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Motivated reasoning is an emotion-biased decision-making phenomenon studied in cognitive science and social psychology. This term describes the role of motivation in cognitive processes such as decision-making and attitude change in a number of paradigms, including:
- Cognitive dissonance reduction
- Beliefs about others on whom one's own outcomes depend
- Evaluation of evidence related to one's own outcomes
The processes of motivated reasoning are a type of inferred justification strategy which is used to mitigate cognitive dissonance. When people form and cling to false beliefs despite overwhelming evidence, the phenomenon is labeled "motivated reasoning". In other words, "rather than search rationally for information that either confirms or disconfirms a particular belief, people actually seek out information that confirms what they already believe." This is "a form of implicit emotion regulation in which the brain converges on judgments that minimize negative and maximize positive affect states associated with threat to or attainment of motives."
Early research on the evaluation and integration of information supported a cognitive approach consistent with Bayesian probability, in which individuals’ weighted new information using rational calculations. More recent theories endorse cognitive processes as partial explanations of motivated reasoning but have also introduced motivational or affective processes to further illuminate the mechanisms of the bias inherent in cases of motivated reasoning. To further complicate the issue, the first neuro-imaging study designed to test the neural circuitry of individuals engaged in motivated reasoning found that motivated reasoning ‘was not associated with neural activity in regions previously linked with cold reasoning tasks [Bayesian reasoning] and conscious (explicit) emotion regulation.” This section focuses on two theories that elucidate the mechanisms involved in motivated reasoning. Both theories distinguish between mechanisms present when the individual is trying to reach an accurate conclusion, and those present when the individual has a directional goal.
Goal Oriented Motivated Reasoning
One review of the research develops the following theoretical model to explain the mechanism by which motivated reasoning results in bias. The model is summarized as follows:
Motivation to arrive at a desired conclusion provides a level of arousal, which acts as an initial trigger for the operation of cognitive processes. Historically, motivated reasoning theory identifies that directional goals enhance the accessibility of knowledge structures (memories, information, knowledge) that are consistent with desired conclusions. This theory endorses previous research on accessing information, but adds a procedural component in specifying that the motivation to achieve directional goals will also influence which rules (procedural structures such as inferential rules) and which beliefs are accessed to guide the search for information. In this model the beliefs and rule structures are instrumental in directing which information will be obtained to support the desired conclusion.
In comparison, Milton Lodge and Charles Taber (2000) introduce an empirically supported model in which affect is intricately tied to cognition, and information processing is biased toward support for positions that the individual already holds.
This model has three components:
1) On-line processing - in which when called on to make an evaluation, people instantly draw on stored information which is marked with affect;
2) Affect is automatically activated along with the cognitive node to which it is tied;
3) A ‘heuristic mechanism’ for evaluating new information triggers a reflection on ‘How do I feel?” about this topic. The result of this process results in a bias towards maintaining existing affect, even in the face of other, disconfirming information.
This theory of motivated reasoning is fully developed and tested in Lodge and Taber's The Rationalizing Voter (2013). Interestingly, David Redlawsk (2002) found that the timing of when disconfirming information was introduced played a role in determining bias. When subjects encountered incongruity during an information search, the automatic assimilation and update process was interrupted. This results in one of two outcomes: subjects may enhance attitude strength in a desire to support existing affect (resulting in degradation in decision quality and potential bias) or, subjects may counter-argue existing beliefs in an attempt to integrate the new data. This second outcome is consistent with the research on how processing occurs when one is tasked with accuracy goals.
Accuracy Oriented Motivated Reasoning
Kunda asserts that accuracy goals delay the process of coming to a premature conclusion, in that accuracy goals increase both the quantity and quality of processing - particularly in leading to more complex inferential cognitive processing procedures. When researchers manipulated test subjects motivation to be accurate by informing them that the target task was highly important or that they would be expected to defend their judgments, it was found that subjects utilized deeper processing, and that there was less biasing of information. This was true when accuracy motives were present at the initial processing and encoding of information. Tetlock (1983, 1985) In reviewing a line of research on accuracy goals and bias, Kunda concludes, “several different kinds of biases have been shown to weaken in the presence of accuracy goals.” She asserts that for accuracy to reduce bias the following conditions must be present.
- Subjects must possess appropriate reasoning strategies
- They must view these as superior to other strategies,
- And be capable of using them at will.
These last two conditions introduce the construct that accuracy goals include a conscious process of utilizing cognitive strategies in motivated reasoning. This construct is called into question by later neuroscience research that concludes that motivated reasoning is qualitatively distinct from reasoning (in instances when there is no strong emotional stake in the outcomes), (Weston, 2006 ).
In summary, both models differentiate between accuracy goals, and goal directed processing. They differ in that Redlawsk identifies a primary role for affect in guiding cognitive processes and in maintaining bias. In contrast, Kunda identifies a primary role for cognitive processes such as memory processes, and the use of rules in determining biased information selection. At least one study in neuroscience does not support the use of cognitive processes in motivated reasoning, lending greater support to affective processing as a key mechanism in supporting bias. Of interest, neuroscience is consistent with Freud’s (1933) theory of "defensive processing" which occurred in the unconscious, and was seen as a mechanism to avoid feelings of anxiety and guilt.
Neuroscientific research suggest that "motivated reasoning is qualitatively distinct from reasoning when people do not have a strong emotional stake in the conclusions reached."
Social science research suggests that reasoning away contradictions is psychologically easier than revising feelings. In this sense, emotions are shown to color how "facts" are perceived. Feelings come first, and evidence is used mostly in service of those feelings. Evidence that supports what is already believed is accepted, that which contradicts it is not.
The outcomes of motivated reasoning derive from "a biased set of cognitive processes — that is, strategies for accessing, constructing, and evaluating beliefs. The motivation to be accurate enhances use of those beliefs and strategies that are considered most appropriate, whereas the motivation to arrive at particular conclusions enhances use of those that are considered most likely to yield the desired conclusion.
Research on motivated reasoning tested accuracy goals (i.e., reaching correct conclusions) and directional goals (i.e., reaching preferred conclusions). Factors such as these affect perceptions; and results confirm that motivated reasoning affects decision-making and estimates.
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