In his book Incognito: The Secret Lives of the Brain, David Eagleman explained what is known as the illusion-of-truth effect: “you are more likely to believe that a statement is true if you have heard it before — whether or not it is actually true.”
“In one study, subjects rated the validity of plausible sentences every two weeks. Without letting on, the experimenters snuck in some repeat sentences (both true and false ones) across the testing sessions. And they found a clear result: if subjects had heard a sentence in previous weeks, they were more likely to now rate it as true, even if they swore they had never heard it before.”
“This is the case even when the experimenter tells the subjects that the sentences they are about to hear are false: despite this, mere exposure to an idea is enough to boost its believability upon later contact. The illusion-of-truth effect highlights the potential danger for people who are repeatedly exposed to the same religious edicts or political slogans.”
I think that the illusion-of-truth effect also helps explain why although most organizations acknowledge the importance of data quality, they don’t believe that data quality issues occur very often because the data made available to end users in dashboards and reports often passes through many processes that cleanse or otherwise sanitize the data before it reaches them.
Therefore, even when an organization regularly evaluates the validity of its data, they are likely to rate themselves as having excellent data quality because they are repeatedly exposed to what appears to be high-quality data, but which might be the result of what could be called the illusion-of-quality effect caused by the excessive filtering and data cleansing performed by up-stream processing.
Is it possible some of the data your organization is relying on to support its daily business activities could be affected by the illusion-of-quality effect?
Are you turning Ugly Data into Cute Information?