The Zero-Sum Fallacy in Evidence Evaluation

Pilditch, Toby D.; Fenton, Norman; Lagnado, David A.

doi:10.1177/0956797618818484

Cited by 26 publications

(32 citation statements)

References 12 publications

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“…However, even in contexts that have the potential to be non-zero-sum, there is reason to expect that people will continue to perceive moral value as a limited resource. A pervasive bias to believe that most situations are zero-sum has been documented in disparate other domains (Bazerman, 1983;Meegan, 2010;Norton & Sommers, 2011;Pilditch, Fenton, & Lagnado, 2019) and may be a general feature of social reasoning (Różycka-Tran, Boski, & Wojciszke, 2015). Given that moral cognition often recruits aspects of general-purpose cognition (Miller & Cushman, 2018), a zero-sum bias can also be expected to emerge in the moral domain.…”

Section: The Finitude Of Moral Concernmentioning

confidence: 99%

Tree‐Huggers Versus Human‐Lovers: Anthropomorphism and Dehumanization Predict Valuing Nature Over Outgroups

Rottman¹,

Crimston

Syropoulos

2021

Cognitive Science

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Previous examinations of the scope of moral concern have focused on aggregate attributions of moral worth. However, because trade‐offs exist in valuing different kinds of entities, tabulating total amounts of moral expansiveness may conceal significant individual differences in the relative proportions of moral valuation ascribed to various entities. We hypothesized that some individuals (“tree‐huggers”) would ascribe greater moral worth to animals and ecosystems than to humans from marginalized or stigmatized groups, while others (“human‐lovers”) would ascribe greater moral worth to outgroup members than to the natural world. Additionally, because moral valuation is often treated as being zero‐sum, we hypothesized that there would be no difference in aggregate levels of moral concern between tree‐huggers and human‐lovers. Finally, because attributions of mental capacities substantially contribute to moral valuation, we predicted that tree‐huggers and human‐lovers would show different patterns of mind attribution for animals versus humans. Three studies (N = 985) yielded evidence in support of our hypotheses. First, over one‐third of participants valued nature over outgroups. Second, extending moral value to animals and nature was not indicative of more expansive moral concern overall; instead, tree‐huggers and human‐lovers were identical in their aggregate ascriptions of moral worth. Third, tree‐huggers had relatively amplified tendencies to attribute mental capacities to animals and relatively reduced tendencies to attribute mental capacities to outgroup members—thus having elevated rates of both anthropomorphism and dehumanization. These findings necessitate a reconceptualization of both the extension of moral worth and the attribution of minds.

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Section: The Finitude Of Moral Concernmentioning

confidence: 99%

Tree‐Huggers Versus Human‐Lovers: Anthropomorphism and Dehumanization Predict Valuing Nature Over Outgroups

Rottman¹,

Crimston

Syropoulos

2021

Cognitive Science

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“…However, integrative performance in general has been shown to suffer when complexity increases, though this has typically been assessed in qualitative judgments (see e.g. Pilditch, Hahn, & Lagnado, 2018;Pilditch, Fenton & Lagnado, 2019), with deleterious performance found when witness reliabilities differ across a single integration (Phillips, Hahn, & Pilditch, 2018).…”

Section: Discussionmentioning

confidence: 99%

Strange but true: Corroboration and base rate neglect.

Pilditch

Lagator

Lagnado

2021

Journal of Experimental Psychology: Learning, Memory, and Cogni

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How do we deal with unlikely witness testimonies? Whether in legal or everyday reasoning, corroborative evidence is generally considered a strong marker of support for the reported hypothesis. However, questions remain regarding how the prior probability, or base rate, of that hypothesis interacts with corroboration. Using a Bayesian Network model, we illustrate an inverse relationship between the base rate of a hypothesis, and the support provided by corroboration. More precisely, as the base rate of hypothesis becomes more unlikely (and thus there is lower expectation of corroborating testimony), each piece of confirming testimony provides a non-linear increase in support, relative to a more commonplace hypothesis-assuming independence between witnesses. We show across three experiments that lay reasoners consistently fail to account for this impact of (rare) base rates in both diagnostic and intercausal reasoning, resulting in substantial underestimation in belief updating. We consider this a novel demonstration of an inverted form of base rate neglect. We highlight the implications of this work for any scenario in which one cannot assume the confirmation or disconfirmation of a reported hypothesis is uniform.

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“…The problem descriptions and the rubrics used to mark the solutions are included in the OSF repository for the study. The probabilistic features measured by each problem are summarized in Table 1 (for more specific theoretical and empirical background to the problems see Dewitt et al, 2018;Liefgreen et al, 2018;Phillips et al, 2018;Pilditch et al, 2018Pilditch et al, , 2019. Participants in the treatment group worked through the problems using the Bayesian network tool.…”

Section: Methodsmentioning

confidence: 99%

Widening Access to Bayesian Problem Solving

et al. 2020

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Bayesian reasoning and decision making is widely considered normative because it minimizes prediction error in a coherent way. However, it is often difficult to apply Bayesian principles to complex real world problems, which typically have many unknowns and interconnected variables. Bayesian network modeling techniques make it possible to model such problems and obtain precise predictions about the causal impact that changing the value of one variable may have on the values of other variables connected to it. But Bayesian modeling is itself complex, and has until now remained largely inaccessible to lay people. In a large scale lab experiment, we provide proof of principle that a Bayesian network modeling tool, adapted to provide basic training and guidance on the modeling process to beginners without requiring knowledge of the mathematical machinery working behind the scenes, significantly helps lay people find normative Bayesian solutions to complex problems, compared to generic training on probabilistic reasoning. We discuss the implications of this finding for the use of Bayesian network software tools in applied contexts such as security, medical, forensic, economic or environmental decision making.

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The Zero-Sum Fallacy in Evidence Evaluation

Cited by 26 publications

References 12 publications

Tree‐Huggers Versus Human‐Lovers: Anthropomorphism and Dehumanization Predict Valuing Nature Over Outgroups

Tree‐Huggers Versus Human‐Lovers: Anthropomorphism and Dehumanization Predict Valuing Nature Over Outgroups

Strange but true: Corroboration and base rate neglect.

Widening Access to Bayesian Problem Solving

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