Inferences about moral character moderate the impact of consequences on blame and praise

Siegel, Jenifer Z.; Crockett, Molly J.; Dolan, Raymond J.

doi:10.1016/j.cognition.2017.05.004

Cited by 78 publications

(71 citation statements)

References 46 publications

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“…Siegel, Crockett, and Dolan () combined the moral judgment task (described in the previous section) with a manipulation of agents’ moral character. Participants judged the blameworthiness/praiseworthiness of a series of decisions made by two agents with differing moral character.…”

Section: Intersecting Dimensions Of Moral Cognitionmentioning

confidence: 99%

“…One possible explanation for this kind of hypocrisy is readily apparent from our model of moral judgment (Eq. 2), where blame is mitigated by the profitability of harmful actions (Crockett et al., ; Siegel et al., ). It is well established that people value others’ profits far less strongly than their own (Engel, ; Ruff & Fehr, ).…”

Section: Intersecting Dimensions Of Moral Cognitionmentioning

confidence: 99%

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Modeling Morality in 3‐D: Decision‐Making, Judgment, and Inference

Siegel

Crockett

2018

Topics in Cognitive Science

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Humans face a fundamental challenge of how to balance selfish interests against moral considerations. Such trade‐offs are implicit in moral decisions about what to do; judgments of whether an action is morally right or wrong; and inferences about the moral character of others. To date, these three dimensions of moral cognition–decision‐making, judgment, and inference–have been studied largely independently, using very different experimental paradigms. However, important aspects of moral cognition occur at the intersection of multiple dimensions; for instance, moral hypocrisy can be conceived as a disconnect between moral decisions and moral judgments. Here we describe the advantages of investigating these three dimensions of moral cognition within a single computational framework. A core component of this framework is harm aversion, a moral sentiment defined as a distaste for harming others. The framework integrates economic utility models of harm aversion with Bayesian reinforcement learning models describing beliefs about others’ harm aversion. We show how this framework can provide novel insights into the mechanisms of moral decision‐making, judgment, and inference.

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Section: Intersecting Dimensions Of Moral Cognitionmentioning

confidence: 99%

Section: Intersecting Dimensions Of Moral Cognitionmentioning

confidence: 99%

Modeling Morality in 3‐D: Decision‐Making, Judgment, and Inference

Siegel

Crockett

2018

Topics in Cognitive Science

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“…Previous authors have argued that when people make moral judgments, the primary evaluation is of the character of the person committing the act (e.g., Uhlmann et al, 2015;Landy & Uhlmann, 2018; see also, Siegel et al, 2017Siegel et al, , 2018. MJAC does not adopt this position, rather we recognize that there are many potential contextual factors that influence whether the target of any given moral categorization is the actor or on the action (or both).…”

Section: Categorizing People Versus Categorizing Actionsmentioning

confidence: 95%

“…Success in social interactions involves successfully predicting the actions of others (Waytz & Young, 2018). As such, a key goal of moral categorization is to distinguish "good" from "bad" people (Uhlmann et al, 2015), by attempting to identify a person's moral "essence" (e.g., Dunlea & Heiphetz, 2020;Heiphetz & Dunlea, 2019), or "character" (e.g., Klein & O'Brien, 2016;Siegel et al, 2017Siegel et al, , 2018. This enables people to establish relationships or pursue continued interactions with "good" people, and to limit their interactions with "bad" people (or at least treat interactions with "bad" people with caution).…”

Section: Moral Categorization Involving Unknown Othersmentioning

confidence: 99%

Moral Judgment as Categorization (MJAC)

McHugh¹,

McGann²,

Igou³

et al. 2019

Preprint

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Observed variability and complexity of judgments of 'right' and 'wrong' cannot currently be readily accounted for within extant approaches to understanding moral judgment. In response to this challenge we present a novel perspective on categorization in moral judgment. Moral judgment as categorization (MJAC) incorporates principles of category formation research while addressing key challenges to existing approaches to moral judgment. People develop skills in making context-relevant categorizations. That is, they learn that various objects (events, behaviors, people etc.) can be categorized as morally 'right' or 'wrong'. Repetition and rehearsal results in reliable, habitualized categorizations. According to this skill formation account of moral categorization, the learning and the habitualization of the forming of moral categories, occurs within goal-directed activity that is sensitive to various contextual influences. By allowing for the complexity of moral judgments, MJAC offers greater explanatory power than existing approaches, while also providing opportunities for a diverse range of new research questions.

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“…Thus, we predicted that manipulating likability by providing information about others' moral decisions (Siegel, Crockett, & Dolan, 2017) would increase vicarious optimism. 1 Participants read about two strangers who participated in a "Shock Study."…”

Section: Study 3: Vicarious Optimism Is Greater For Likable Strangersmentioning

confidence: 99%

Concern for Others Leads to Vicarious Optimism

Kappes¹,

Crockett²,

Faber³

et al. 2018

Preprint

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An optimistic learning bias leads people to update their beliefs in response to better-than-expected “good news”, but neglect worse-than-expected “bad news”. Because evidence suggests this bias arises from self-concern, we hypothesized that a similar bias may affect beliefs about others’ future, to the extent that people care about others. Here, we demonstrate the phenomenon of vicarious optimism and show that it arises from concern for others. Participants predicted the likelihood of unpleasant future events that could happen to either themselves or others. In addition to showing an optimistic learning bias for events affecting themselves, people showed vicarious optimism when learning about events affecting friends and strangers. Vicarious optimism for strangers correlated with generosity toward strangers, and experimentally increasing concern for strangers amplified vicarious optimism for them. These findings suggest that concern for others can bias beliefs about their future welfare and that optimism in learning is not restricted to oneself.

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Inferences about moral character moderate the impact of consequences on blame and praise

Abstract: HighlightsWe studied how inferences about moral character affect blame and praise judgments.Blame and praise judgments were sensitive to character, consequences and causation.Inferring bad character amplified effects of consequences on judgments.

Cited by 78 publications

References 46 publications

Modeling Morality in 3‐D: Decision‐Making, Judgment, and Inference

Modeling Morality in 3‐D: Decision‐Making, Judgment, and Inference

Moral Judgment as Categorization (MJAC)

Concern for Others Leads to Vicarious Optimism

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