The title might seem ridiculously over-generalized. Debate tournaments in high school, for example, are a public battle of ideas that have a clear winner and a loser. Surely those should be combative?
Of course they should — they’re a classic zero-sum game, where if one side wins the other must lose. But this form of debate, while familiar, is extremely rare in real life and not particularly important in the grand scheme of things. Its familiarity means that when we hear “debate” we too often jump straight to a combative stance.
The far more important type of debate in the real world is a wholly different animal. It, too, is about pitting ideas against one another to find the strongest one. But unlike in high-school debate, the team who advances the strongest idea isn’t the winner. The goal is to uncover the best solution to a given problem: to understand a complicated and complex problem space as fully as possible. Who had the best idea is immaterial. Unlike a high-school debate, this framing reveals it to be a positive-sum game.
And that difference between zero- and positive-sum game makes all of the difference. In a zero sum game, the proper stance is competitive. But in a positive sum game, the proper stance is collaborative. If the two parties together come to a better understanding than either had individually before, everyone wins.
How to approach a collaborative debate
No one knows everything. Everyone approaches problems in a different way. This diversity, if properly harnessed, can lead to better results than any one party could have come up with on their own.
Seek to understand the other parties’ insights, concerns, and confusions. If they have an insight, then you can incorporate it and make the leading idea better. If they have a legitimate concern then you can improve your idea to better defend against it (or, if it’s significant enough, pivot to a better approach altogether). And even if they are confused, figuring out how to help them understand will help you communicate your idea more effectively to others in the future.
In a collaborative stance you go into the debate willing to learn and willing to change course when presented with better arguments or data. Riff off of one another’s ideas. Try different framings, different models, different metaphors and see which ones stick — and then build off of those. At all times focus on adding positive energy to the exploration.
Staying in a collaborative stance is difficult, and it’s easy to accidentally shift back into a combative stance. Be careful not to privilege your own ideas. Be on the watch for emotional responses to critiques or competing ideas — if left unchecked they tend to cause similar responses in others, derailing the whole discussion. It’s tempting to conclude that your debate partners are not participating in good faith, or are taking a combative stance. But challenge yourself to assume good faith and to always bring the other participants back to a collaborative stance whenever they stray. After all, everyone has a shared interest in identifying the best solution, and the only way to do that is to maintain a collaborative stance.
If, with patience and a willing partner, you are not able to convince the other that your idea is superior, than perhaps it isn’t. Get to the root of the disagreement, the core point where you don’t see eye to eye. Is it a misunderstanding? A legitimate disagreement? Different assumptions about the value of a currently unknown quantity? Work until you uncover it and fully understand it.
The collaborative approach to debate is one of the best ways to understand complicated, and especially complex, problem spaces. The result is a stronger idea that more perfectly anticipates the messy reality it will have to operate within.
Note: The original version of this essay, confusingly, used the concepts of complexity for the easier type, and ambiguity for the harder type, instead of complication vs complexity. I’ve updated the essay to use the word “complexity” in the sense it is used elsewhere, including the cynefin framework, complexity theory, etc.