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# No one loses: Career as an infinite game

Recently, I came across an article which uses the idea of finite vs. infinite games to analyze the startup and venture capital ecosystem in Canada. It got me thinking about the way I’ve grown my career thus far, framed by the finite vs. infinite game concept. In this post, I will not be commenting about the Canadian tech scene, but rather, career in terms of games.

Said article about the Canadian tech scene, which I found thought-provoking: link

- Finite games and infinite games
- Career as an non-linear, infinite game
- Explore! Don’t only do what seems to win finite games

## Finite games and infinite games

*Finite games* are played with the purpose of winning. As the name suggests, it is assumed that there is a finite amount of steps or timeframe for this game, at which point one party wins, and the rest of the participants lose.

For the purpose of this post, I will also assume that finite games are zero-sum games, meaning that for every participant that wins/gains, an equivalent amount of losses is distributed among all those that lose.

On the other hand, *infinite games* are played for a different purpose: since there isn’t a limit to when the game terminates, no party necessarily wins or loses. If one is in a “losing” position right now (subjectively), as long as they stay in the game, they have the chance to flip to a relatively winning position.

Since the game doesn’t terminate, the main goal is to stay in the game, not zero-sum behavior like the finite game. Instead, infinite games encourage the idea that a rising tide can lift all boats, and the whole pie can get bigger.

## Career as an non-linear, infinite game

The formal education system in many, if not most, societies are set up as a finite game. One is the top of class, or they are not. One can concretely say they scored higher or lower in an exam than another student. One graduates, or does not - those that do, are commonly regarded as “winning” over those that dropped out.

I went to middle school and high school in Taiwan. In one class of around 30 students, every ranking was posted publicly. The names of the students with the top 50 highest marks across the whole year (out of ~900 students) were posted at the entrance to the school. The public ranking sheets, both year-wide and class-wide, were updated every month, since we had monthly exams.

Now, personally, this activity in itself can be neutral. It doesn’t suggest, per se, that having a high rank means the student will do great in life, in the lens of an infinite game. But we are humans, and we apply meaning to it, that there are winners and losers in each and every occasion.

Back then, I just took the rank as a “suggestion”, and went about my own life quite unbothered. I played hooky and was in a rock band - and still scored in the top 1% in the Taiwan-wide high school entrance exams, and top 4% in the Taiwan-wide university entrance exams (think their version of the SAT).

Those years inspired the setting of my video game A Summer with the Shiba Inu (Switch / PS4 / Xbox One / Steam), where dogs on an Island fight for social ranking and a magical artifact.

However, many people have built their lives and identity in high school and university around finite game thinking. This paradigm unfortunately carries over to professional life after graduation, with the interviewing process being one of the most obvious examples.

When one gets a rejection, it’s easy to blame oneself, or think that they have “lost” compared to the candidate that did get the job. In this case, we’re still thinking in terms of winners and losers, and believe that the best candidate wins.

To flip this over to an infinite game, a rejection isn’t so much a win or loss - it’s just a step toward a positive outcome. It’s just a “suggestion” for an area of improvement. As long as one stays in the game, and continues to interview, they have the possibility of winning.

Seeing one’s career as an infinite game is powerful in many ways, because it encourages continuous learning and growth. To see why finite games stifle the above positive behaviors, here are some examples:

- In a finite game, if I got into [some prestigious school] I can just consider that I’ve won.
- If one is playing a finite game in their career, and their goal was to enter Google (as an example), once they do it,
*then what*? - If one sees a promotion as a finite game, once they get it,
*then what*?

Because the finite game frames the outcome the end goal as either having won or lost, and that the game terminates, people often neglect to think deeply about what to do afterward.

## Explore! Don’t only do what seems to win finite games

When picking a hobby or side project, it’s easy to base it off the reasoning of “if I do this, does it immediately help me land [x] job or get into [y university] graduate program? If not, I *won’t* do it.” Unfortunately, the above way of thinking is common. Once again, this is finite game behaviour, as it prioritizes an activity that helps one win in the short term, instead of genuine interest.

On the other hand, if all our goals and activities are just steps in a very long trajectory, framed as an infinite game, it’s less about winning and losing. One’s path can be meandering, as mine certainly was, yet still find success eventually.

I continued my journey despite failing multiple university courses, developed my own game that sold quite well for a solo indie developer, and now I’m still wandering and exploring in my career as a data scientist. Nurturing one’s own skills simply out of interest (like my seemingly random activities above) is a trait of an infinite game.

Some time ago my parents asked me *how* I got myself into this career, since they had not heard of the data science field, much less see how I found myself here. I think there was some incredulity in their questions, since the path to data science isn’t clear in their mind at all, like the path to being an engineer, doctor, or lawyer (all suggested as careers to me).

I do understand their concern, and do not dismiss it in the least. the path to data science is very murky for those *already familiar* with the field, much less those like my parents who weren’t even in software or tech to begin with.

My response was that it was simply because I didn’t see a straight line point A to B career for myself, and played the infinite game, retroactively speaking. I’m grateful I allowed myself to explore, from economics to game development, to leading an organization in student union, and whatever I fancied. As to how this landed me solidly in data science, the story is in these posts.

In short, I wasn’t only doing activities that seemed to immediately land me in [x] job. I couldn’t quite explain what made my path different from others at the time, but I think infinite vs. finite games makes sense as an explanation, and is a powerful way to stay optimistic and inspire continuous growth.

## In conclusion

The main summary of my thoughts are as such:

- Careers don’t really have a win or loss condition. Bad situations are temporary with infinite game thinking, but career-ending with finite game thinking.
- Finite game thinking encourages trying to take shortcuts, but infinite games allow for wandering and exploring out of curiosity, which is likely better and more fulfilling in the long run.
- In infinite games, the overall benefit to everyone can be greater, since the pie can be grown and a rising tide lifts all boats.

I hope that some of these thoughts were helpful! As usual, you can find me on LinkedIn or hello@susanshu.com to discuss this post.