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Thinking, Problem Solving & Decision Making

You’ll be able to

Concepts, algorithms, and heuristics

We organize knowledge into concepts — mental categories — often anchored by a prototype, the best example of a category (a robin is a prototypical bird). To solve problems we use two broad strategies. An algorithm is a step-by-step procedure that guarantees a solution but can be slow (trying every letter combination to unscramble a word). A heuristic is a mental shortcut that is faster but error-prone (starting with likely letter pairs). We also get flashes of insight — sudden realization of a solution, the "aha!" moment studied by the Gestalt psychologists.

Heuristics that mislead: Kahneman and Tversky

Daniel Kahneman and Amos Tversky catalogued shortcuts that systematically bias judgment. The availability heuristic judges likelihood by how easily examples come to mind — vivid plane crashes make flying feel more dangerous than driving. The representativeness heuristic judges probability by resemblance to a prototype, ignoring base rates (assuming a quiet reader is "a librarian" rather than the far more numerous "salesperson"). These fast judgments usually serve us well but predictably fail in ways the exam loves to test.

Obstacles: fixation, framing, and belief

Several forces block good thinking. Fixation is the inability to see a problem from a fresh angle; mental set is the tendency to approach problems the way that worked before, and functional fixedness is seeing objects only in their usual use (not realizing a coin can be a screwdriver). Confirmation bias leads us to seek evidence that supports our beliefs and ignore what contradicts them. Framing shows that how a choice is worded sways decisions: "90% survival" and "10% mortality" describe the same odds, yet people choose differently. Belief perseverance keeps beliefs alive even after the evidence is discredited.

Worked example

After watching several news stories about shark attacks, a vacationer refuses to swim in the ocean, convinced attacks are common, even though the statistical risk is minuscule. Identify the cognitive bias and explain the reasoning error.

  1. 1.Identify what drives the fear: the vivid, memorable news stories are easy to recall.
  2. 2.Match to the heuristic: judging how likely something is by how easily examples come to mind is the availability heuristic.
  3. 3.Explain the error: mental availability (dramatic, well-publicized attacks) is mistaken for actual frequency, so a rare event feels common.
  4. 4.Note the correction: the real base rate of shark attacks is extremely low, but the emotionally vivid examples override the statistics.
Answer: This is the availability heuristic: because dramatic shark-attack stories are so easy to recall, the vacationer overestimates their frequency. Vivid, memorable events feel more probable than they are, overriding the tiny actual base rate.
Checkpoint

A researcher tries to open a locked box and never thinks to use the metal ruler on the desk as a pry bar, because she sees the ruler only as a measuring tool. This difficulty best illustrates:

Watch out

Keep the two heuristics distinct: availability = judging by how easily examples come to mind (vividness/frequency), representativeness = judging by how well something matches a prototype (ignoring base rates). Ask whether the clue is "easy to recall" or "fits a stereotype."

Checkpoint

A surgeon tells patients a procedure has a "90% survival rate," and far more agree to it than when a colleague describes the identical procedure as having a "10% death rate." This difference is best explained by:

On the exam

On FRQs, tie each bias to a one-line trigger: availability = vivid/easily recalled examples, representativeness = matches a stereotype, confirmation bias = only seeking supporting evidence, framing = same facts worded differently. Naming the trigger nails the definition point.

Answer the 2 checkpoints as you read.

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