Elisa van der Plas’s research while affiliated with University College London and other places

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Publications (2)


Overview of experimental design. Manipulation of source and destination as a function of study number. In Study 1 participants made moral decisions that varied as a function of the source (dirty vs. clean). In Study 2 participants made blame judgments about moral decisions that varied as a function of destination (profit vs. charity). In Study 3 participants made moral decisions that varied as a function of the source and destination.
Moral decision-making task and modeling framework. (a) To probe moral decisions, participants (known as the “Decider”) made a series of real decisions, where each decision involved choosing between two options: a smaller amount of money plus a smaller number of painful electric shocks, or a larger amount of money plus a larger number of shocks. Before observing the choice options, a screen was presented indicating the recipient of the money and the shocks on the current trial. For half of the trials the shocks were allocated to the Decider and for the other half the shocks were allocated to an anonymous stranger in the next room. In study 1, the money recipient was always the Decider. In study 3, for half of the trials the recipient of money was the Decider and for half the trials the money was donated to a charity (Children with Cancer, UK). (b) Visual schematic for how the DDM captures choices and response times in Study 1 and Study 3. Responses are coded as larger shocks on the upper threshold and smaller shocks on lower threshold. Model parameters are discussed in the main text. (c) Moral decisions involving clean and dirty money (Study 1). The valuation of pain and money are sensitive to source effects: The weight on shocks was significantly higher when considering dirty relative to clean money (purple), while the weight on money was significantly lower when considering dirty relative to clean money (green).
Moral judgment task and destination effects on blame. (a) In Study 2 participants rated how blameworthy they thought it would be if a person chose the more harmful option (i.e., the larger amount of money and shocks, highlighted in red) on a continuous scale ranging from 0 (extremely praiseworthy) to 100 (extremely blameworthy). (b) Estimated blame judgments from a linear mixed-effects model as a function of money and shocks. Blame for accepting dirty money is sensitive to the destination of the money. Dashed diagonal lines indicate mix of money and shocks that are neither praiseworthy nor blameworthy.
Source and destination effects on moral decision making. (a) Proportion of harmful choices made as a function of the source (dirty/clean) and destination (profit/charity) of the money. (b) In line with Study 1 (Fig. 2c) the weight on money was significantly lower when considering dirty relative to clean money for profit. (c) The weight on shocks was significantly lower when considering dirty relative to clean money for charity. (d) Scatterplot showing out-of-sample correlation between differences in blame judgments (Profit-Charity) in Study 2 (horizontal axis) and the estimated differences in value associated with choosing the more harmful option (Profit-Charity) in Study 3 (vertical axis). Each dot represents a possible combination of money and shocks offers. Dots are color coded according to the highest/lowest shock offers. Error bars represent standard error of the mean.
A computational account of how individuals resolve the dilemma of dirty money
  • Article
  • Full-text available

November 2022

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114 Reads

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6 Citations

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Elisa van der Plas

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Felix Heise

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[...]

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M. J. Crockett

Money can be tainted when it is associated with direct or indirect harm to others. Deciding whether to accept “dirty money” poses a dilemma because money can be used to help others, but accepting dirty money has moral costs. How people resolve the dilemma of dirty money remains unknown. One theory casts the dilemma as a valuation conflict that can be resolved by integrating the costs and benefits of accepting dirty money. Here, we use behavioral experiments and computational modeling to test the valuation conflict account and unveil the cognitive computations employed when deciding whether to accept or reject morally tainted cash. In Study 1, British participants decided whether to accept “dirty” money obtained by inflicting electric shocks on another person (versus “clean” money obtained by shocking oneself). Computational models showed that the source of the money (dirty versus clean) impacted decisions by shifting the relative valuation of the money’s positive and negative attributes, rather than imposing a uniform bias on decision-making. Studies 2 and 3 replicate this finding and show that participants were more willing to accept dirty money when the money was directed towards a good cause, and observers judged such decisions to be more praiseworthy than accepting dirty money for one’s own profit. Our findings suggest that dirty money can be psychologically “laundered” through charitable activities and have implications for understanding and preventing the social norms that can justify corrupt behavior.

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Resolving the dilemma of dirty money: a computational account

July 2022

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29 Reads

·

2 Citations

Money can be tainted when it is associated with direct or indirect harm to others. Deciding whether to accept “dirty money” poses a dilemma because money can be used to help others, but accepting dirty money has moral costs. How people resolve the dilemma of dirty money remains unknown. One theory casts the dilemma as a valuation conflict that can be resolved by integrating the costs and benefits of accepting dirty money. Here, we use behavioral experiments and computational modeling to test the valuation conflict account and unveil the cognitive computations employed when deciding whether to accept or reject morally tainted cash. In Study 1, British participants decided whether to accept “dirty” money obtained by inflicting electric shocks on another person (versus “clean” money obtained by shocking oneself). Computational models showed that the source of the money (dirty versus clean) impacted decisions by shifting the relative valuation of the money’s positive and negative attributes, rather than imposing a uniform bias on decision-making. Studies 2 and 3 replicate this finding and show that participants were more willing to accept dirty money when the money was directed towards a good cause, and observers judged such decisions to be more praiseworthy than accepting dirty money for one’s own profit. Our findings suggest that dirty money can be psychologically “laundered” through charitable activities and have implications for understanding and preventing the social norms that can justify corrupt behavior.

Citations (2)


... Meanwhile, developments in drift diffusion modeling have afforded a clearer understanding of the cognitive processes that facilitate decisionmaking on basic perceptual tasks evoking response competition. In this work, we brought together these parallel lines of research, and contributed to ongoing efforts to apply drift diffusion modeling to higher-order reasoning tasks (Cohen & Ahn, 2016;Yu, Siegel, Clithero, & Crockett, 2021;Siegel, van der Plas, Heise, Clithero, & Crockett, 2022;Engelmann & Hannikainen, 2024). ...

Reference:

Understanding rule enforcement using drift diffusion models
A computational account of how individuals resolve the dilemma of dirty money

... Most applications of drift diffusion models have been in psychophysics, and only few in higher order reasoning like moral judgment (but see Cohen & Ahn, 2016;Siegel et al., 2022;Yu et al., 2021). Therefore, there are no clear benchmarks as to how the model's parameters are affected by moral content, and we regard our analysis as exploratory. ...

Resolving the dilemma of dirty money: a computational account
  • Citing Preprint
  • July 2022