The next turn on the right.
A new study pooh-poohs the conventional wisdom people are inherently over-optimistic or optimistically biased about the future.
The study by King's College London, UCL and Birkbeck, University of London noted that scientists for many decades have believed people have an "irrational optimism bias," that is, a tendency to underestimate their chances of negative experiences while overestimating their chances of positive events.
Optimism bias is thought to have contributed to past financial crises such as the Great Recession of 2008 and the failure of individuals to look after themselves (such as eating healthily to avoid obesity). Researchers noted the British government even considers an "optimism bias" when planning large infrastructure projects and deciding which projects should be funded.
Other new research has revealed that people fail to learn from bad news when they learn about the actual chance of experiencing a negative life event such as cancer, which is an irrational optimism bias. Such a failure to learn from bad news could result in an optimistic outlook.
This new study published today in Cognitive Psychology, however, demonstrates major flaws in research supporting the existence of this optimism bias. According to the King's College study, previous studies generated data patterns that look like people are being over-optimistic, when no such bias exists.
It first found that people's failure to learn from bad news was reversed when they were considering their chance of experiencing a positive event.
Researchers subsequently created computerized simulations designed to behave in a completely rational way when faced with the same psychological tests used in previous research, that is, learning from good vs. bad news about future events.
By definition, these simulations are not optimistic and thus will not show bias. These computer simulations produced the same pattern of data usually interpreted as showing optimism bias, due to the fact that belief scores changed more in response to good than bad news.
The study, therefore, shows how apparent optimism for negative events (and pessimism for positive events) can arise as a result of purely statistical processes. According to the authors, this supposed optimism bias is an artefact of the tests used to assess it, in conjunction with the rarity of negative events.
"Previous studies, which have used flawed methodologies to claim that people are optimistic across all situations and that this bias is 'normal,' are now in serious doubt," said Dr Adam Harris from UCL.
He said we need to look for new ways of studying optimism bias to establish whether it is a universal feature of human cognition or not.
