{"id":2821,"date":"2013-05-02T11:59:45","date_gmt":"2013-05-02T18:59:45","guid":{"rendered":"https:\/\/www.scotthyoung.com\/blog\/?p=2821"},"modified":"2018-04-03T08:20:17","modified_gmt":"2018-04-03T15:20:17","slug":"break-your-map","status":"publish","type":"post","link":"https:\/\/www.scotthyoung.com\/blog\/2013\/05\/02\/break-your-map\/","title":{"rendered":"Break Your Map"},"content":{"rendered":"

In the process of getting better at something there are two mistakes that hold you back. The first kind is the mistake of not knowing. Not knowing how the market works, which major to choose, what to do.<\/p>\n

If I wanted to start a business selling industrial solvents, I suffer under the first error. I have no idea how the industry works (or much about solvents, for that matter). Ignorance holds me back.<\/p>\n

Ignorance, however, isn\u2019t too hard to fix. If I spent several months researching, I could probably have a decent idea of how the industry works. If I spent several years working in it, I\u2019d know even more. The first error has a straightforward remedy\u2014learn more.<\/p>\n

The second kind of mistake, and far more insidious, is the mistake of believing things that happen to be wrong. If you\u2019ve convinced yourself that a hill is a valley, it will take a lot of climbing before you realize you were wrong. I worry more about the second mistake.<\/p>\n

The Map and the Territory<\/h2>\n

We spend our lives devising theories for explaining the world. These theories form crude maps of the impossibly complex terrain of our lives. We have a map for our careers, a map for our relationships, a map for our beliefs about the meaning in our lives.<\/p>\n

Maps are good. Even a map that is wrong occasionally is a lot better than no map. Philosophical skepticism may have its adherents but it\u2019s utterly impractical. You must have beliefs about the world to make decisions, and even imperfect ones are better than nothing.<\/p>\n

But the map is not the territory. The territory is alien, strange and perhaps even incomprehensibly complex. Any map-making process undertaken by an individual over the course of one lifetime is going to be error-ridden.<\/p>\n

The rational thing to do, is a cost-benefit analysis. If we can invest less resources to fix our map than the benefits of a correct map yield, fix the map. Yet human beings rarely do the rational thing.<\/p>\n

Confirmation Bias and Protecting Our Maps<\/h2>\n

It turns out we don\u2019t follow the rational process for map fixing. Through a set of interesting experiments<\/a>, psychologists could show that instead of trying to hunt for the information that would force us to change our maps, we instead seek to information confirming what we already \u201cknow\u201d.<\/p>\n

The experiment was ingenious. Subjects were given a set of three numbers, such as 2, 4, 6 and told it fits a secret pattern. The task was to guess the identity of the secret pattern by suggesting further sets of three numbers, which the experimenter would say either fit or didn\u2019t fit the pattern.<\/p>\n

Given only one data point, many possible hypotheses could be dreamt up by the participants. The numbers could be all even, for example, or the middle number could be the average of the first and last.<\/p>\n

The rational method for testing these hypotheses would be to choose counterexamples. If you believed the numbers were all even, try 3, 4, 6 and see if it is validated. If it did, you\u2019d know that your only-evens rule was not the correct rule.<\/p>\n

This wasn\u2019t how subjects proceeded, however. Instead, they picked examples which confirmed their previous hypothesis. All-evens testers would pick 4, 8, 10 or 2, 6, 12 as candidate patterns, seeking validation for their theory.<\/p>\n

The problem with this method was that the actual rule was \u201cany ascending numbers\u201d so the previous two examples would have been valid, but so would 1, 3, 12 or 3, 9, 11. The method of testing hypotheses sought confirmation, even when it couldn\u2019t determine the secret rule.<\/p>\n

What relevance does this have outside the laboratory? The relevance is that we look for information to support our theories, not to break them. We try to protect our maps instead of pointing out where they may be flawed. Worse, when we expend energy trying to improve our maps, the methods we default to are unsound.<\/p>\n

Looking Around the Edges<\/h2>\n

The most profitable method to winning the secret-rule game of the experiment is not to pick random counterexamples. After seeing 2, 4 and 6 validate, picking 1, 17, 4 and seeing it fail doesn\u2019t teach you too much. Instead, the best bet is to try to break the edges of your rule: make one odd, flip the order, make two the same.<\/p>\n

The same strategy is effective in life: test around the edges of your map, so you\u2019ll know where to redraw. By breaking your map in precise ways, you can get more information than seeking confirmation or pulling counterexamples out of a hat.<\/p>\n

I\u2019ll give an example from my business. When I first launched Learning on Steroids, it was unusually successful compared to my previous business efforts and I wanted to know which principles guided that so I could use those insights in the future. Here were some candidate hypotheses:<\/p>\n