Retrieval-constrained valuation: Toward prediction of open-ended decisions

Zhihao Z., Shichun Wang, et al.

PNAS May 2021, 118 (20) e2022685118

DOI: 10.1073/pnas.2022685118

Abstract

Real-world decisions are often open ended, with goals, choice options, or evaluation criteria conceived by decision-makers themselves. Critically, the quality of decisions may heavily rely on the generation of options, as failure to generate promising options limits, or even eliminates, the opportunity for choosing them. This core aspect of problem structuring, however, is largely absent from classical models of decision-making, thereby restricting their predictive scope. Here, we take a step toward addressing this issue by developing a neurally inspired cognitive model of a class of ill-structured decisions in which choice options must be self-generated. Specifically, using a model in which semantic memory retrieval is assumed to constrain the set of options available during valuation, we generate highly accurate out-of-sample predictions of choices across multiple categories of goods. Our model significantly and substantially outperforms models that only account for valuation or retrieval in isolation or those that make alternative mechanistic assumptions regarding their interaction. Furthermore, using neuroimaging, we confirm our core assumption regarding the engagement of, and interaction between, semantic memory retrieval and valuation processes. Together, these results provide a neurally grounded and mechanistic account of decisions with self-generated options, representing a step toward unraveling cognitive mechanisms underlying adaptive decision-making in the real world.

Significance

Life is not a multiple-choice test: Many real-world decisions leave goals, choice options, or evaluation criteria to be determined by decision-makers themselves. However, a mechanistic understanding of how such problem structuring processes influence choice has largely eluded standard models of decision-making. By developing a neurally grounded cognitive model that integrates semantic knowledge retrieval and valuation processes, we offer a computational framework providing strikingly accurate out-of-sample predictions of choices with self-generated options. This framework generates psychological insights into the nature and force of memory retrieval’s substantial influence on choice behavior. Together, these findings represent a step toward predicting complex, ill-structured decisions in the real world, opening up new approaches that may broaden the scope of formal models of decision-making.

The research is here.

Harm to others outweighs harm to self in moral decision making

Molly J. Crockett, Zeb Kurth-Nelson, Jenifer Z. Siegel, Peter Dayand, and Raymond J. Dolan
PNAS 2014 ; published ahead of print November 17, 2014, doi:10.1073/pnas.1408988111

Abstract

Concern for the suffering of others is central to moral decision making. How humans evaluate others’ suffering, relative to their own suffering, is unknown. We investigated this question by inviting subjects to trade off profits for themselves against pain experienced either by themselves or an anonymous other person. Subjects made choices between different amounts of money and different numbers of painful electric shocks. We independently varied the recipient of the shocks (self vs. other) and whether the choice involved paying to decrease pain or profiting by increasing pain. We built computational models to quantify the relative values subjects ascribed to pain for themselves and others in this setting. In two studies we show that most people valued others’ pain more than their own pain. This was evident in a willingness to pay more to reduce others’ pain than their own and a requirement for more compensation to increase others’ pain relative to their own. This ‟hyperaltruistic” valuation of others’ pain was linked to slower responding when making decisions that affected others, consistent with an engagement of deliberative processes in moral decision making. Subclinical psychopathic traits correlated negatively with aversion to pain for both self and others, in line with reports of aversive processing deficits in psychopathy. Our results provide evidence for a circumstance in which people care more for others than themselves. Determining the precise boundaries of this surprisingly prosocial disposition has implications for understanding human moral decision making and its disturbance in antisocial behavior.

Significance

Concern for the welfare of others is a key component of moral decision making and is disturbed in antisocial and criminal behavior. However, little is known about how people evaluate the costs of others’ suffering. Past studies have examined people’s judgments in hypothetical scenarios, but there is evidence that hypothetical judgments cannot accurately predict actual behavior.  Here we addressed this issue by measuring how much money people will sacrifice to reduce the number of painful electric shocks delivered to either themselves or an anonymous stranger. Surprisingly, most people sacrifice more money to reduce a stranger’s pain than their own pain. This finding may help us better understand how people resolve moral dilemmas that commonly arise in medical, legal, and political decision making.

The entire article is here.

Harm to others outweighs harm to self in moral decision making

By Molly J. Crockett, Zeb Kurth-Nelson, Jenifer Z. Siegel, Peter Dayan, and Raymond J. Dolan
PNAS 2014 ; published ahead of print November 17, 2014, doi:10.1073/pnas.1408988111

Abstract

Concern for the suffering of others is central to moral decision making. How humans evaluate others’ suffering, relative to their own suffering, is unknown. We investigated this question by inviting subjects to trade off profits for themselves against pain experienced either by themselves or an anonymous other person. Subjects made choices between different amounts of money and different numbers of painful electric shocks. We independently varied the recipient of the shocks (self vs. other) and whether the choice involved paying to decrease pain or profiting by increasing pain. We built computational models to quantify the relative values subjects ascribed to pain for themselves and others in this setting. In two studies we show that most people valued others’ pain more than their own pain. This was evident in a willingness to pay more to reduce others’ pain than their own and a requirement for more compensation to increase others’ pain relative to their own. This ‟hyperaltruistic” valuation of others’ pain was linked to slower responding when making decisions that affected others, consistent with an engagement of deliberative processes in moral decision making. Subclinical psychopathic traits correlated negatively with aversion to pain for both self and others, in line with reports of aversive processing deficits in psychopathy. Our results provide evidence for a circumstance in which people care more for others than themselves. Determining the precise boundaries of this surprisingly prosocial disposition has implications for understanding human moral decision making and its disturbance in antisocial behavior.


Significance

Concern for the welfare of others is a key component of moral decision making and is disturbed in antisocial and criminal behavior. However, little is known about how people evaluate the costs of others’ suffering. Past studies have examined people’s judgments in hypothetical scenarios, but there is evidence that hypothetical judgments cannot accurately predict actual behavior. Here we addressed this issue by measuring how much money people will sacrifice to reduce the number of painful electric shocks delivered to either themselves or an anonymous stranger. Surprisingly, most people sacrifice more money to reduce a stranger’s pain than their own pain. This finding may help us better understand how people resolve moral dilemmas that commonly arise in medical, legal, and political decision making.

The entire article is here.