Acting knowingly: effects of the agent's awareness of an opportunity on causal attributions

Hilton, Denis; McClure, John; Moir, Briar Helen

doi:10.1080/13546783.2016.1191547

Cited by 6 publications

(7 citation statements)

References 43 publications

(60 reference statements)

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“…the action that caused the outcome. Integrating epistemic states into causal models and counterfactual frameworks allows us to explain why people often attribute decreased causality to ignorant agents (Hilton, McClure, & Moir, 2016;Hilton & Slugoski, 1986;Kirfel & Lagnado, 2021;Lombrozo, 2010;Samland & Waldmann, 2016a). We present an extension to current counterfactual accounts by introducing epistemic state variables, and we test this extension by investigating people's causal judgments in four experiments.…”

Section: Aim Of This Papermentioning

confidence: 99%

“…While ignorant Romeo might not be blamed for Juliet's death, the causal role of Romeo's acting in Juliet's death seems undisputed at first glance. Recent studies in causal cognition, however, find evidence that agents' epistemic states such as knowledge or ignorance also influence people's causal judgments (Darley & Pittman, 2003;Hilton et al, 2016;Kirfel & Lagnado, 2020;Lagnado & Channon, 2008;Lombrozo, 2010). Agents lacking knowledge (Gilbert, Tenney, Holland, & Spellman, 2015) or foreseeability of the consequences of their actions (Lagnado & Channon, 2008) are judged to be less of a cause for the outcome.…”

Section: Causation By Ignorancementioning

confidence: 99%

“…Agents lacking knowledge (Gilbert, Tenney, Holland, & Spellman, 2015) or foreseeability of the consequences of their actions (Lagnado & Channon, 2008) are judged to be less of a cause for the outcome. In causal chains, the causality of knowing agents is rated higher than those of ignorant ones (Hilton et al, 2016;Lombrozo, 2010;McClure, Hilton, & Sutton, 2007). If the proximal cause is a human action, the agent is judged as more causal if the agent was aware of the causal opportunity created by prior events (Hilton et al, 2016).…”

Section: Causation By Ignorancementioning

confidence: 99%

“…In causal chains, the causality of knowing agents is rated higher than those of ignorant ones (Hilton et al, 2016;Lombrozo, 2010;McClure, Hilton, & Sutton, 2007). If the proximal cause is a human action, the agent is judged as more causal if the agent was aware of the causal opportunity created by prior events (Hilton et al, 2016). Likewise, people's preference for abnormal actions as causes has been shown to be moderated by the agents' knowledge states about their actions (Kirfel & Lagnado, 2020;Kirfel & Phillips, 2021;Samland, Josephs, Waldmann, & Rakoczy, 2016).…”

Section: Causation By Ignorancementioning

confidence: 99%

“…(Gerstenberg, Goodman, Lagnado, & Tenenbaum, 2015;Gerstenberg, Halpern, & Tenenbaum, 2015;Gerstenberg & Icard, 2020;Henne, Kulesza, Perez, & Houcek, 2021;Icard, Kominsky, & Knobe, 2017;Woodward, 2011), both for inanimate causal factors as well as causal agents (Gerstenberg, Halpern, & Tenenbaum, 2015;Gerstenberg & Icard, 2020;Icard et al, 2017). However, a crucial factor that has not yet been considered in detail is the influence of epistemic states on causal judgments about agents (Hilton et al, 2016). In the case of social or agent causation, it is often assumed that the variable that is intervened on in the counterfactual scenario is the agent's action Halpern, 2016;Woodward, 2011).…”

Section: Counterfactual Thinking and Causationmentioning

confidence: 99%

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Changing Minds ― Epistemic Interventions in Causal Reasoning

Kirfel¹,

Lagnado²

2021

Preprint

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Did Tom’s use of nuts in the dish cause Billy’s allergic reaction? According to counterfactual theories of causation, an agent is judged a cause to the extent that their action made a difference to the outcome (Gerstenberg, Goodman, Lagnado, & Tenenbaum, 2020; Gerstenberg, Halpern, & Tenenbaum, 2015; Halpern, 2016; Hitchcock & Knobe, 2009). In this paper, we argue for the integration of epistemic states into current counterfactual accounts of causation. In the case of ignorant causal agents, we demonstrate that people’s counterfactual reasoning primarily targets the agent’s epistemic state – what the agent doesn’t know –, and their epistemic actions – what they could have done to know – rather than the agent’s actual causal action. In four experiments, we show that people’s causal judgment as well as their reasoning about alternatives is sensitive to the epistemic conditions of a causal agent: Knowledge vs. ignorance (Experiment 1), self-caused vs. externally caused ignorance (Experiment 2), the number of epistemic actions (Experiment 3), and the epistemic context (Experiment 4). We see two advantages in integrating epistemic states into causal models and counterfactual frameworks. First, assuming the intervention on indirect, epistemic causes might allow us to explain why people attribute decreased causality to ignorant vs. knowing causal agents. Moreover, causal agents’ epistemic states pick out those factors that can be controlled or manipulated in order to achieve desirable future outcomes, reflecting the forward-looking dimension of causality. We discuss our findings in the broader context of moral and causal cognition.

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Section: Aim Of This Papermentioning

confidence: 99%

Section: Causation By Ignorancementioning

confidence: 99%

Section: Causation By Ignorancementioning

confidence: 99%

Section: Causation By Ignorancementioning

confidence: 99%

Section: Counterfactual Thinking and Causationmentioning

confidence: 99%

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Changing Minds ― Epistemic Interventions in Causal Reasoning

Kirfel¹,

Lagnado²

2021

Preprint

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Attributions for extreme weather events: science and the people

2022

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Both climate scientists and non-scientists (laypeople) attribute extreme weather events to various influences. Laypeople’s attributions for these events are important as these attributions likely influence their views and actions about climate change and extreme events. Research has examined laypeople’s attribution scepticism about climate change in general; however, few climate scientists are familiar with the processes underpinning laypeople’s attributions for individual extreme events. Understanding these lay attributions is important for scientists to communicate their findings to the public. Following a brief summary of the way climate scientists calculate attributions for extreme weather events, we focus on cognitive and motivational processes that underlie laypeople’s attributions for specific events. These include a tendency to prefer single-cause rather than multiple-cause explanations, a discounting of whether possible causes covary with extreme events, a preference for sufficient causes over probabilities, applying prevailing causal narratives, and the influence of motivational factors. For climate scientists and communicators who wish to inform the public about the role of climate change in extreme weather events, these patterns suggest several strategies to explain scientists’ attributions for these events and enhance public engagement with climate change. These strategies include showing more explicitly that extreme weather events reflect multiple causal influences, that climate change is a mechanism that covaries with these events and increases the probability and intensity of many of these events, that human emissions contributing to climate change are controllable, and that misleading communications about weather attributions reflect motivated interests rather than good evidence.

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