Welcome to the Nexus of Ethics, Psychology, Morality, Philosophy and Health Care

Welcome to the nexus of ethics, psychology, morality, technology, health care, and philosophy
Showing posts with label Human Behaviors. Show all posts
Showing posts with label Human Behaviors. Show all posts

Thursday, August 3, 2023

The persistence of cognitive biases in financial decisions across economic groups

Ruggeri, K., Ashcroft-Jones, S. et al.
Sci Rep 13, 10329 (2023).

Abstract
While economic inequality continues to rise within countries, efforts to address it have been largely ineffective, particularly those involving behavioral approaches. It is often implied but not tested that choice patterns among low-income individuals may be a factor impeding behavioral interventions aimed at improving upward economic mobility. To test this, we assessed rates of ten cognitive biases across nearly 5000 participants from 27 countries. Our analyses were primarily focused on 1458 individuals that were either low-income adults or individuals who grew up in disadvantaged households but had above-average financial well-being as adults, known as positive deviants. Using discrete and complex models, we find evidence of no differences within or between groups or countries. We therefore conclude that choices impeded by cognitive biases alone cannot explain why some individuals do not experience upward economic mobility. Policies must combine both behavioral and structural interventions to improve financial well-being across populations.

From the Discussion section

This study aimed to determine if rates of cognitive biases were different between positive deviants and low-income adults in a way that might explain some elements of what impedes or facilitates upward economic mobility. We anticipated finding small-to-moderate effects between groups indicating positive deviants were less prone to biases involving risk and uncertainty in financial choices. However, across a sample of nearly 5000 participants from 27 countries, of which 1458 were low-income or positive deviants, we find no evidence of any difference in the rates of cognitive biases—minor or otherwise—and no systematic variability to indicate patterns vary globally.

In sum, we find clear evidence that resistance to cognitive biases is not a factor contributing to or impeding upward economic mobility in our sample. Taken along with related work showing that temporal choice anomalies are tied more to economic environment rather than individual financial circumstances, our findings are (unintentionally) a major validation of arguments (especially that of Bertrand, Mullainathan, and Shafir) stating that poorer individuals are not uniquely prone to cognitive biases that alone explain protracted poverty. It also supports arguments that scarcity is a greater driver of decisions, as individuals of different income groups are equally influenced by biases and context-driven cues.

What makes these findings particularly reliable is that multiple possible approaches to analyses had to be considered while working with the data, some of which were considered into extreme detail before selecting the optimal approach. As our measures were effective at eliciting biases on a scale to be expected based on existing research, and as there were relatively low correlations between individual biases (e.g., observing loss aversion in one participant is not necessarily a strong predictor of also observing any other specific bias), we conclude that there is no evidence from our sample to support that biases are directly associated with potentially harming optimal choices uniquely amongst low-income individuals.

Conclusion

We sought to determine if individuals that had overcome low-income childhoods showed significantly different rates of cognitive biases from individuals that remained low-income as adults. We comprehensively reject our initial hypotheses and conclude that outcomes are not tied—at least not exclusively or potentially even meaningfully—to resistance to cognitive biases. Our research does not reject the notion that individual behavior and decision-making may directly relate to upward economic mobility. Instead, we narrowly conclude that biased decision-making does not alone explain a significant proportion of population-level economic inequality. Thus, any attempts to reduce economic inequality must involve both behavioral and structural aspects. Otherwise, similar decisions between disadvantaged individuals may not lead to similar outcomes. Where combined effectively, it will be possible to assess if genuine impact has been made on the financial well-being of individuals and populations.

Sunday, November 21, 2021

Moral labels increase cooperation and costly punishment in a Prisoner’s Dilemma game with punishment option

Mieth, L., Buchner, A. & Bell, R.
Sci Rep 11, 10221 (2021). 
https://doi.org/10.1038/s41598-021-89675-6

Abstract

To determine the role of moral norms in cooperation and punishment, we examined the effects of a moral-framing manipulation in a Prisoner’s Dilemma game with a costly punishment option. In each round of the game, participants decided whether to cooperate or to defect. The Prisoner’s Dilemma game was identical for all participants with the exception that the behavioral options were paired with moral labels (“I cooperate” and “I cheat”) in the moral-framing condition and with neutral labels (“A” and “B”) in the neutral-framing condition. After each round of the Prisoner’s Dilemma game, participants had the opportunity to invest some of their money to punish their partners. In two experiments, moral framing increased moral and hypocritical punishment: participants were more likely to punish partners for defection when moral labels were used than when neutral labels were used. When the participants’ cooperation was enforced by their partners’ moral punishment, moral framing did not only increase moral and hypocritical punishment but also cooperation. The results suggest that moral framing activates a cooperative norm that specifically increases moral and hypocritical punishment. Furthermore, the experience of moral punishment by the partners may increase the importance of social norms for cooperation, which may explain why moral framing effects on cooperation were found only when participants were subject to moral punishment.

General discussion

In human social life, a large variety of behaviors are regulated by social norms that set standards on how individuals should behave. One of these norms is the norm of cooperation. In many situations, people are expected to set aside their egoistic interests to achieve the collective best outcome. Within economic research, cooperation is often studied in social dilemma games. In these games, the complexities of human social interactions are reduced to their incentive structures. However, human behavior is not only determined by monetary incentives. There are many other important determinants of behavior among which social norms are especially powerful. The participants’ decisions in social dilemma situations are thus affected by their interpretation of whether a certain behavior is socially appropriate or inappropriate. Moral labels can help to reduce the ambiguity of the social dilemma game by creating associations to real-life cooperation norms. Thereby, the moral framing may support a moral interpretation of the social dilemma situation, resulting in the moral rejection of egoistic behaviors. Often, social norms are enforced by punishment. It has been argued “that the maintenance of social norms typically requires a punishment threat, as there are almost always some individuals whose self-interest tempts them to violate the norm” [p. 185]. 

Tuesday, November 16, 2021

Decision Prioritization and Causal Reasoning in Decision Hierarchies

Zylberberg, A. (2021, September 6). 
https://doi.org/10.31234/osf.io/agt5s

Abstract

From cooking a meal to finding a route to a destination, many real life decisions can be decomposed into a hierarchy of sub-decisions. In a hierarchy, choosing which decision to think about requires planning over a potentially vast space of possible decision sequences. To gain insight into how people decide what to decide on, we studied a novel task that combines perceptual decision making, active sensing and hierarchical and counterfactual reasoning. Human participants had to find a target hidden at the lowest level of a decision tree. They could solicit information from the different nodes of the decision tree to gather noisy evidence about the target's location. Feedback was given only after errors at the leaf nodes and provided ambiguous evidence about the cause of the error. Despite the complexity of task (with 10 to 7th power latent states) participants were able to plan efficiently in the task. A computational model of this process identified a small number of heuristics of low computational complexity that accounted for human behavior. These heuristics include making categorical decisions at the branching points of the decision tree rather than carrying forward entire probability distributions, discarding sensory evidence deemed unreliable to make a choice, and using choice confidence to infer the cause of the error after an initial plan failed. Plans based on probabilistic inference or myopic sampling norms could not capture participants' behavior. Our results show that it is possible to identify hallmarks of heuristic planning with sensing in human behavior and that the use of tasks of intermediate complexity helps identify the rules underlying human ability to reason over decision hierarchies.

Discussion

Adaptive behavior requires making accurate decisions, but also knowing what decisions are worth making. To study how people decide what to decide on, we investigated a novel task in which people had to find a target, hidden at the lowest level of a decision tree, by gathering stochastic information from the internal nodes of the decision tree. Our central finding is that a small number of heuristic rules explain the participant’s behavior in this complex decision-making task. The study extends the perceptual decision framework to more complex decisions that comprise a hierarchy of sub-decisions of varying levels of difficulty, and where the decision maker has to actively decide which decision to address at any given time.  

Our task can be conceived as a sequence of binary decisions, or as one decision with eight alternatives.  Participants’ behavior supports the former interpretation.  Participants often performed multiple queries on the same node before descending levels, and they rarely made a transition from an internal node to a higher-level one before reaching a leaf node.  This indicates that participants made categorical decisions about the direction of motion at the visited nodes before they decided to descend levels. This bias toward resolving uncertainty locally was not observed in an approximately optimal policy (Fig. 8), and thus may reflect more general cognitive constraints that limit participants’ performance in our task (Markant et al., 2016). A strong candidate is the limited capacity of working memory (Miller, 1956). By reaching a categorical decision at each internal node, participants avoid the need to operate with full probability distributions over all task-relevant variables, favoring instead a strategy in which only the confidence about the motion choices is carried forward to inform future choices (Zylberberg et al., 2011).