Prerequisites

This textbook is designed to be accessible to a wide audience — from high school seniors to graduate students to working professionals. Different parts of the book have different prerequisite levels. Here is what you need to know before starting.

For Parts I–V and VII (Non-Technical Chapters)

No formal prerequisites. If you can read a newspaper critically and are comfortable with basic percentage calculations (e.g., "a 20% increase from a baseline of 50 means the new value is 60"), you have everything you need.

Helpful but not required: - High school-level statistics (mean, median, standard deviation) - Basic familiarity with social media platforms - Any introductory course in psychology, sociology, political science, or philosophy

For Part IV, Chapters 22–24 (Python-Heavy Chapters)

These chapters assume basic Python familiarity: - You can read and write simple Python functions - You understand lists, dictionaries, loops, and conditionals - You're comfortable installing packages with pip

You do not need experience with machine learning, NLP, or network analysis — the chapters teach these from scratch.

If you need a Python refresher: We recommend the free resources at python.org/about/gettingstarted or the "Python for Everybody" course on Coursera (free to audit). Completing Chapters 1–3 of either resource (about 3 hours) will give you what you need.

Mathematical Prerequisites

Mathematical content in this book is intentionally minimal (MATH_INTENSITY = "low"). You will encounter:

  • Percentages and ratios throughout (universal requirement)
  • Basic probability (P(A), P(A|B)) — explained from scratch in Chapter 28
  • Simple statistics (mean, standard deviation, correlation) — explained when they appear
  • Bayes' Theorem — fully derived and explained intuitively in Chapter 28 and Appendix A

You will not encounter calculus, linear algebra, or advanced statistics. When formulas appear, they are always accompanied by plain-language explanations of what they mean.

Background Reading Suggestions

If you want to prepare before beginning the book, these accessible works are excellent background:

For the philosophical foundations (Part I): - Plato's Meno (short, freely available) — on the nature of knowledge - Carl Sagan, The Demon-Haunted World (1995) — on scientific thinking

For the psychological foundations (Chapters 3–5): - Daniel Kahneman, Thinking, Fast and Slow — particularly Chapters 1, 11, and 12

For the media/platform context (Part II): - Tim Wu, The Attention Merchants — the history of attention capture - Or any recent journalism about social media platforms

For the political context (Part VI): - Steven Levitsky & Daniel Ziblatt, How Democracies Die — democratic backsliding context

None of these are required — everything you need is in the textbook itself. But any of them will enrich your reading.

A Note on Prior Beliefs

This textbook asks you to hold your prior beliefs lightly — to be willing to update your views when you encounter new evidence, and to apply the same critical standards to claims you find congenial as to claims you find challenging. This is intellectually difficult. It is also the central skill the book teaches. If you find yourself resisting a chapter's argument because it conflicts with your existing political views, that resistance is itself worth examining. The tools in Part I and Part V will help.

Welcome to the course.