Reasoning supports forgiving accidental harms

Abstract

People experience a strong conflict while condemning someone who brought about an accidental harm, her innocent intention exonerating her, but the harmful outcome incriminating her. In the present research (total N = 4879), we explore how reasoning ability and cognitive style relate to how people choose to resolve this conflict and judge the accidental harms. A first set of studies (1a-c) showed that individual differences in cognitive style predicted severity of judgments in fictitious accidental harms scenarios, with more able (or willing) reasoners being less harsh in their judgments. A second set of studies (2a-c) relied on experimental manipulations of cognitive load (Dot matrix, Time pressure, Mortality Salience manipulations), aiming to tax available cognitive resources to participants while evaluating third-party harmful behaviors. These manipulations, however, failed to modulate people’s moral judgments for accidental harms. We discuss the importance of individual differences in reasoning ability in the assessment of accidental harms, and we also propose potential explanations for the failure of our experimental manipulations to affect severity of moral condemnation.

Judging accidental harm: Reasoning style modulates the weight of intention and harm severity

“…Given that we were interested in the effect of both intent and harm severity on moral evaluations and their interaction, we ran the power analysis on the interaction. We used a medium effect size based on a prior data set which found a medium effect of reasoning on moral judgement of accidental harms ( β = –0.15); see Patil & Trémolière, 2021. We set an effect size f = 0.25 (medium effect size) with numerator df = 1 (2 predictors with 2 levels each), and number of groups = 4 (corresponding to the 4 possible combinations of intention by harm severity that were presented to each participant).…”

“…The stories framed an interaction between an agent and a victim in a daily-life context, ending with the perpetrator harming the victim. The perpetrator’s intention was not explicitly stated but had to be inferred by participants from the narratives (see also Patil & Trémolière, 2021). Letting participants infer intentions is indeed more in line with real-life interactions where people have to attribute mental states to others based on implicit cues.…”

“…In the present study, we investigate how reasoning style modulates the contribution of intent and harm severity to third-party moral judgement. Instead of manipulating intent and outcome in a 2 × 2 design with an intent to harm (present/absent) and harmful outcome (present/absent) as in a previous study (Patil & Trémolière, 2021), we proceeded to a subtler manipulation of outcome (mild or severe harm) in scenarios involving a negative versus neutral intention towards the victim (experiment 1) or a positive versus neutral intention (experiment 2). Participants also completed reasoning measures.…”

“…In a recent study which manipulated intent and harm in a 2 x 2 design (negative intent/neutral intent x harmful outcome/no harm), Patil and Trémolière (2021) explored how reasoning impacted judgement severity. Relying on a battery of measures consisting of performance tests (e.g., Cognitive Reflection Test, Belief Bias syllogisms) and self-report questionnaires (e.g., actively open-minded thinking, rational experiential inventory) assessing reasoning, they observed that participants who favoured cognitive deliberation were more forgiving of accidental transgressors specifically.…”

Reasoning supports utilitarian resolutions to moral dilemmas across diverse measures.

“…Several prior studies explore the role of reasoning in utilitarian moral judgment by taxing executive resources necessary for deliberation (Patil & Trémolière, 2018;Trémolière, Neys, & Bonnefon, 2018). This is done in several ways: a) time pressure manipulation: limiting the amount of time available to provide moral judgments (Cummins & Cummins, 2012;Rosas & Aguilar-Pardo, 2019;Suter & Hertwig, 2011); b) cognitive load manipulation: taxing working memory capacity through another concurrent cognitively demanding task (Conway & Gawronski, 2013;Gawronski, Armstrong, Conway, Friesdorf, & Hütter, 2017;Greene, Morelli, Lowenberg, Nystrom, & Cohen, 2008), or exhausting cognitive resources via sleep deprivation (Killgore et al, 2007;Tempesta et al, 2012) or with a prior sequential cognitive depletion task (Timmons & Byrne, 2018), or leading people to think about their mortality (Trémolière, Neys, & Bonnefon, 2012), or, the reverse, easing up the cognitive load by presenting efficient kill-save ratios (Trémolière & Bonnefon, 2014); c) cognitive priming manipulation: nudging participants to use a deliberative thinking mode (versus "feelings thinking mode") (Li, Xia, Wu, & Chen, 2018), priming analytical thinking mode by asking them to solve mathematical puzzles before performing the moral judgment task (Kvaran, Nichols, & Sanfey, 2013), or presenting dilemmas written in hard-to-read (disfluent) fonts (Spears, Fernández-Linsenbarth, Okan, Ruz, & González, 2018) to trigger analytic thinking.…”