Whether you're an employee or manager, cognitive biases, like the FAE, can play a role in how you interact with others in the workplace and how you make key business decisions. It's clear to see how the fundamental attribution error (FAE) can impact your personal life, but it's important to recognize the influence it can have on your work, as well. Similar to confirmation and overconfidence biases, its impact on business and life can be reduced by taking several measures. While you have at least some idea of your character, motivations, and situational factors that affect your day-to-day, you rarely know everything that's going on with someone else. The fundamental attribution error exists because of how people perceive the world. In other words, you tend to cut yourself a break while holding others 100 percent accountable for their actions.įor instance, if you've ever chastised a "lazy employee" for being late to a meeting and then proceeded to make an excuse for being late yourself that same day, you've made the fundamental attribution error. The fundamental attribution error refers to an individual's tendency to attribute another's actions to their character or personality, while attributing their behavior to external situational factors outside of their control. What Is the Fundamental Attribution Error? In the world of business, understanding these biases and becoming aware of the ways that they influence your behavior is vital to becoming a better manager. But the most important, and troubling, error that professionals tend to make in their thinking may be the fundamental attribution error.Ĭognitive biases such as these often shape how an individual interacts with the world around them. Many cognitive biases affect humans and their everyday actions, like confirmation bias and overconfidence. If you walk into the Psychology section of Barnes of Noble today or browse Amazon for "decision-making," you're sure to see a library of books about how irrational humans can be. There's been a lot written about cognitive biases in the last decade.
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