Topic guide

When are choices biased, and what is the comparison standard?

Specify the information, goal and comparison rule before interpreting a response as a judgement bias.

For: Readers who want to evaluate claims about human irrationality.

Begin here

  1. MIT OpenCourseWare · Source-checked annotation

    Lecture 13: Thinking

    MIT OpenCourseWare Speaker not established foundation 1 hr 7 min

    The MIT session connects concrete puzzles to heuristics and framing, offering examples that can be reconstructed rather than merely labelled.

Calling a choice biased requires a comparison. Was relevant information ignored? Was a probability calculation mistaken? Did the person pursue a different goal from the one the observer assumed? These possibilities should be separated before an error label becomes an explanation of the person.

MIT’s thinking session is a useful start because its official outline links concrete problems to functional fixedness, heuristics, anchoring and framing. Reconstruct an example in your own words. Specify the information, available responses and criterion for success before asking which mental shortcut might explain an answer.

Noba’s judgement chapter sets out a proposed systematic decision procedure and contrasts it with examples of confidence, anchoring and framing. Use it to distinguish a normative proposal—how a decision should be made under specified goals—from a descriptive claim about what people tend to do. The two claims need different kinds of support.

The additional selections deliberately widen the standards of comparison. Conditional probability supplies a mathematical rule when the problem concerns evidence. Gendler’s utilitarianism lecture introduces one moral framework; disagreement with that framework is not, by itself, an arithmetic error. Her discussion of sampling bias also reminds us that a striking classroom example is not automatically a reliable estimate for a wider population.

For the exercise, vary the wording of a fictional problem while holding its stated outcomes fixed. A changed answer would motivate a question about framing. It would not immediately establish a universal effect, its size or its mechanism. Different participants may interpret the wording differently, and the task may leave important goals unstated.

This guide teaches a way to read claims about bias rather than a catalogue of labels to apply to other people. Its foundational lectures are historically situated. Continue with probability if you need a clearer formal standard, or with strategic interaction when the outcome depends on what another person chooses.

Build the connection

  1. Open Yale Courses · Source-checked annotation

    Lecture 4 - Parts of the Soul II

    Open Yale Courses Speaker not established foundation Duration unknown

    Compare arguments and sampling. Gendler brings sampling bias and dual-process accounts into the same introductory discussion.

  2. NPTEL — National Programme on Technology Enhanced Learning

    Heuristics and Framing Effects

    NPTEL — National Programme on Technology Enhanced Learning Speaker not established Level not established Duration unknown

    Focus on framing. A behavioural-economics lecture explicitly pairs heuristics with framing effects.

  3. MIT OpenCourseWare · Source-checked annotation

    Lecture 2: Conditioning and Bayes' Rule

    MIT OpenCourseWare John Tsitsiklis intermediate 51 min

    Specify a probability standard. Conditional probability provides a clear mathematical comparison when a task concerns evidence.

  4. Open Yale Courses · Source-checked annotation

    Lecture 12 - Utilitarianism and its Critiques

    Open Yale Courses Speaker not established foundation Duration unknown

    Distinguish a value judgement. The utilitarianism lecture illustrates that evaluating a choice can involve a moral criterion, not just a probability calculation.

  5. NPTEL — National Programme on Technology Enhanced Learning

    Bayesian Updating and Confirmation Bias

    NPTEL — National Programme on Technology Enhanced Learning Speaker not established Level not established Duration unknown

    Connect updating and bias. The named Bayesian-updating lecture gives a route into the behavioural-economics treatment.

Change a frame, hold the outcomes fixed

Take a fictional choice with two options. Write the information and goal, choose a comparison rule, then change only the wording. Explain what a changed answer would and would not demonstrate.

Exercise or methods at source ↗

Read alongside

Go into the full course →

Next step

Use the uncertainty path to establish a formal comparison before interpreting a response as mistaken.

Limits of this route

The foundational psychology and philosophy lectures are dated teaching material. Examples and definitions do not establish current effect sizes or universal mechanisms; the exercise illustrates a comparison, not a population result. Source checks establish scope and selection usefulness; they do not claim full-video viewing, human review or scientific validation.

Sources and editorial check · 2026-11-07

Individual publisher overviews for selected Yale/MIT material; ordered official NPTEL outlines and available course descriptions; the specifically identified supporting reading sections. Each source record states its inspection limit.

Checked by agent. This is not human peer review.

  1. Lecture 13: Thinking — official publisher material

    Retrieved 2026-11-07. Official Session Overview and lecture chapter headings, including the exact full-video link; not a full transcript or viewing.

  2. Lecture 4 - Parts of the Soul II — official publisher material

    Retrieved 2026-11-07. Official lecture Overview paragraph. Transcript is linked or included on the page but was not read in full; video not viewed.

  3. Principles of Behavioral Economics — official course outline

    Retrieved 2026-11-07. Official ordered lecture outline and course attribution inspected. No substantive course description was supplied; the item is selected for its named topic and place in the outline only. No individual transcript read or video viewed.

  4. Lecture 2: Conditioning and Bayes' Rule — official publisher material

    Retrieved 2026-11-07. Official resource page description and explicit instructor attribution; not a full transcript or viewing.

  5. Lecture 12 - Utilitarianism and its Critiques — official publisher material

    Retrieved 2026-11-07. Official lecture Overview paragraph. Transcript is linked or included on the page but was not read in full; video not viewed.

  6. Judgment and decision making — Noba

    Retrieved 2026-11-07. Proposed rational procedure and sections/examples on confidence, anchoring and framing read.

  7. MIT probability — syllabus and prerequisites

    Retrieved 2026-11-07. General Information and Prerequisites sections inspected, including no previous probability and the required year of college-level calculus.

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