Heuristic Bias

Heuristic bias refers to the tendency of people to rely on mental shortcuts or simplified strategies—known as heuristics—when making judgments or decisions under complexity or uncertainty. These heuristics serve as cognitive shortcuts that allow for efficient information processing and conserve mental effort. However, overreliance on or misapplication of heuristics can lead to systematic deviations in thinking, known as biases. Unlike random errors, these biases are predictable and follow consistent patterns. Common types of heuristic biases include availability bias, representativeness bias, and anchoring effects. They appear widely in domains such as investment decisions, public policy, and everyday judgment, influencing how individuals assess probabilities, values, and risks.

1. Availability Bias in Investment Decisions: An investor, when selecting stocks, tends to buy shares of companies that have been frequently covered in recent media and have shown strong price performance—even if their fundamentals are weak. Because recent and vivid information is more easily recalled, the investor overestimates the investment potential and future prospects of these stocks, overlooking comprehensive market analysis and risk evaluation.

2. Representativeness Bias in Job Interviews: During a job interview, a hiring manager interviews a candidate who graduated from a prestigious university and lists several successful projects on their resume. The interviewer assumes the candidate must be highly competent and suitable for the role, giving them a high score, while ignoring red flags such as poor communication skills and lack of teamwork experience observed during the interview. The interviewer has matched the candidate to the stereotype of a "top-tier graduate," resulting in representativeness bias.

1. Heuristics enable fast decision-making but may lead to systematic biases.
2. Biases are not random; they are predictable patterns of flawed judgment.
3. Common heuristic biases include availability, representativeness, and anchoring effects.
4. Understanding heuristic biases helps improve decision quality and avoid intuitive errors.
5. In critical decisions, one should remain alert to heuristic biases and conduct more thorough, comprehensive analyses.