User:Lnbiggs/Motivated reasoning

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Motivated reasoning is a phenomenon studied in cognitive science and social psychology that uses emotionally biased reasoning to produce justifications or make decisions that are most desired rather than those that accurately reflect the evidence. In other words, motivated reasoning is the "tendency to find arguments in favor of conclusions we want to believe to be stronger than arguments for conclusions we do not want to believe".

Motivated reasoning is similar to confirmation bias, where evidence that confirms a belief (which might be a logical belief, rather than an emotional one) is either sought after more or given more credibility than evidence that disconfirms a belief. It stands in contrast to critical thinking where beliefs are approached in a skeptical and unbiased fashion.

It can lead to forming and clinging to false beliefs despite substantial evidence to the contrary. The desired outcome acts as a filter that affects evaluation of scientific evidence and of other people.

Mechanisms

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. In order for someone to participate in motivated reasoning, either consciously or subconsciously, that individual first needs be motivated.

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). 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

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".

However, current research refutes that conclusion. “Banks and Hope (2014) early conflict sensitivity findings indicate that logical reasoning—a process that is traditionally believed to require slow System 2 computations—can literally be accomplished in a split second." That is according to Bago et al. EEG study which shows that elementary logical reasoning happens in the same neurocircuitry as the emotional fast reasoning. The next 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.

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:

1. Subjects must possess appropriate reasoning strategies.
2. They must view these as superior to other strategies.
3. They must be capable of using these strategies 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).

To summarize, 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.^{[citation needed]}

Research

As stated above, neuroscience research suggests that "motivated reasoning is qualitatively distinct from reasoning when people do not have a strong emotional stake in the conclusions reached." However, if there is a strong emotion attached during their previous round of motivated reasoning and that emotion is again present when the individual's conclusion is reached, a strong emotional stake is then attached to the conclusion. Any new information in regards to that conclusion will cause motivated reasoning to reoccur. This can create pathways within the neural network that further ingrains the reasoned beliefs of that individual along similar neural networks where logical reasoning occurs. This causes the strong emotion to reoccur when confronted with contradictory information, time and time again. This is what is referred to by Lodge and Taber as the affective contagion. But instead of "infecting" other individuals, the emotion "infects" the individuals reasoning pathways and conclusions.

Social science research suggests that reasoning away contradictions is psychologically easier than revising feelings. As previously discussed, emotions are shown to color how "facts" are perceived. Feelings come first, and evidence is used in service of those feelings. Evidence that supports what is already believed is accepted. Evidence which contradicts those beliefs is not. An example of motivated reasoning in the public sphere is the fact that many people continued to believe that Barack Obama was not born in the United States in the face of ample evidence that he was.

Outcomes

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." Recent studies have shown that when people are presented with and forced to think analytically about something complex that they lack adequate knowledge of (i.e. being presented with a new study on meteorology whilst having no degree in the subject), there is no directional shift in thinking, and their extant conclusions are more likely to be supported with motivated reasoning. Conversely, if they are presented with a more simplistic test of analytical thinking that confronts their beliefs (i.e. seeing implausible headlines as false), motivated reasoning is less likely to occur and a directional shift in thinking may result.

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. These results have far reaching consequences because, when confronted with a small amount of information contrary to an established belief, an individual is motivated to reason away the new information, contributing to the hostile media effect. If this pattern continues over an extended period of time, the individual becomes more entrenched in their beliefs. However, recent studies have shown that motivated reasoning can be overcome. "When the amount of incongruency is relatively small, the heightened negative affect does not necessarily override the motivation to maintain [belief]." However, there is evidence of a theoretical "tipping point" where the amount of incongruent information that is received by the motivated reasoner can turn certainty into anxiety. This anxiety of being incorrect may lead to a change of opinion.

Climate Change

Coal-fired power station Neurath in Grevenbroich, North Rhine-Westphalia, Germany.

The topic of climate change is a prime example where motivated reasoning to not believe in climate change is shown. Climate change is becoming an increasingly obvious issue in the US specifically. Though there are many facts and evidence showing it many still like to debate if the issue really is what it seems to be. Many deny climate change, say it is a hoax, blames the government, mind control, conspiracy theories, etc. “A significant segment of the American public has fixed beliefs, either because they are not politically engaged, or because they hold strong beliefs that are unlikely to change”(Brulle). With the hundreds of facts given to people about climate change, the thousands of power plants and melting ice caps, the phenomenon of motivated reasoning keeps people stubborn in their belief that climate change is not real.

Social Media

Social media is used for many different purposes and ways of spreading opinions. It is the number one place people go to get information and most of that information is complete opinion and bias. The way this applies to motivated reasoning is the way it spreads, “However, motivated reasoning suggests that informational uses of social media are conditioned by various social and cultural ways of thinking” (Diehl). All ideas and opinions are shared and makes it very easy for motivated reasoning and biases to come through when searching for an answer or just facts on the internet or any news source.

References

1. Curry, Judith. “Climate scientists’ motivated reasoning.” Offcampus.lib.washington.edu, 19 June 2019, www.proquest.com/agricenvironm/docview/2253348492/C68EE68BD104AF0PQ/3?accountid=14784.

2. Trevor Diehl, Brigitte Huber, Homero Gil de Zúñiga, James Liu, Social Media and Beliefs about Climate Change: A Cross-National Analysis of News Use, Political Ideology, and Trust in Science, International Journal of Public Opinion Research, Volume 33, Issue 2, 2021, Pages 197–213, https://doi-org.offcampus.lib.washington.edu/10.1093/ijpor/edz040

3. Brulle, Robert J., et al. “Shifting Public Opinion on Climate Change: An Empirical Assessment of Factors Influencing Concern over Climate Change in the U.S., 2002–2010.” Climatic Change, vol. 114, no. 2, 3 Feb. 2012, pp. 169–188, 10.1007/s10584-012-0403-y.

4. Brenes-Peralta, Carlos, et al. “Can I Stick to My Guns? Motivated Reasoning and Biased Processing of Balanced Political Information.” Communication & Society, 13 Apr. 2021, pp. 49–66, 10.15581/003.34.2.49-66.