7 Areas of Game Theory That Can Help You Understand the World

In his conversation with Dave Rubin and his brother Eric, Bret Weinstein says that seeing the world through a game theoretic lens gives you a more fundamental understanding of the world. When asked later about the parts of game theory he’d recommend learning, he listed seven. In this post I’d like to give a brief overview of each and link to more resources if you’d like to explore the ideas further.

Prisoner’s Dilemma

The prisoner’s dilemma is a hypothetical situation in which there are two prisoners (call them prisoner A and B) and they have no way of communicating. They are each given the following offer. If they each betray the other, then they will each get 10 years in prison. If prisoner A betrays prisoner B, then prisoner A goes free and prisoner B gets 15 years in prison. The same goes for prisoner B betraying prisoner A. If they both stay silent then each gets 5 years in prison. Here’s a chart to model the situation:

You can see that it’s in their best interest for each to stay silent, if they could communicate. But since they can’t, the rational decision is to betray. This is because the incentives are too great for the other person to betray (meaning the silent person would get the longest sentence).

This video explains it more in depth.

Race to the Bottom

A “race to the bottom” occurs when states (or other entities) lower regulations or taxes on an industry in an effort to attract financial interests from that industry. States might compete with each other in deregulation (thus making it cheaper to do business there) until the given industry faces little or no regulation from the government.

It isn’t always state to state, however. It can be any situation in which entities in a given geographic region compete for business through deregulation, lower taxes, etc. Free trade is another example of this, where the competing entities are countries.

It’s easy to see the negative repercussions of this situation. Consider lowering environmental regulations on energy companies, relaxing labor laws (like those pertaining to working conditions, for example), lowering minimum wages, or loss of tax revenue and how those things would impact the citizenry of the state.

Free Rider Problem/Tragedy of the Commons

This idea is fairly easily summarized by the following thought experiment. Suppose that you live in a village of sheep herders and there’s a common area where anyone can let their sheep graze. Now, if everyone is mindful of the scarcity of the resource then each would be careful to only let a limited number of their animals graze for a limited amount of time. However, a rational agent might decide that if he let’s only his animals overgraze, it might not be noticed by the rest of the community. He could get greater benefit from the resource without an added cost.

However, if everyone acts in this way the outcome is clear. The resource gets overused and will ultimately be used up, thereby not benefitting anyone.

This pattern can be seen in countless situations in economics, healthcare, environmental resources, and more.

This shows up especially when communication and accountability between parties is difficult or impossible. If each of the herders had a way to know if another herder was letting their animals overgraze, there’d be much less incentive for any one of them to take advantage of the situation.

Here’s a great video that explains the problem in more detail.

Zero-Sum versus Non-Zero-Sum

A zero-sum game is one in which a gain for one player is an equivalent loss for the other player and vice versa. These games are unlike non-zero-sum games because there are no “win-win” possibilities. There’s no enlarging of the proverbial pie. A bigger piece for one person means a smaller piece for another person. Non-zero-sum games are generally better because both sides can benefit from playing.

Here’s a quick video explaining zero-sum games.

Principal-Agent Problem

This problem describes a situation in which one player’s actions (agent) have an impact on another player (principal). This can present problems when the interests of the agent and the principal don’t align. A classic example of this is politicians (agents) and voters (principals). The incentives and resulting actions of the politicians may not align with those of the voters. Other examples include lawyers (agent) and their clients (principal) or mechanics (agent) and customers (principal).

This situation is often accompanied by an asymmetry in information between the two players (the agent has more). This can cause the principal not to trust the agent, especially when the there are sufficient barriers to understanding the motivations of the agent’s actions.

Of course, the principal in not powerless in these situations. Often they are entering into some sort of a contract with the agent and can therefore stipulate terms that change the incentives of the agent. Consider a politician elected while running on the platform “no more taxes”. If said politician raises taxes (thereby ignoring the interests or desires of the principal) it’s likely the politician will succumb to defeat in the next election (which is counter to the politician’s interests).

It’s easy to see variations of this problem. Gerrymandering is a case that can be applied to the previous example. If the politician is operating in a gerrymandered district and there is no fear from a primary challenger, their incentives could be completely misaligned with their constituency. The agent’s actions could undercut the interests of the principal and the principal would have no recourse.

Here’s a great 3-minute explanation of the problem.

For an in-depth explanation of the principal-agent problem in politics from Berkley Law School, click here.

Diminishing Returns

Suppose you own a factory that’s purpose is to make widgets. At first, with nobody working in the factory, no widgets are made. But as you add people to the factory you start to make more and more widgets. Your output increases the more workers you add, but that can’t continue indefinitely. At some point adding more workers will complicate the process and your factory’s productivity will decrease. A cliche that suits this situation is “too many cooks in the kitchen”. The idea is essentially adding more of a particular variable to a system, while other factors are held constant, will eventually result in a diminishing of returns.

Weinstein explains this a bit differently in one of his discussions with Joe Rogan. He explains it this way: “The message of diminishing returns is that you can very often get 90% of a solution that you want and not disrupt other things unduly. But if you say ‘I want 100% of the solution to this problem’ you’ll cause a catastrophe. Getting people to realize, don’t shoot for a utopia in which the problem you are talking about is 100% solved. If you can accept a 90% solution then you can have a whole bunch of other things that you don’t even realize you’re using.”

Here’s a short video describing diminishing returns (I pulled the factory example from this video).

Nash Equilibrium/Evolutionarily Stable Strategy

A Nash Equilibrium can be defined as “a set of strategies in which no player has an incentive to change his or her strategy given what the other players are doing”. That definition comes from this video by William Spaniel, founder of GameTheory101 and it provides a great explanation of it.

The easiest way to understand this is as a set of strategies that people would follow in the absence of some authority forcing them to use those strategies. Spaniel uses the example of a stoplight. Suppose two people arrive at a stoplight. The options available to them are to both go, both stop, or abide by the stoplight (person A goes and B stops, or vice versa). See the screenshot below.

The situation in which either A goes and B stops, or B goes and A stops represents a Nash Equilibrium. There are no incentives to use a strategy other than “heed to the stoplight’s instructions”. If they both stop, neither person gets to where they’re going in the fastest amount of time. If they both go, then they crash (which is the worst possible outcome). The latter two situations do not represent a Nash Equilibrium because there are incentives to change strategies.

I encourage you to watch the whole video as it gives a better explanation than what I’ve given here.

A logical extension of the Nash Equilibrium is that of an Evolutionarily Stable Strategy. An ESS is a strategy that, if adopted by everyone in the system, cannot be “invaded” by another strategy. In other words, it’s not rational for a population to change strategies.

Here’s a great Veritasium video explaining Evolutionarily Stable Strategies.

That’s my best shot at explaining these ideas. I think you’ll find the more you understand and reflect on these aspects of game theory the more you’ll notice them in society. You’ll also more understand what’s going on in the world at a more fundamental level.

(I’m not an expert in game theory and some these ideas I understand better than others, so if you think I’ve explained something incorrectly or misrepresented an idea please let me know.)

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