Definite Games, Indefinite Optimism

December 6, 2022

One of the more thought-provoking pieces I read last year was Alex Danco’s post “Why the Canadian Tech Scene Doesn’t Work,” which dissects the structural and institutional factors that make Silicon Valley so much more effective at spawning successful companies than Toronto. I’ll briefly summarize the piece’s key arguments here, connect it to some ideas from Zero to One, and finish by drawing some conclusions for academia.

Danco’s key insight is applying James Carse’s distinction between finite and infinite games to entrepreneurship. What makes a game “finite” or “infinite”?

First, finite games are played for the purpose of winning. Whenever you’re engaging in an activity that’s definite, bounded, and where the game can be completed by mutual agreement of all the players, then that’s a finite game. Much of human activity is described in finite game metaphors: wars, politics, sports, whatever. When you’re playing finite games, each action you take is directed towards a pre-established goal, which is to win.

In contrast, infinite games are played for the purpose of continuing to play. You do not “win” infinite games; these are activities like learning, culture, community, or any exploration with no defined set of rules nor any pre-agreed-upon conditions for completion. The point of playing is to bring new players into the game, so they can play too. You never “win”, the play just gets more and more rewarding.

In entrepreneurship, Danco argues that infinite games are good and finite games are bad. Good founders are playing infinite games: they want to build something important and keep on contributing to society and progress. In contrast, bad founders are playing to win a finite game—acquiring lots of funding, getting high valuation, or exiting with a big IPO.

Danco identifies numerous ways that the Canadian startup ecosystem incentivizes finite games at the expense of infinite games. One important factor favoring finitude is the scrutiny given to deals between founders and funders (e.g. in a seed round), which tends to favor conservative or incremental ventures over ambitious, idealistic ones:

[High deal scrutiny] is bad, for two reasons. It’s bad because the very best startups, who have the longest time horizon and are most curious about the world, will look disproportionately uninspiring. They’ll have the fewest definite wins relative to their ambition, and the most things that can potentially go wrong.…

Conversely, [high deal scrutiny is] bad because startups will learn to optimize for how to get funded. So if seed deals take 3 months, then founders will learn to build companies that look good under that kind of microscope. And that means they’re going to optimize for playing determinate games, so that they can show definable wins that can’t be argued against; rather than what they should be focusing on, which is open-ended growth.

Government support for startups also tends to prioritize finite games at the expense of infinite games, since the requisite bureaucracy tends to stifle fast-moving innovation:

The problem with [research tax] credits, honestly through no fault of their own, is that you have to say what you’re doing with them. This seems like a pretty benign requirement; and honestly it’s pretty fair that a government program for giving out money should be allowed to ask what the money’s being used for. But in practice, once you take this money and you start filling out time sheets and documenting how your engineers are spending their day, and writing summaries of what kind of R&D value you’re creating, you are well down the path to destroying your startup and killing what makes it work.

Overall, Danco paints a picture of a place where an obsession with goals and benchmarks has almost completely crowded out sincere innovation:

Quite in character with our love of milestones, Canada loves anything with structure: accelerators, incubators, mentorship programs; anything that looks like an “entrepreneurship certificate”, we can’t get enough of it. We’re utterly addicted with trying to break down the problem of growing startups into bite-size chunks, thoughtfully defining what those chunks are, running a bunch of promising startups through them, and then coming out perplexed when it doesn’t seem to work. (emphasis added)

While Danco limits himself to comparing Canada and Silicon Valley, this failure mode is sadly not confined to Canada. Indeed, many of his observations are directly applicable to academic research. The large number of finite games in academia—publishing papers, writing a dissertation, submitting grants, getting tenure—tends to crowd out the more impactful infinite games that lead to real, meaningful progress, and promotes incremental projects with a high chance of success. (This is simply Charles Hummel’s “tyranny of the urgent” by a different name.)

My claim is that the distinction between finite and infinite games is best understood through Peter Thiel’s concept of definite and indefinite optimism. In Thiel’s dichotomy, indefinite optimists believe the world will get better but have no idea how, whereas definite optimists have a concrete proposal for how to make the world better.

How does this connect to finite and infinite games? Paradoxically, indefinite optimism leads to an obsession with finite games, since there’s no higher animating principle at work to drive progress. When you don’t have any positive vision for innovation, the natural solution is to write procedures and hope that progress will arise spontaneously if the right steps are followed. Companies, research groups, and other organizations can learn to mimic what actual innovation looks like from afar, but without the proper motivations their ultimate success is improbable.

In contrast, an organization playing an infinite game doesn’t need to be forced to jump through arbitrary hoops. Pharmaceutical companies don’t bother to acquire 13C NMR and IR spectra for every intermediate; startups putting together a minimum viable product don’t worry about properly formatting all their code. Finite games are only a distraction for properly motivated organizations, and one which should be avoided whenever possible.1

What conclusions can we draw from this? On a personal level, seek to make your games as infinite as possible. Every startup has to raise money and every graduate student has to publish papers, but one shouldn’t spend most of one’s time worrying about how to publish papers as efficiently as possible. If you can treat finite games as the distraction that they are, you can give them as little mental effort as possible and spend your time and talents on worthier pursuits.

On a broader level, I’m struck by the fact that finite games are a problem of our own making. Nobody becomes a scientist hoping to write papers or win grants;2 our aspirations start out infinite, and it’s only through exposure to the paradigms of the field that we learn to decrease our ambition. Indeed, calling a research proposal “ambitious” is reportedly one of the worst criticisms that an NIH study section can give.

We should therefore be skeptical about bureaucratic solutions to research stagnation. If our scientific institutions themselves are part of the problem, expanding their reach and importance is unlikely to fix the problem and may indeed do more harm than good. “If you find yourself in a hole, stop digging.”

Thanks to Jacob Thackston and Ari Wagen for reading drafts of this piece.

Footnotes

  1. I’m intentionally eliding the normative question of “how do we assign funding if not through quantitative measures?”—it’s an excellent question, and one which deserves a larger treatment than I can offer here. The Nielsen/Qiu metascience essay has some ideas here.
  2. This may not always be true, but I think it’s generally true. Most high schoolers or undergraduates are drawn to science because of a sense of wonder or curiosity, which gets transmuted to “publish JACS papers” through the alchemy of graduate school. Ari pointed me towards this essay by a physics graduate student, which seems relevant.


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