Bugs or Features? Exploring Cognitive Biases, Fallacies, and Heuristics 

Department: Cognitive Science

Instructors: Adrian Seeley
Instructors' Emails: adrian.marie.seeley@gmail.com 
Prerequisites: None

Course Description

With limited cognitive resources, we humans have developed an array of mental shortcuts (often non- conscious) which are pragmatically useful but can result in error. This course is designed to give an overview of the research, literature, and implications surrounding some of the systematic errors to which we humans are prone, both in everyday decision-making, as well as in social, political, and scientific practices. In particular, the course will focus on cognitive biases, logical fallacies, and heuristics.

Motivation for inquiry into our cognition extends far beyond mere intellectual curiosity. On the individual level, our biases and blunders can affect risk-taking, how we spend our money, whether we save our money, important medical decisions, and more. On a larger scale, biases affect scientific integrity (confirmation bias among researchers, publication biases, etc.), susceptibility to propaganda and “fake news”, education and employment (implicit bias, etc.), public safety (implicit biases, predicting successful strategies, etc.), and more.

Because of the inherently interdisciplinary nature of the course, readings and activities cover topics over a wide scope, including:

  • Psychology (especially social psychology)
  • Philosophy (especially logic and critical thinking)
  • Cognitive Science
  • Behavioral Economics (incl. opt-in versus opt-out retirement programs)
  • Marketing (especially persuasion and advertising)
  • Medicine, g. framing-effects (medical decision-making such as organ donation, etc.)
  • Law and public policy (“Nudges” and Libertarian Paternalism)

Course Goals / Learning Objectives

By the end of the program, students should have an appreciation for the many ways our mental shortcuts, fallacious reasoning, and other cognitive blunders impact the structure of our social institutions, as well as our ideas and behaviors, both as individuals and in groups.

A (non-exhaustive) list of (tentative) topics includes the following biases and fallacies:

  • Confirmation bias
  • Implicit biases (especially racial and gender)
  • Implicit Attitude Test (IAT)
  • Hindsight bias
  • Status quo bias
  • Base-rate fallacy
  • Correlation-causation fallacy
  • Logical Fallacies (e.g. ad hominem, slippery-slope, )
  • Diffusionof responsibility


The final grade for this course will be calculated as follows:

  • Participation (incl. group work, field-trips): 30%
  • Quizzes: 30%
  • Homework (in- or out-of-class assignments): 10%
  • Exams: 30%

Topical Outline

Week 1 - Intro, Cognition, Heuristics: “Who’s in Control, You or Your Brain?”


  • Introduction: How we think, for better or worse!
  • System 1 and System 2-thinking (Kahneman)
  • Systems conflicts: Conscious cognition automaticity: attention, performance, etc.


  • “Biases and Blunders” [excerpt from Nudge]
  • Daniel Kahneman’s: Thinking: Fast and Slow [excerpts]

Week 2 -Cognitive biases and logical fallacies: “Putting the ‘I’ in Irrationality!”


  • Quantification and numbers (including framing effects, probability judgments)
  • Overestimation and exaggeration
  • Practical impacts of biases: susceptibility to persuasion, misinformation, propaganda, fake news, future discounting,


  • Kahneman, Daniel, and Amos "Choices, values, and frames." American psychologist 39, no. 4 (1984): 341.
  • Rispo, Vito: “The Power of Framing Effects”
  • Tversky, Amos, and Daniel "The Framing of Decisions and the Psychology of Choice." SCIENCE 211 (1981): 30. pp. 453-458

Week 3 - Biases and Society: "Climbing Back up the Rabbit Hole"

We will explore the further implications of the mental shortcuts discussed in weeks 1 and 2. Emphasis will be placed on scientific methodology and publishing — the problems therein and the improvements already being made.


  • Publication biases among journals and some new safeguards in place to combat them
  • (Un)likely journals will publish negative results
  • failure to replicate
  • File-drawer problem
  • Researcher’s vulnerability to Confirmation bias
  • P-value fallacy
  • Education and hiring practices



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