Let’s start with a quiz:
Amy is a 29 year old woman, married, with no children. She has high ability and high motivation, and promises to be quite successful in her field. She is well liked by his colleagues. Amy comes from a group of 100 individuals, among which there are 30 lawyers and 70 engineers. Is Amy more likely to be a lawyer or an engineer?
Hard to say, right? Both descriptions fit either profession quite well.
Let’s try once again and take James, who also comes from the same group. He is outgoing, interested in politics, and displays particular skill in argument. Is James more likely to be a lawyer or an engineer? This time it’s easier to decide because those seem like skills we would associate with a lawyer, aren’t they?
If you said yes to both examples, I apologize for having led you astray. In both cases, the individuals are likely to be engineers.
Wait, what?
The answer is obvious if you take the probability of an individual belonging to either group: 70% engineer and 30% lawyer. The questions even hinted to the answer, as “likelihood” implies probability. Yet, the descriptions seem to have lead us to completely ignore probabilities.
This happens because the world around us is too vast and unpredictable for us to fully comprehend its complexity. To try and make sense of our environment, our minds often rely on shortcuts and heuristics to make sense of complex information.
One such mental shortcut is representativeness, where we judge the likelihood of an event based on how well it aligns with our preconceived notions and stereotypes. In a groundbreaking 1974 study, psychologists Daniel Kahneman and Amos Tversky revealed how easily we can be fooled by representativeness and overlook the crucial role of probability.
The duo found that this bias arises because we are drawn to compelling narratives that offer a coherent and consistent picture of the world. By prioritizing descriptive narratives over statistical reasoning, we fall into the trap of overlooking the complexities of probability.
Why you should care
If preventing yourself from being fooled isn’t enough of a reason to make efforts to overcome this bias, you should know that representativeness can have far-reaching implications in various aspects of our lives.
- In financial decision-making, for instance, investors might make poor choices by favoring certain stocks or investment opportunities based on representativeness rather than considering objective data and probability.
- In legal proceedings, jurors might be swayed by the representation of a defendant that aligns with a certain stereotype, leading to incorrect judgments.
- In hiring processes, employers might favor candidates who fit their preconceived notions of what a successful employee should be like, rather than objectively evaluating qualifications and skills
How to overcome the bias
Recognizing and mitigating the influence of representativeness bias is essential for making sound decisions. By understanding the role of probability and incorporating statistical reasoning, we can improve our judgment and decision-making abilities.
In other words, it’s all about the data! By knowing how to incorporate data into our decision-making process, we can avoid bad decisions and make better ones. That’s the power of? Data. Decisions. Repeat-ing!