Nandhini Parthasarathy ’26

Emotions are often dismissed as irrational forces that undermine decision-making. However, emerging research suggests that emotions can contribute to accurate decisions when approached with a structured framework. This article explores the intersection of cognitive science and decision-making theories, examining the limitations of traditional rational models such as Expected Value Theory (EVT) and Expected Utility Theory (EUT). It introduces Prospect Theory as a partial explanation for emotional influences and highlights the role of affective forecasting and surrogation in refining emotional accuracy. Empirical studies on revenge behaviors and prediction errors demonstrate the nuanced relationship between emotion and rationality, underscoring the potential for emotional decisions to align with scientific models of accuracy.

Traditional decision-making models prioritize logic and rationality, often framing emotions as sources of error. Expected Value Theory (EVT) and Expected Utility Theory (EUT) epitomize this perspective, relying on numerical calculations to determine optimal choices. Yet, these models struggle to explain the complexity of human behavior, especially under conditions of risk and uncertainty. Emotional responses such as dread and regret frequently deviate from the mathematically optimal predictions of EVT and EUT.

This disconnect has spurred the development of alternative models like Prospect Theory, which incorporates psychological phenomena such as loss aversion. However, even Prospect Theory fails to account for the broader spectrum of emotions influencing everyday decisions. This paper reviews findings from cognitive science to argue that emotions, while seemingly irrational, can lead to accurate decision-making when structured frameworks such as affective forecasting and surrogation are employed.

Rational decision-making theories assume that individuals evaluate probabilities and outcomes objectively. Expected Value Theory calculates decisions based on potential gains, while Expected Utility Theory adjusts these calculations to incorporate subjective preferences. However, when decisions involve emotional stakes—such as fear of failure or anticipated happiness—these models falter.

Prospect Theory, introduced by Kahneman and Tversky, provides a more nuanced framework. It recognizes that individuals are disproportionately sensitive to losses compared to gains, leading to irrational behaviors like risk aversion. Nonetheless, Prospect Theory primarily addresses financial and risk-based decisions, leaving out the impact of emotions like revenge or empathy.

One key limitation of rational theories is their inability to account for affective forecasting—the prediction of future emotional states. Research by Daniel Gilbert highlights how individuals consistently overestimate the intensity and duration of their emotional responses to future events. For example, people may expect profound happiness from achieving a goal or deep regret from a perceived failure, only to experience muted emotions once the event occurs. This systematic bias complicates decision-making, particularly in contexts where hypothetical emotions drive choices.

Gilbert’s work on surrogation provides a potential solution. By relying on the experiences of others, individuals can mitigate errors in affective forecasting. Empirical studies on speed dating revealed that participants who used surrogate information—feedback from others who had experienced similar situations—made more accurate predictions about their emotional reactions compared to those relying on personal judgment.

Daniel Ariely’s experiments in the Trust Game demonstrate how emotions like revenge can override rationality. In this simulation, participants were given the option to punish others for perceived unfairness at a personal cost. Despite the financial irrationality of revenge, many participants chose to incur losses to achieve emotional satisfaction. While this behavior highlights the limitations of rational theories like EVT, it also underscores the profound role emotions play in decision-making.

The findings from Ariely and Gilbert suggest that rational decision-making models, while valuable, are insufficient to explain the full range of human behavior. For instance, EVT and EUT fail to capture the emotional weight of decisions involving moral judgment or social interaction. Even Prospect Theory, with its focus on risk and loss aversion, does not account for hypothetical emotions or their influence on current behavior.

The studies reviewed in this article reveal two key insights:

  1. Affective forecasting is inherently biased. People are poor predictors of their future emotional states, leading to suboptimal decisions in both personal and professional contexts.
  2. Surrogation improves decision accuracy. By leveraging the emotional experiences of others, individuals can reduce affective forecasting errors by up to 50%, as demonstrated in Gilbert’s speed dating studies.

While emotions may seem antithetical to rationality, they serve as critical heuristics in complex decision-making scenarios. For example, feelings of trust or distrust can guide social decisions more effectively than purely numerical evaluations. Similarly, the emotional satisfaction derived from revenge, while irrational from a financial perspective, aligns with evolutionary theories of social cooperation and justice.

Emotions are often maligned as irrational forces that derail decision-making. However, the evidence reviewed here suggests that emotions can enhance decision accuracy when guided by frameworks like surrogation. By acknowledging the biases of affective forecasting and incorporating the experiences of others, individuals can harness the power of emotions while minimizing their pitfalls.

Future research should explore the integration of emotional insights into computational decision-making models, bridging the gap between cognitive science and artificial intelligence. Such interdisciplinary approaches could redefine our understanding of rationality, positioning emotions as allies rather than adversaries in the decision-making process.

Edited by Namitha Alluri ’25

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