The world is complex. That’s why one of the best ways to navigate it is to use a mental model as a simplification tool.

Simplicity is not the truth, but if it’s true enough, then simplicity is power. A simplifying tool frees you from having to make every decision as if from a blank slate, saving you time and energy which you can use to wrestle with the genuine edge cases or to combine aspects of different disciplines creatively.

One discipline that I’m intimately familiar with is poker, and the mental model used by the best poker players is probabilistic thinking, or thinking in ranges. And it’s not just helpful with poker—it’s useful for all kinds of decision-making, even your day-to-day choices.

What is thinking in ranges?

We live in the present, in one unified world where there is only one experience happening to us. But in poker, players have to learn to think not deterministically, but probabilistically, meaning that they think of multiple outcomes, and how likely they are to happen.

In poker, this often means assessing how much I should bet on a given hand. I have to think probabilistically based on what I think my opponent might have. In any given deck of cards, there’s a 10% chance any player has a strong hand, a 45% chance they’ve got a medium hand, and a 45% chance they’ve got a weak hand.

Pulitzer-prize winning journalist Charles Duhigg spent a lot of time with professional poker players, and found that when they apply this kind of thinking, they make better choices in the short-term that affect long-term outcomes. As Duhigg writes,

[Poker players] commit to living probabilistically. They might not win this hand of cards that’s right in front of them, but if they make the best probabilistic choices, then over time, they’ll win more often than they lose.

The real benefit of probabilistic thinking is that it allows you to evaluate how your choices impact the long-term.

Thinking in Ranges in Everyday life

But this applies to real life as well. Let’s say you’ve been on the job hunt for a while, and have suddenly been offered 3 different jobs. You’ve got a lot of variables to consider, and really want to make sure you make the best possible choice.

A probabilistic thinker would look at those options on the table and think about how the choice affects the long-term, and how to make the best choice to win most of the time. So if I’m choosing between three jobs, I might look at the best possible outcome of each one, and the worst. Now I have six options on the table. What’s the likelihood of each one coming true? Should I work for a startup that could take off but has a 30% chance of going under? Or a less interesting company that has a 0% chance of going under?

By weighing the chances of each possibility (like in poker, where I weigh the possibility of strong, weak, and medium hands), it allows me to make the best decision.



Check out Too many tools? Too much to do?Check out ScribblePost – the world’s first Productivity Network.

Creativity v. Optimality

Thinking in ranges is, by no means, a pure calculation. It definitely involves some creativity and experimentation. In fact, getting creative can allow you to make better decisions in the future.

Recently, the importance of experimentation was shown in the 5-game Go tournament between Korean Go champion Lee Sedol and Google’s AlphaGo artificial intelligence program. This tournament was the first time an AI used something like the pattern-matching of humans.

The AI won.

Go has a ton of possible outcomes—way more than other games, even poker or chess. Because the game-space is so large, computers can’t win by brute-forcing all possibilities. This is why previous Go AI had failed in becoming competitive against human players. But Google’s AlphaGo was fed the game data of human players and “learned” to recognize certain patterns, certain strategies that seemed optimal over the long-term.

Now AlphaGo had the “intuition” of the value of certain moves versus the uselessness of others, which drastically reduced the amount of moves it had to search. Then, it got better by playing against itself.

source

Each game of this tournament was a battle, but two games in particular are noteworthy for what they say about experimentation and creativity in a larger sense, both in poker and in everyday life.

In Game 2, AlphaGo made a stunning move. Humans had never really made this move in this spot before, and yet after the move was made, Sedol and the rest of the Go community immediately recognized how strong it was. Lee Sedol had to leave the room and take a break before resigning shortly after. Sedol’s confidence in his chances of winning even a single game was shaken after game 2 because of this move.

In Game 4, Lee Sedol made a stunning move of his own. It actually took AlphaGo several moves before it realized that its win probability had dropped drastically and was forced to resign. After the game, Google’s team praised Sedol for his creativity in pushing AlphaGo to a place it hadn’t studied when it played against itself.

In poker or Go, which have tons of possible outcomes, there is still room for risk-taking, or not taking the “normal” route. As the Go example has taught many poker players, playing probabilistically doesn’t mean you can’t get creative. In fact, sometimes getting creative is the only way to get ahead.

Key takeaway

Studying the data means knowing which actions are standard. But knowing what’s standard is exactly what allows you to get creative. Let’s say you’re practicing a presentation you’re going to give at a big conference. You know that everyone else is going to use a PowerPoint. Understanding what the general rules are allows you to play against other people’s expectations—going notes-free for your presentation might be the most creative (and stand-out) way to go.

This logic applies to the job example as well. There’s a ton of moving parts when choosing between job offers, but simplifying some of those variables and knowing what’s standard and what’s experimental can help you choose the option that’s right for you. A 9-5 job is standard, and most people take offers with regular hours.

But if you’re choosing between a full-time position and freelance work (which can feel riskier), if you’ve experimented with freelance work in the past, you’ll be able to make a better decision for you instead of going in blind.

Live probabilistically

Most people think deterministically. For each event, they think that there’s a single outcome and they just try to figure out what that’s going to be.

The problem with that kind of thinking is that it’s incredibly restrictive. You end up focusing and obsessing over the short-term, and this one decision, when you need to be thinking about pushing small-to-large edges to win over the long-term.

You’ll be freed from the worry of the vagaries of individual events and looking foolish in the short-term, and you’ll be able to start making the right decisions in the toughest of spots, with limited data and everything on the line.