Motivated Reasoning in an Explore‐Exploit Task

Abstract

The current research investigates how prior preferences affect causal learning. Participants were tasked with repeatedly choosing policies (e.g., increase vs. decrease border security funding) in order to maximize the economic output of an imaginary country and inferred the influence of the policies on the economy. The task was challenging and ambiguous, allowing participants to interpret the relations between the policies and the economy in multiple ways. In three studies, we found evidence of motivated reasoning despite financial incentives for accuracy. For example, participants who believed that border security funding should be increased were more likely to conclude that increasing border security funding actually caused a better economy in the task. In Study 2, we hypothesized that having neutral preferences (e.g., preferring neither increased nor decreased spending on border security) would lead to more accurate assessments overall, compared to having a strong initial preference; however, we did not find evidence for such an effect. In Study 3, we tested whether providing participants with possible functional forms of the policies (e.g., the policy takes some time to work or initially has a negative influence but eventually a positive influence) would lead to a smaller influence of motivated reasoning but found little evidence for this effect. This research advances the field of causal learning by studying the role of prior preferences, and in doing so, integrates the fields of causal learning and motivated reasoning using a novel explore-exploit task.

The polarized mind in context: Interdisciplinary approaches to the psychology of political polarization.

“…Second, psychological needs can strengthen existing beliefs through motivated reasoning (Kunda, 1990). People can preferentially access information from memory that supports a desired view of the world (Bower, 1981; Festinger & Carlsmith, 1959; Kunda, 1987), seek out external evidence that uniquely supports desired beliefs (Bakshy et al, 2015; Caddick & Rottman, 2019; Campbell & Kay, 2014; De Dreu et al, 2008; Frimer et al, 2017; Garrett, 2009a, 2009b; Gilovich, 1983; Lord et al, 1979; Nyhan & Reifler, 2010, 2015; Sharot et al, 2011; Stanley et al, 2019; Wood & Porter, 2019), and apply specific rules to make judgments or choices that support desired goals (e.g., ignoring the base rate; Ginossar & Trope, 1987). Third, once a person has developed a biased worldview, any new information is interpreted in a partisan way even without motivated reasoning (Cook & Lewandowsky, 2016; Gerber & Green, 1999; Jern et al, 2014; Miller & Ross, 1975).…”

A Bayesian decision-theoretic framework for studying motivated reasoning

“…In studies of motivated reasoning, participants are motivated to believe one hypothesis over another. For example, they are motivated to believe that their political party has the right economic policy (Caddick & Rottman, 2021). We quantify this motivation using a utility function, which maps world states (e.g., the actuality of a hypothesis h i ) to utility values.…”

Polarized imagination: partisanship influences the direction and consequences of counterfactual thinking

“…Much like people selectively search their memories for evidence consistent with preferred beliefs (e.g. [14]) or test the impact of selected economic choices in line with their political preference [15], partisans may thus selectively imagine counterfactuals in whichever direction is consistent with preferred political conclusions. Second, different partisans have different knowledge, beliefs and assumptions.…”