Game Theory 1: The Dating Game
Source: YouTube lecture by Professor Jiang, delivered to his Beijing high school students, January 6, 2026. Introduction to a semester-long course on game theory.
What the source covers
Professor Jiang opens his game theory semester with a single extended example — the mating game — to make the framework concrete before applying it to geopolitics, economics, and history.
He proposes five rival theories of what drives human behavior (religion, biology, race/culture, economics, liberalism) and argues that game theory is a better unifying lens. The dating-game example demonstrates why: biology predicts people should seek the best genes, economics predicts they should be efficient, but neither predicts what actually happens. Game theory can, once you identify the right incentive.
The game theory framework
Any game has exactly three components:
- Players — who is participating
- Rules / constraints — the boundary conditions of the game
- Incentives — how you win; what you actually get from playing
Once you map all three, you can predict how the game unfolds. This is the transferable skill: not memorizing outcomes, but learning to identify players, rules, and incentives in any new situation.
See game-theory.
Nash Equilibrium and the dating game
Using five men and five women ranked 1–5 by genes, wealth, and status, the professor demonstrates what rational cooperation looks like: each person matches with their peer (5–5, 4–4, 3–3, 2–2, 1–1). Everyone has a partner; the population reproduces; no one has an incentive to deviate. This is the Nash Equilibrium — the state where all players simultaneously maximize their outcomes.
The problem: this is not what happens in real life.
When male #5 tries to sleep with all five women, the best women recognize this and preemptively choose #4. #4 then chooses #3. #5 ends up with #1. The same cascade punishes anyone who tries to individually maximize across the whole group. Individual maximization destroys collective outcomes — the textbook prisoner's dilemma analog.
See nash-equilibrium.
The actual incentive: status, not sex
The Nash Equilibrium fails to describe reality because the assumed incentive is wrong. People are not optimizing for procreation. They are optimizing for status — Instagram likes, walking through a mall while others are jealous, the ability to brag.
This is the key insight: apparent irrationality is actually rational behavior in a different game. Once you swap in status as the incentive, the mating patterns become predictable again. Women choose the highest-status available man not because of biology but because pairing with him raises their own status. Men at the bottom of the rank don't seek biological alternatives — they withdraw.
The "incel" phenomenon is a downstream consequence: men ranked 1–3 play video games and watch Netflix because competing in the status game feels unwinnable. The entire competition effectively collapses to a contest between rank 4 and rank 5 for all women, which the professor calls "suicidal" for the species.
See status-as-driver.
Superstructure: which game is being played?
The dating game is not universal — it is a product of a specific macro context. Professor Jiang calls this the superstructure: demographics, economics, culture, politics, religion considered together. Superstructure determines which game is in play.
Three historical archetypes:
| Superstructure | Population | Wealth | Technology | Competition | Mating strategy |
|---|---|---|---|---|---|
| Early/primitive | Low (~200–300) | Poor | Very low | Low | Communal sex to disguise paternity — all men protect children they might have fathered |
| Growing/competitive | Medium (~10,000+) | Rising | Some | High | Arranged marriages — maximize child count for warfare/survival |
| Overpopulated/modern | Very high | High but unequal | Advanced | Equilibrium | Dating game — status-maximizing mate selection; fertility collapses |
The civilizational insight: every game is rational given its superstructure. Polygynous-seeming early societies weren't disordered — they were optimizing survival given mortality rates. Arranged marriages weren't oppressive by the standards of societies at war. The dating game isn't stupid — it's what status-rational agents produce in late-civilization conditions.
Fertility decline as a civilizational signal
In a dating-game superstructure, women with means choose to minimize childbearing because:
- Children cost status (time, body, money)
- Raising the bar on partner quality means accepting none over accepting someone who doesn't meet it
- Status is zero-sum — there are only so many high-status men
The professor presents global data: North America, Europe, and East Asia are all below replacement (2.1 children per woman). South Korea is the extreme case at 0.6–0.8, producing projections of near-total population collapse by 2100 if trends hold. China is at approximately 1.0. Immigration is the only near-term fix for Western nations; East Asia lacks that option.
The policy implication is sobering: governments have tried financial incentives (South Korea's cash transfers). None work, because people don't want money — they want status, and status is zero-sum. You cannot print more status.
The one major outlier is Israel: the only wealthy, high-tech nation above replacement fertility. The professor's explanation: because Israel is existentially threatened, fertility itself is status there. Having many children signals patriotism and survival commitment. When the game's incentive structure changes, behavior changes.
The best predictor of civilizational trajectory, in this model: in which societies do wealthy, well-educated women choose to have children?
The life cycle of civilizations
The superstructure framework implies a cycle: low-population societies must reproduce aggressively → growth and competition require organized reproduction (arranged marriage) → prosperity and stability enable the dating game → the dating game produces fertility decline → collapse. Every major civilization appears to have followed this trajectory.
Game theory, in this reading, is not just an analytical tool — it is a way to locate yourself in civilizational time.
Concepts introduced
- game-theory — players, rules, incentives as the universal analytical frame
- nash-equilibrium — theoretically optimal collective state; fails when incentive assumptions are wrong
- status-as-driver — the actual incentive in modern mating; zero-sum; explains why biology/economics predictions fail