Why do we think we’re destined to fail?
Pessimism bias
, explained.What is the Pessimism bias?
The pessimism bias refers to the tendency to overestimate the likelihood of negative events while underestimating the likelihood of positive events. This attitude of expecting the worst is a prominent cognitive feature of depression and can have considerable ramifications on both a personal and societal level.
Where it occurs
Did you ever have a studious friend in school who thought they were going to fail every exam? What about someone who thinks everyone dislikes them? We often label this a glass-half-empty perspective, as garden variety pessimism, rather than a nuanced psychological phenomenon. Fortunately, there is a breadth of research that can help shine a light on such dark perceptions.
The realm of pessimism can play out in our beliefs about ourselves and of society, with the inclinations behind these beliefs sometimes leading us astray. The brain does not always have access to accurate predictions of the future, or the ability to mentally calculate them, so we often rely on how we feel about a future event. If we’re depressed, fearful, or hopeless about a prospect, these feelings may seep into our estimations and expectations.
Individual effects
The consequences of pessimism bias can considerably alter one’s behavior. Many decisions that include a component of potential downside may be nullified due to an overestimation of such a downside. For example, someone might choose not to take on a new challenge because they overperceive the likelihood that they’ll fail.
A clear representation of the overestimation of negative events comes from a French study that asked participants to imagine a coin were to be flipped ten times, with a payout of $10 if the coin landed on heads. People were then asked how often they expected to win. Despite the sample size of the study being over 1,500 individuals, the average answer was 3.9, well below the expected average of 5. The authors suggested a pessimistic bias resulted in people overestimating the likelihood of losing a toss, while simultaneously underestimating the likelihood of winning one.1
Systemic effects
Although the pessimism bias can occur in regard to an individual’s beliefs about themselves and personal events, as the coin toss example illustrates, the general empirical finding is that people are optimistic about themselves, but pessimistic about society.2
This societal pessimism can have significant political consequences, as it can affect prospective public opinion towards certain events. For example, an overestimation in expectations towards negative events such as violence and terrorism can drive a population into voting for a certain candidate or holding misguided beliefs. The popular psychologist Steven Pinker makes this argument in his book The Better Angels of Our Nature, citing how people’s beliefs in modernity bringing forth terrible violence don’t exactly align with the data. Some comparisons show the past as 40 times more violent than the present according to certain empirical metrics of suffering.3
Regardless of how much these pessimistic beliefs are due to a media that disproportionately covers negative events, or to the human tendency to have a rose-tinted view of the past, widespread pessimism can have a wide-ranging impact on systems driven by public opinion.
Why it happens
It can be tricky to discuss the pessimism bias without also considering the optimism bias. Both biases can indeed coexist in a population as cognitive phenomena since not every bias applies to every person. Moreover, both biases can also coexist for the same person, depending on the context of the situation (more on that later). In general, however, most people skew towards expressing an optimism bias. For example, the majority of people expect to live longer and be healthier than others.4
The neural mechanisms that are suggested to be involved in mediating optimism include a functional connectivity between the rostral anterior cingulate cortex and the amygdala. This network is also related to pessimism; specifically, irregularities in this pathway are linked to depression,5 which in turn often feeds into pessimism.6 This divergence from the typical circuitry involved in optimism can lead to negative expectations, such as living shorter lives and being less healthy than others.
Aside from neuroscientific evidence, cultural differences in optimism and pessimism biases have been recorded. One study found that Westerners (European American respondents) were more likely to expect positive events to happen to them compared to Easterners (Japanese respondents), with Easterners being more likely to expect negative events to happen to them.7 The authors of the study suggest the results may be due to the idea that Western individualism promotes self-enhancement while Eastern collectivism promotes self-criticism, with these cultural connotations manifesting in our cognition.
The biological aspect of aberrant neural circuitry in the mechanisms of optimism, coupled with a cultural view on the optimism-pessimism dichotomy, bring nuance to the subject and pose great challenges in untangling a causal relationship that can explain the pessimism bias. Does pessimism cause depression, or does depression cause pessimism? How does one’s culture factor in? One study looking at 852 twin pairs found distinct genetic influences on optimism and pessimism in addition to a family-level environment effect.8 Given the nebulous nature of pessimism, there is likely no single clear-cut variable that can summarize the phenomenon, but rather a multitude of contributing factors.
Why it is important
Pessimism bias is important to keep in mind on both a personal level, as it can hold individuals back from achieving desired outcomes that are more attainable than one may believe, and on an interpersonal level, as it is commonly associated with depression, and our cognizance of this relationship can be a step forward in mental health awareness.
Additionally, with pessimism bias being more common among women and the elderly,1 the bias may be more of a barrier for some groups than others. For example, women may be more likely to withhold a job application that they are more than qualified for because they underestimate the likelihood of getting an interview.
How to avoid it
Although advice on dealing with depression is beyond the scope of this piece, we can suggest trying to consider future events from a more logical perspective rather than letting your intuition prepare for the worst, as a way to combat the pessimism bias. If the forecast calls for 40% chance of rain on the day of your hike, is it reasonable to conclude that it’s probably going to rain? Probably not.
It should also be mentioned that the pessimism bias does not always lead to irrational behavior, as it can sometimes result in more optimal decision-making.9 Prior to the 2008 financial crisis, much of the infamous “irrational exuberance” was driven by excess optimism, where more pessimistic strategies would have been more ideal in hindsight.
How it all started
The history of the pessimism bias starts with the history of pessimism. Derived from the Latin word pessimus, meaning “worst,” early use of the term predominantly applied to philosophical doctrines that emphasized the evils of life.
Apart from the world of philosophy, research from experimental psychology offered little support for a pessimism bias, as it was the optimism bias that received most attention through the now well-known findings of people believing themselves to be better on average, or to be less likely to have bad things happen to them. It wasn’t until the late ‘90s and early ‘2000s that pessimistic tendencies began to emerge in the literature, such as Justin Kruger’s 1999 paper highlighting a “below-average effect,”10 which suggested that the optimism bias may not be as ubiquitous as many believed.
Relationships between a pessimism bias and depression, however, can be traced further back to the ‘60s, with Aaron Beck, one of the pioneers of Cognitive Behavioral Therapy, suggesting a cognitive-bias model of depression whereby patients exhibit an unrealistic negative perception of themselves and the world,11 arguing that depressed people’s inferences are defined by a “systematic bias against the self.”
Example 1 - Half full, but half empty
The contrast between the optimism bias and the pessimism bias can be confusing, considering both are abundant in our thought processes. Like all cognitive biases, however, they are context dependent, rather than universal effects.
Max Roser and Mohamed Nagdy2 offer a fascinating example that highlights how both optimism and pessimism can coexist in a similar evaluation, depending on the context. They cite the European Union’s Eurobarometer surveys that explore individual’s beliefs around their country’s economic situation as well as their own job prospects. From 1995 to 2015, 60% of people predicted their job situation would remain the same, with 20% predicting improvement. The same group of individuals, however, expected their country’s economic situation to get worse or stay the same. As noted earlier, people are generally optimistic about themselves but pessimistic about society, ie: my job will be okay even if most people are jeopardized.
Example 2 - Depression
A 1987 study from Lauren Alloy and Anthony Ahrens looked at differences in predictions made by people with and without depression.12 They provided participants with predictive information on a student sample and asked them to estimate the percentage of students who would make the Dean’s List as well as the amount who would be put on academic probation. Alloy and Ahrens found that participants overall were more likely to expect others to succeed rather than fail, however this was less likely to be the case among depressed individuals. Additionally, despite everyone being provided with the same contextual information, people with depression were also less likely to forecast future personal success.
Summary
What it is
The pessimism bias relates to the overestimation in the likelihood of negative events alongside an underestimation in the likelihood of positive events.
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