of a given suspect, which we took as a direct assessment of support. These subjects rated two suspects per case by providing a number between 0 (indicating that the suspect was “not at all suspicious”) and 100 (indicating that the suspect was “maximally suspicious”) in proportion to the suspiciousness of the suspect.
As in the previous study, we assumed binary complementarity and estimated k by a logarithmic regression of R(A, B) against the suspiciousness ratio. For these data, k was estimated to be .84, and R2 was .65. Rated suspiciousness, therefore, provides a reasonable predictor of the judged probability of guilt. However, the relation between judged probability and assessed support was stronger in the basketball study than in the crime study. Furthermore, the estimate of k was much smaller in the latter than in the former. In the basketball study, a team that was rated twice as strong as another was judged more than twice as likely to win; in the crime stories, however, a character who was twice as suspicious as another was judged less than twice as likely to be guilty. This difference may be due to the fact that the judgments of team strength were based on more solid data than the ratings of suspiciousness.
When to use it
Legal decision-making: Jurors evaluating suspects based on cumulative evidence.
Risk assessment: Estimating the likelihood of different risks when evidence is ambiguous or incomplete.
Consumer choice: Judging product quality based on information that may make all options seem better/worse.
Medical diagnosis: Assessing likelihood of diseases based on symptoms that may be common to multiple conditions.
FROM THEORY TO EVERYDAY LIFE
In practice
Embezzlement Case
In the embezzlement case, four suspects (manager, buyer, accountant, seller) were presented with low-information descriptions of role and motive. After high-information strengthened motives, subjects judged probability or rated suspiciousness. The ratio of suspiciousness predicted probability but with a sublinear mapping (k=0.84).
Murder Case
The murder case involved four suspects: an activist, artist, scientist and writer. Participants judged guilt probabilities or rated suspiciousness before and after additional motive information. The fitted relationship concerned relative suspiciousness and relative judged probability; it does not mean that every suspect’s probability rose.
A MOMENT TO REFLECT
Put it to work.
How might the nature of evidence (solid data vs. subjective assessments) affect the relationship between judged probability and support?
In what real-world situations might we over- or under-estimate probability based on intuition about suspiciousness?
If exactly one suspect is guilty, how should the individual guilt probabilities change when new information makes every suspect seem more suspicious?
Often confused with
References
- Teigen, 1983 — Teigen (1983)
- Robinson and Hastie, 1985 — Robinson and Hastie (1985)
CONTINUE THE CONVERSATION
Source texts
- Heuristics and Biases The Psychology of Intuitive Judgment (Thomas Gilovich, Dale Griffin, Daniel Kahneman)