In today's article, we will look at a key concept behind ReDem's technology. This is the psychological effect known as the "false consensus effect" or "consensus bias".
Due to the designation, one might think that this is a negative effect. However, it is important to understand that this is not necessarily negative and can even be used in a very supportive way in the case of ReDem. This effect merely describes a natural psychological tendency of people.
The False Consensus Effect describes the tendency for people to overestimate the frequency of their own opinions, beliefs, characteristics, or even actions in the population.
People use all kinds of information that is available to them. Information can be opinions as well as experiences or knowledge. People draw on different types of information, including opinions, experiences, and knowledge. Because everyone lives in their own "bubble,” we tend to overestimate the frequency of our beliefs and information. This phenomenon is called the False Consensus Effect and happens unconsciously, which is why it is difficult to simply ignore it.
Even when people believe that their opinion differs from the majority opinion, the False Consensus Effect manifests itself. This means that people tend to always value the dissemination of their own views more highly than those of people with opposing opinions or attitudes.
Why does the False Consensus Effect occur?
Researchers have found that the False Consensus Effect occurs mainly for three reasons.
- Our family, friends and colleagues are often similar to ourselves and share the same or similar views. We like to surround ourselves with people who are like us.
- To increase our own self-esteem, we try to imagine that other people are like us. It simply feels better not to be alone with a certain opinion or attitude.
- Since we are very familiar with our own attitudes and beliefs and these are at the forefront of our thinking, we are particularly struck when other people exhibit similar views or behaviors to our own. An example of this is when we get a new car and suddenly notice an increase in cars of the same type on the roads.
Scientific background
The effect was discovered as early as 1977 by researchers Lee Ross, David Greene and Pamela House at Stanford University and called the False Consensus Effect.
In one experiment, study participants were informed about a conflict situation and given two different response options. Participants were asked to select their preferred option and also to estimate which choice the other persons would make. In addition, they were asked to describe the character traits of those individuals who would choose one option or the other.
The researchers observed that participants, regardless of their own choice, tended to believe that the majority of individuals would also prefer this option. In addition, the researchers found that participants portrayed the characteristics of those individuals who chose a different option as extreme.
In the meantime, there are countless other scientific studies and findings on this topic that clearly confirm these results.
An Example
Suppose we survey people about their opinion of electric cars like Tesla and Co. We contrast two groups of equal size and ask both groups the following question:
Do you support electric vehicles or are you against them? (Yes / No)
The first group consists of supporters of electric vehicles, the second group of opponents of electric vehicles. If both groups now have to give an estimate of what percentage of the population shares their opinion, what would this estimate look like?
- Electric Vehicle Supporters:
The combined estimate of supporters for "yes" will be higher than that of opponents. - Opponents of electric vehicles:
Conversely, the combined estimate of opponents for "No" will be higher than that of supporters.
Each of the groups will tend to overestimate the frequency of their own opinions.
Why is False Consensus Effect helpful for ReDem?
The false consensus effect is particularly useful for ReDem because we use it to assess the response quality of survey participants. In doing so, we ask participants a projection question about the response behavior of other participants in addition to a single-choice question.
Our technology then examines whether participants' responses and associated projections are consistent with the assumptions of the false consensus effect.
Thus, if participants give superficial answers or are insincere due to social desirability, their answers are very unlikely to match the projections. The False Consensus Effect thus helps us to distinguish "high quality" from "low quality" respondents.
