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Imperial Records
PSYCHOLOGY
psychology
kahneman
biases
decision-making
logic

Cognitive Biases: The Bugs in Our Brain

Why do smart people make stupid decisions? The answer lies in 'Cognitive Biases'—the mental shortcuts our brains use to save energy. Explore the errors that shape your reality.

OIYO Research Institute• 12 min read

Abstract

The human brain is not a logic machine; it is a survival machine. To process millions of bits of data per second, it relies on

Heuristics

. Often these shortcuts work, but frequently they lead to systematic errors known as Cognitive Biases. This whitepaper explores the "Bugs" in our operating system identified by Nobel laureate Daniel Kahneman.

1. Genesis: System 1 vs. System 2

In Thinking, Fast and Slow, Kahneman distinguishes two modes of thought:

  • System 1 (Fast): Automatic, emotional, unconscious. (e.g., Driving a car on an empty road, recognizing a face).
  • System 2 (Slow): Effortful, logical, conscious. (e.g., Parallel parking, calculating 17 x 24).

Biases occur because System 1 is in charge 95% of the time. It jumps to conclusions to save System 2 from doing the hard work.

2. The Big Bugs (Major Biases)

① Confirmation Bias

  • The Bug: We notice data that supports our beliefs and ignore data that contradicts them.
  • Example: You believe "Left-handed people are creative." Whenever you meet a creative lefty, you say "Aha!" When you meet an uncreative lefty, you forget it instantly.

② Sunk Cost Fallacy

  • The Bug: We continue a losing course of action because of what we have already invested, rather than the future value.
  • Example: Staying in a bad relationship or finishing a boring movie because "I've already put in two years/two hours."
  • Logic: The past investment is "sunk" (gone). The only question is: "Is the future worth it?"

③ Anchoring Bias

  • The Bug: We rely too heavily on the first piece of information offered (the "anchor").
  • Example: A shirt is marked "$100" but on sale for "$50." You feel it's a steal. If it was just marked "$50," you might think it's expensive. The initial $100 anchored your perception of value.

④ Fundamental Attribution Error

  • The Bug: We judge others by their character, but ourselves by our circumstances.
  • Example: If someone cuts you off in traffic, they are a "jerk" (Character). If you cut someone off, it's because "I'm late for a meeting" (Circumstance).

3. The Dunning-Kruger Effect

Perhaps the most dangerous bias: Incompetent people overestimate their competence. Because they lack the knowledge to know how much they don't know, they feel confident. Conversely, experts often underestimate their competence because they assume what is easy for them is easy for everyone.

Scholarly Insight

Naive Realism: The belief that "I see the world as it is, and those who disagree are biased." The moment you think you are unbiased, you are exhibiting Naive Realism.

4. Modern Relevance: The Algorithms of Anger

Social media algorithms weaponize our biases. They feed Confirmation Bias by showing us only what we agree with, creating echo chambers. They exploit Negativity Bias (we pay more attention to bad news) to keep us scrolling. Understanding these bugs is a form of digital self-defense.

5. Conclusion: Debugging the Mind

You cannot remove your biases; they are part of your biology. But you can become aware of them. By pausing to engage System 2—"Am I only reading this because it makes me feel right?"—you can overwrite the faulty code and make decisions based on reality, not instinct.


References

Daniel Kahneman (2011)Thinking, Fast and Slow
Tversky & Kahneman (1974)Judgment under Uncertainty: Heuristics and Biases
Dan Ariely (2008)Predictably Irrational

FAQ

Q: Are biases always bad? A: No. System 1 is fast for a reason. If a lion jumps out, you don't want System 2 to calculate the trajectory. You want the fear bias to make you run. Biases are speed-accuracy trade-offs.

Q: How can I avoid Sunk Cost? A: Ask yourself: "If I hadn't invested anything yet, would I start this project today?" If the answer is no, quit.

End of Records

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