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Attribution Biases

Updated: 20 April 2016

An attribution bias is  a distortion in perception or judgement about the causes of our own or other people’s behaviour. The attributions people make are not always accurate due to these cognitive biases. Rather than operating as objective perceivers, people are prone to perceptual errors that lead to biased interpretations of their social world

Some of the most important biases are:-

Fundamental Attribution Error
Also known as Correspondence Bias or Overattribution Effect, this is the tendency for people to over-emphasise dispositional (or personality-based), explanations for behaviours observed in others while under-emphasising situational explanations. In other words, people have an unjustified tendency to assume that a person’s actions depend on what ‘kind’ of person that person is rather than on the social and environmental forces influencing the person.

The term was coined by Lee Ross (1977) after a now-classic experiment by Edward E Jones & Victor Harris (1967). Americn participants read short pro- and anti-Fidel Castro essays. They were asked to rate the pro-Castro attitudes of the writers. When the participants believed that the writers freely chose the positions they took (for or against Castro), they naturally rated the people who spoke in favour of Castro as having a more positive attitude toward Castro. However, when the participants were told that the writer’s positions were determined by a coin toss, they still rated writers who spoke in favor of Castro as having, on average, a more positive attitude towards Castro than those who spoke against him. In other words, the participants were unable to see the influence of the situational constraints placed upon the writers; they could not refrain from attributing sincere belief to the writers.

A notable study on the less pleasant effects of the Fundamental Attribution Error was conducted by Dara Musher-Eizenman et al (2004). 42 young children of average age 5 years were asked to describe other children of different body type and explain how body types were different. The children tended to make dispositional attributions for being overweight, with the most negative descriptions of overweight children coming from those who had made dispositional attributions.

Ross explains the Fundamental Attribution Error in terms of people being ‘miserly’ in their cognitive processing – ie: it is quicker and easier simply to make a dispositional attribution than work through situational factors that could influence behaviour. Support for this hypothesis comes from William Rholes & John Pryor (1982) who found that, when people are primed to pay attention to situational factors, they are less likely to be dispositional in their attributions of the observed behaviour.

Fathali Moghaddam (1998) has proposed that there is a cultural bias in the working of the Fundamental Attribution Error. In Western cultures, individuals are encouraged to take responsibility for their own actions (Individualism). In non-Western countries, responsibility is usually with the group (Collectivism) so there are fewer dispositional attributions. Some support for this is found in the work of Joan Miller (1984). She asked adult Americans and Indian Hindus to explain common events such as a work colleague stealing someone else’s idea. The Americans put forward dispositional explanations 3 times more than situational while the Indian Hindus used situational explanations twice as often as dispositional. This shows a potential vMEME effect at a cultural level, with the ‘warm’ express-self colours of the Spiral tending to drive dispositional individual behaviour while the ‘cool’ conformist/self-sacrifice colours look outwards for direction/guidance on behaviour.

At a group level, the Fundamental Attribution Error takes on an in-group/out-group effect and is termed the ‘Ultimate Attribution Error’ (Thomas Pettigrew, 1979).

One example is that of Roos Vonk & Dorien Konst (1998) who read out descriptions of either socially acceptable or unacceptable behaviour by a colleague to a 149 employees in an organisation. The descriptions were accompanied by information to suggest that the behaviour was either dispositional or situational in origin. Vonk & Konst found, that, when the person committing the behaviour was an in-group member, participants were more likely to make situational attributions for socially unacceptable behaviour – so it becomes only primary deviance in Edwin Lemert’s (1972) terms – and dispositional attributions for more positive behaviours. The opposite effects were found for out-group members. This illustrates the way the PURPLE vMEME discriminates between those of ‘our tribe’ and those ‘not of our tribe’.

Disturbingly Jane Workman & Elizabeth Freeburg (1999) found that gender could lead to a very powerful in-group/out-group effect. They read 638 students a story involving date rape, showed them photographs of the victim and asked the students to attribute responsibility to the victim, the perpetrator or the situation. Males were significantly more likely to attribute responsibility to the victim while females were more likely to blame the perpetrator.

Racism equally seems to have an in-group/out-group effect on attributional style. Birt Duncan (1976) showed white participants video of a white or black person pushing another during a heated conversation. Participants made internal attributions (eg: “violent personality”) when the pusher was black and external attributions for the white aggressor (eg: “he was provoked”).

See Prejudice & Discrimination for more on how the in-group/outgroup affect is linked with attribution biases.

Halo Effect
Closely related to the Fundamental Attribution Error is the Halo Effect. This is an attribution bias in which an observer’s overall impression of a person, company, brand or product is strongly influenced by the observer’s feelings and thoughts about a particular trait or characteristic of that entity’s character. The term comes from Edward Thorndike (1920) in reference to a person being perceived as having a halo – being like an angel because of one highly-desirable trait or characteristic. In one of his earlier studies with soldiers asked to rate their commanding officers, Thorndike found high cross-correlations between all positive and all negative traits. The Halo Effect is a specific type of confirmation bias, in which positive feelings in one area lead ambiguous or neutral traits to be viewed positively. One dispositional aspect to the entity is generalised to all dispositional aspects of the entity. Thorndike thought of the term applying only to people; however, its use has been greatly expanded especially in the area of brand marketing.

The Halo Effect works in both positive and negative directions. The Horns Effect is said to apply when people allow an undesirable trait to influence their evaluation of other traits.

People seem to rarely think of each other in mixed terms; instead they seem to see others as universally roughly good or roughly bad across all categories of measurement  Thus, if the observer likes one aspect of something, they will have a positive predisposition toward everything about it. If the observer dislikes one aspect of something, they will have a negative predisposition toward everything about it. Once the Halo or Horns Effect is applied, it effectively creates a label which then impacts upon both the person it is applied to and the expectations of others.

Many researchers have studied the Halo Effect in relation to attractiveness and its bearing on the judicial and educational systems.

For instance, John Stewart (1985), from observations of 60 trials in the American state of Pennsylvania, found a negative correlation between the attractiveness of the person found guilty and the type and length of sentence handed out. In other words, the more attractive the person, the more lenient the sentence. This study of real life trials confirmed the earlier findings of Harold Sigall & Nancy Ostrove’s  much-cited 1975 sentence -recommendation study in which 120 participants were given the nature of the crime and a photograph of the convicted person. However, Sigall & Ostrove also found a a positive correlation between attractiveness and sentence recommendation for fraud, with participants reacting negatively to people using their attractiveness to help defraud their victims. Interestingly, Alexis Scangas (2005) found a long-suspected effect of gender when it came to swindling. In a partial replication of Sigall & Ostrove, male participants stipulated harsher sentences for attractive women who used their attractiveness to defraud men!

Just one of many studies into the Halo Effect in education is that of Jordan Rich (1975).  Female teachers evaluated students individually for blame, punishment and personality after viewing a photograph of an attractive or unattractive child and a vignette of possible misbehaviour by that child,  Attractive children received better personality ratings than did unattractive. Unattractive girls were given more lenient punishments than unattractive boys, again showing a gender effect.

In marketing, a Halo Effect is where the perceived positive features of a particular item extend to a broader brand. Eg: it has been used to describe how the iPhone has had positive effects on perceptions of Apple Computer’s other products.

Actor-Observer Effect
Edward E Jones & Robert Nisbett (1972) extended the Fundamental Attribution Error with the Actor-Observer Effect. This posits that actors carrying out a socially-undesirable behaviour tend to attribute it to their circumstances (ie: situational causes). However, they tend to attribute the socially-undesirable behaviours of those we observe to their dispositions (ie: person causes).

Simply put, the Actor-Observer Effect can be expressed as: “If others do it, it’s their fault. If I do it, it’s not my fault – it’s because of the situation I’m in.”

Evidence does indeed support the Actor-Observer Effect. Eg: from a study of 321 car crash survivors, Alan E Stewart (2005) found they overwhelmingly attributed their accidents to the behaviour of other drivers (external) while their own driving was considered okay (internal). However, evidence does not always support the concept as put forward by Jones & Nusbett. In a meta-analysis of a 173 studies on the Actor-Observer Effect published since Jones & Nisbett, Bertram F Malle (2006) noted there has been distinct lack of support for the Actor-Observer Effect. In other words, actors and observers often do not follow the patterns put forward by Jones & Nisbett. Instead it is hypothesized that we use everyday experiential explanations that are centered around an unintentional or intentional cause – ie: was the behaviour intended? – and the degree of awareness of the consequences of the action (Malle, 2007).

This disrepancies between Jones & Nisbett’s work and Malle’s findings may be due to neither taking motivation or temperament into account. Certainly attributing socially-undesirable behaviour to situational factors enables the RED vMEME to avoid personal guilt.

Self-Serving Bias
Also related to the Fundamental Attribution Error is the Self-Serving Bias which occurs when people attribute their successes to internal or personal factors but attribute their failures to situational factors beyond their control. According to Dale Miller & Michael Ross 1975, the Self-Serving Bias can be seen in the common human tendency to take credit for success but to deny responsibility for failure. It may also manifest itself as a tendency for people to evaluate ambiguous information in a way that is beneficial to their interests. The Self-Serving Bias may be associated with the ‘Better-than-Average Effect’, in which the individual is biased to believe that he or she typically performs better than the average person in areas important to their self esteem. Eg: studies by J Kruger (1999) and Neal Roese & James Olson (2007) show that a majority of drivers think they drive better than the average driver.

The term Self-Serving Bias is most often used to describe a pattern of biased causal inference, in which praise or blame depend on whether success or failure was achieved. For example, a student who gets a good grade on an exam might say, “I got an A because I am intelligent and I studied hard!” whereas a student who does poorly on an exam might say, “The teacher gave me an F because he does not like me!” When someone strategically strives to facilitate external causes for their poor performance (so that they will subsequently have a means to avoid blaming themselves for failure), it may be labelled ‘self-handicapping’. Again, such behaviour is typical of the RED vMEME.

This I’m responsible for my success; my failures are due to others or external circumstances beyond my control pattern is typical of the kind of attributions the RED vMEME creates in the Cognitive Triad, seeking to boost self-esteem and avoid shame. This was demonstrated experimentally by Dale Miller (1976) who gave participants a test of social perceptiveness; they were then told on a random basis whether they had succeeded or failed. Half were told it was a good test; the other half it was a bad test. Those who believed the test was valid showed more of a self-serving bias than the others.

Another example of the Self-Serving Bias can be found in the workplace. Victims of serious occupational accidents tend to attribute their accidents to external factors, whereas their co-workers and management tend to attribute the accidents to the victims’ own actions.

False Consensus Effect
The False Consensus Effect, first put forward by Lee Ross, D Greene & P House (1977). is the tendency for people to project their way of thinking onto other people. In other words, they assume that everyone else thinks the same way they do. This supposed correlation is unsubstantiated, leading to the perception of a consensus that does not exist. This logical fallacy involves a group or individual assuming that their own opinions, beliefs and predilections are more prevalent amongst the general public than they really are.

In the False Consensus Effect, when confronted with evidence that a consensus does not exist, people tend to regard their own views as ‘normal’ and assume that those who do not agree with them are defective in some way (James Fields & Howard Schuman, 1977). When 1st Tier vMEMES dominate the selfplex, people will usually have great difficulty in appreciating that others can have different values and beliefs to them which, to the others, are equally, if not more valid.

Ross (1977) demonstrated the False Consensus Effect when he got students to walk around campus for 30 minutes with a sandwich board proclaiming ‘Eat at Joe’s’. Those who did indeed eat at Joe’s estimated that 62% of their peers also did so. Those who did not eat at Joe’s estimated that 67% of their peers didn’t either.

This bias is commonly present in a group setting where one thinks the collective opinion of their own group matches that of the larger population. Since the members of such a group reach a consensus and rarely encounter those who dispute it, they tend to believe that everybody thinks the same way. This tends to produce the effect Irving Janis (1972) termed groupthink.where there is no perceived need to consult outside the group.

Gilbert Botvin et al (1992) looked at whether students show a higher level of False Consensus Effect among their direct peers as opposed to society at large. The participants of this experiment were 203 college students ranging in age from 18 to 25 (with an average age of 18.5). The participants were given a questionnaire and asked to answer questions regarding a variety of social topics. For each social topic, they were asked to answer how they felt about the topic and to estimate the percentage of their peers who would agree with them. The results determined that the False Consensus Effect was extremely prevalent when participants were describing the rest of their college community; out of 20 topics considered, 16 prominently demonstrated the False Consensus Effect. The high levels of false consensus seen in this study can be attributed to the group studied; because the participants were asked to compare themselves to a group of peers that they are constantly around (and view as very similar to themselves), the levels of false consensus increased, demonstrating an in-group effect.

Donald Granberg (1987) states that tendency to the False Consensus Effect is driven by how important they are to us and how certain we are about them. Clearly the False Consensus Effect is driven primarily by the RED vMEME, but possibly in harmonics with other vMEMES too. A RED/BLUE harmonic false consensus could lead to zealotry. PURPLE will be involved in an in-group false ccnsensus.

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4 Responses

  1. Keith E Rice says

    Both Graves and Maslow would agree with you, Jon, re 1st Tier viewpoints, They both held that 1st Tier is deluded and you can only really see things as they are once you self-actualise into YELLOW. As to what vMEMES are, I would state that they are sets of neurological systems operating in the individual. The work of Svenja Caspers & Marc Lucas, getting people to make values choices while in an MRI scanner, shows that the warm colours are more associated with the limbic system and the cool colours with the frontal cortex. This supports the work of Mark Solms who, using the Freudian model and putting dreamers through a PET scanner, associated the ID (RED) with the limbic system and Ego (PURPLE-ish) and Superego (BLUE/GREEN) functions with the frontal cortex. Fpr more on this, see http://www.integratedsociopsychology.net/articles/a-biological-basis-for-vmemes/ Of course, when you get people thinking the same way, you get a cultural vMEME effect – which is where 4Q/8L is so useful. The interaction of emergence with the external environment is a vital one. Graves – and to some extent Loevinger (with her concept of pacers) – saw emergence as being related to external factors (life conditions). Maslow and Freud saw it as more internal – ie: maturational.

  2. Jon says

    What I was wondering is do we get into the habit of saying things are driven by the colours when perhaps it’s really the other way round – the colours are really collections of behaviours / brain features – programmes with some elements dominant at different colours. So, what is the underlying mechanism for this behaviour and clearly some behaviour can be present at all levels even if they are not the dominant ones. I would say the inability to recognise, or perhaps to empathise with, other points of view is actually first tier generally – just as we progress up through first tier our reactions to “other” views lessons both in scopes and intensity as intellectual recognition of arguments grows. But at second tier we begin to see real empathy for all the first tier views

  3. Keith E Rice says

    Re RED and false consensus…. RED is full of itself, can’t be wrong, can’t be shamed. It only takes into account others either to be dominated/used or challenged or reluctantly submitted to if clearly more powerful. It’s unthinkable to nodal RED that others would not automatically have the same view because it is the centre of its universe.

    Of course, there are myriad contexts in which false consensus occurs which is why I’ve talked about vMEME harmonics.

    In any inability to recognise the validity of another’s viewpoint, I would hazard there is an element of RED. Recognising the validity of other views means we can’t totally express our own which is what nodal RED does.

    Does that explain it…?

  4. Jon says

    a question re false concensus being driven by red – I am not immidiately sure why that would be? Is it not that it would occur wherever we have assumed something to be true we naturally expect other people to believe the same – I e it’s common sense. This would clearly happen more often lower down the spiral generally but could vary individually vs collectively and almost certainly would fall away a lot, but not completely, with 2nd tier awareness of the different motivational values and assumptions ?