Rational simplification and rigidity in human planning

Ho, M. K., Cohen, J. D., & Griffiths, T.

(2023, March 30). PsyArXiv

https://doi.org/10.31234/osf.io/aqxws

Abstract

Planning underpins the impressive flexibility of goal-directed behavior. However, even when planning, people can display surprising rigidity in how they think about problems (e.g., “functional fixedness”) that lead them astray. How can our capacity for behavioral flexibility be reconciled with our susceptibility to conceptual inflexibility? We propose that these tendencies reflect avoidance of two cognitive costs: the cost of representing task details and the cost of switching between families of representations. To test this hypothesis, we developed a novel paradigm that affords participants opportunities to choose different families of simplified representations to plan. In two pre-registered online studies (N = 377; N = 294), we found that participants’ optimal behavior, suboptimal behavior, and reaction time are explained by a computational model that formalizes people’s avoidance of representational complexity and switching. These results demonstrate how the selection of simplified, rigid representations leads to the otherwise puzzling combination of flexibility and inflexibility observed in problem solving.

General Discussion

Here, we evaluated the hypothesis that functional fixedness reflects the avoidance of complexity and switching costs during planning. To do so, we developed a novel paradigm in which participants navigated mazes that could be represented simply as blocks or more complexly as blocks and notches. Experiments revealed that people simplify problems(for instance, by adopting a blocks-only construal strategy if navigating through notches was unnecessary) and that they persist in these strategies (for instance, continuing to ignore notches even when attending to a notch would lead to a better solution).  Additionally, our computational analyses using the value-guided construal framework (Ho et al., 2022)confirmed that the avoidance of complexity and  switching costs explains observed patterns of optimal behavior, suboptimal behavior, and reaction times under different experimental manipulations. Overall, these results support our proposal and  help  clarify  the  computational  principles  that  underlie functional fixedness.

A pdf is here.

Summary:

The authors argue that people often simplify problems in order to make them more manageable, but this can lead to rigidity and suboptimal solutions.

The authors conclude that rational simplification is a common cognitive mechanism that can lead to both flexibility and rigidity in planning. They argue that the model provides a useful framework for understanding how people simplify problems and make decisions.

Here are some of the key takeaways from the article:

• People often simplify problems in order to make them more manageable.
• This can lead to rigidity and suboptimal solutions.
• The tendency to simplify problems is a cognitive mechanism that can be explained by the limited capacity for representing task details.
• The model provides a useful framework for understanding how people simplify problems and make decisions.

Produced and counterfactual effort contribute to responsibility attributions in collaborative tasks

Xiang, Y., Landy, J., et al. (2023, March 8). 

PsyArXiv

https://doi.org/10.31234/osf.io/jc3hk

Abstract

How do people judge responsibility in collaborative tasks? Past work has proposed a number of metrics that people may use to attribute blame and credit to others, such as effort, competence, and force. Some theories consider only the produced effort or force (individuals are more responsible if they produce more effort or force), whereas others consider counterfactuals (individuals are more responsible if some alternative behavior on their or their collaborator's part could have altered the outcome). Across four experiments (N = 717), we found that participants’ judgments are best described by a model that considers both produced and counterfactual effort. This finding generalized to an independent validation data set (N = 99). Our results thus support a dual-factor theory of responsibility attribution in collaborative tasks.

General discussion

Responsibility for the outcomes of collaborations is often distributed unevenly. For example, the lead author on a project may get the bulk of the credit for a scientific discovery, the head of a company may  shoulder the blame for a failed product, and the lazier of two friends may get the greater share of blame  for failing to lift a couch.  However, past work has provided conflicting accounts of the computations that drive responsibility attributions in collaborative tasks.  Here, we compared each of these accounts against human responsibility attributions in a simple collaborative task where two agents attempted to lift a box together.  We contrasted seven models that predict responsibility judgments based on metrics proposed in past work, comprising three production-style models (Force, Strength, Effort), three counterfactual-style models (Focal-agent-only, Non-focal-agent-only, Both-agent), and one Ensemble model that combines the best-fitting production- and counterfactual-style models.  Experiment 1a and Experiment 1b showed that theEffort model and the Both-agent counterfactual model capture the data best among the production-style models and the counterfactual-style models, respectively.  However, neither provided a fully adequate fit on their own.  We then showed that predictions derived from the average of these two models (i.e., the Ensemble model) outperform all other models, suggesting that responsibility judgments are likely a combination of production-style reasoning and counterfactual reasoning.  Further evidence came from analyses performed on individual participants, which revealed that he Ensemble model explained more participants’ data than any other model.  These findings were subsequently supported by Experiment 2a and Experiment 2b, which replicated the results when additional force information was shown to the participants, and by Experiment 3, which validated the model predictions with a broader range of stimuli.

The research is here.

Summary: Effort exerted by each member & counterfactual thinking play a crucial role in attributing responsibility for success or failure in collaborative tasks. This study suggests that higher effort leads to more responsibility for success, while lower effort leads to more responsibility for failure.

Norms Affect Prospective Causal Judgments

Henne, P., & others

(2019, December 30). 

https://doi.org/10.31219/osf.io/2nwb4

Abstract

People more frequently select norm-violating factors, relative to norm-conforming ones, as the cause of some outcome. Until recently, this abnormal-selection effect has been studied using retrospective vignette-based paradigms. We use a novel set of video stimuli to investigate this effect for prospective causal judgments—i.e., judgments about the cause of some future outcome. Four experiments show that people more frequently select norm-violating factors, relative to norm-conforming ones, as the cause of some future outcome. We show that the abnormal-selection effects are not primarily explained by the perception of agency (Experiment 4). We discuss these results in relation to recent efforts to model causal judgment.

From the Discussion

The results of these experiments have some important consequences for the study of causal cognition. While accounting for some of the limitations of past work on abnormal selection, we present strong evidence in support of modal explanations for abnormal-selection effects. Participants in our studies select norm-violating factors as causes for stimuli that reduce the presence of agential cues (Experiments 1-3), and increasing agency cues does not change this tendency (Experiment 4). Social explanations might account for abnormal-selection behavior in some contexts, but, in general, abnormal-selection behavior likely does not depend on perceived intentions of agents, assessments of blame, or other social concerns. Rather, abnormal-selection effects seem to reflect a more general causal reasoning process, not just processes related to social or moral cognition, that involves modal cognition.The modal explanations for abnormal selection effects predict the results that we present here; in non-social situations, abnormal-selection effects should occur, and they should occur for prospective causal judgments. Even if the social explanation can account for the results of Experiments 1-3, it does not predict the results of Experiment 4. In Experiment 4, we increased agency cues, and we saw an increase in perceived intentionality attributed to the objects in our stimuli. But we did not see a change in abnormal-selection behavior, as social explanations predict. While these results are not evidence that the social explanation is completely mistaken about causal-selection behavior, we have strong evidence that modal explanations account for these effects—even when agency cues are increased.

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Editor's note: This research is very important for psychologists, clinicians, and psychotherapists trying to understand and conceptualize their patient's behaviors and symptoms.  Studies show clinicians have poor inter-rater reliability to explain accurate the causes of behaviors and symptoms.  In this study, norm violations are more likely seen as causes, a bias for which we all need to understand.