I like losing. I don’t even think that losing is necessarily evil. Personally, I believe this has less to do with a desire to lose and more to do with curiosity about the game-space.
Technically, my goals are probably shifted into some form of meta-winning — I like to understand winning or non-winning moves, strategies, and tactics. Actually winning is icing on the cake. The cake is learning as much as I can about whatever subject in which I am competing. I can do that if I win; I can do that if I lose.
I still prefer winning and I want to win and I play to win, but I also like losing. When I dive into a competition I will like the outcome. No matter what happens I will be happy because I will either (a) win or (b) lose and satiate my curiosity. Of course, learning is also possible while watching someone else lose and this generally makes winning more valuable than losing (I can watch them lose). It also provides a solid reason to watch and study other people play (or play myself and watch me “lose”).
The catch is that the valuable knowledge contained within winning has diminishing returns. When I fight I either (a) win or (b) lose and, as a completely separate event, (c) may have an interesting match to study. Ideally I get (a) and (c) but the odds of (c) get lower the more I dominate because my opponents could lose in a known fashion (by me winning in an “old” method). (c) should always be found next to (b). If there is a reason I lost I should learn the reason. If I knew the reason I should not have lost. Because of this, (c) offsets the negative of (b) and losing is valuable. This makes winning and losing worth the effort. When I lose, I win.
Personally, I find (c) so valuable that I start getting bored when I no longer see anything to learn. If I keep winning over and over and never learn anything from the contest I have to find someone stronger to play or start losing creatively so that I can start learning again. Both of these solutions set up scenarios where I am increasing my chances to lose. Mathematically, this starts to make sense if the value of knowledge gained and the penalty of losing combine into something greater than winning without learning anything. (c—b > a) My hunches tell me that I value winning too little and curiosity is starting to curb my desire to win. I am not playing to win; I am playing to learn.
To be fair, I am specifically talking about winning within organized systems of competition. This generally means something like Magic: The Gathering, Go, or Mafia. Translating this onto Life is harder because I have more emotional investment in the outcome. The penalty of losing is stronger. If I lose a Game I know that the next round is entirely independent of this loss and there are minimal long-term effects to worry about. The consequences of losing will be much more severe if I screw up an investment portfolio or fail at attempting the perfect murder. To draw a finer line between life and gaming: If the win or loss means placing in a tournament with cash prizes the incentive for winning jumps well beyond the incentive to learn something new and I start playing to win. But is the pain of a loss inversely proportional to the value of a win? No, not necessarily.
To map a tournament into payouts, say it costs $10 for entering and the prize for winning is $20. Losing at any point in the tournament has no monetary costs assigned to it. The $10 is a sunk cost and the $20 is only eligible to winners. Losing has some intrinsic emotional penalty but, other than feeling icky, the loss simply gives another opportunity to learn. The value of winning is greater than that of losing, but losing still has value. Because it has value, losing is good.
Life works the same way. If I am applying for a competitive job I should be playing to win because the payouts are enormous. Losing is a bummer, but the value in the loss is learning new information within the game-space of applying for jobs. Namely, this could mean properly building past experience or learning to sell yourself well. Because you learned something, you are better off than when you started even though you lost. Therefore, losing is good. Winning is better, but losing is still valuable. The cost of losing is not the same as flipping the value of winning negative. You did not “lose” the job because you never had it. You failed simply failed to win.
Irrational winning
Winning is great, but if there is no value in winning other than simply being the winner, losing may be worth more. Winning for the sake of winning is noble but useless. In such a scenario, playing to win may not be the most beneficial course. Playing to learn can result in a gain even if it means you “lose” the game. Looking at it rationalistically, “losing” is winning.
If I play Carcassonne against my opponents and whomp them thirty times in a row by repeating my best known strategies I will have gained nothing. If I decide to use the game as a learning experience to test new strategies I can create an opportunity to learn, but am no longer playing to win. If I play just strong enough to win I can learn and win but this is less valuable than simply learning as much as you can because the win still means nothing. And if it did than you should have played to win.
A better example would be a movie ticket that you purchased for $10. The game-space revolves around whether or not you get more value out of watching a movie than what you spent on the ticket. If you purchase a non-refundable ticket in advance but, on the day of the movie, you do not feel like going to the movie the “win” would be staying home which is actually a “loss” in the original game. The losing scenario has changed because “losing” now has more value.
Note: This example is directly borrowed from Z_M_Davis’s Sunk Cost Fallacy article.
Minor point: In this example, the value of “losing” could be learning to not prepay for tickets or checking the weather first or learning from whatever caused you to mispredict your mood.
Rationalistic losing
Rationalistic losing is essentially acknowledging and playing a super-game so that no matter what happens, you win. In this super-game, playing to win does not mean winning the contest. It means getting something valuable from the contest. In the above examples, even though the contests were lost, the rationalist should still win by learning the information available. Losing should be good. If it wasn’t, something went wrong before you got to this point. Do not rob yourself of the value of losing by focusing on the lost win.
This principle is hard to see when it applies to something you really, really wanted to win. If you really, really wanted that job than losing feels like losing the job. If you skip the movie it feels like losing $10. But you never had the job and you already spent the $10. The only thing left to lose is information. You can still win the super-game if you are able to gather this information. This is rationalistic losing.
There are many examples of, and exceptions to, this principle but the whole point can be boiled into this:
Assume a contest where you can win or lose.
If there is value in winning the contest, play to win, otherwise play to learn.
If you play to win and lose, learn why you lost.
If you already knew why you lost, you were not playing to win.
Learning why you lost is valuable.
Learning after a loss means the loss was valuable.
Rationalistic Losing
Playing to learn
I like losing. I don’t even think that losing is necessarily evil. Personally, I believe this has less to do with a desire to lose and more to do with curiosity about the game-space.
Technically, my goals are probably shifted into some form of meta-winning — I like to understand winning or non-winning moves, strategies, and tactics. Actually winning is icing on the cake. The cake is learning as much as I can about whatever subject in which I am competing. I can do that if I win; I can do that if I lose.
I still prefer winning and I want to win and I play to win, but I also like losing. When I dive into a competition I will like the outcome. No matter what happens I will be happy because I will either (a) win or (b) lose and satiate my curiosity. Of course, learning is also possible while watching someone else lose and this generally makes winning more valuable than losing (I can watch them lose). It also provides a solid reason to watch and study other people play (or play myself and watch me “lose”).
The catch is that the valuable knowledge contained within winning has diminishing returns. When I fight I either (a) win or (b) lose and, as a completely separate event, (c) may have an interesting match to study. Ideally I get (a) and (c) but the odds of (c) get lower the more I dominate because my opponents could lose in a known fashion (by me winning in an “old” method). (c) should always be found next to (b). If there is a reason I lost I should learn the reason. If I knew the reason I should not have lost. Because of this, (c) offsets the negative of (b) and losing is valuable. This makes winning and losing worth the effort. When I lose, I win.
Personally, I find (c) so valuable that I start getting bored when I no longer see anything to learn. If I keep winning over and over and never learn anything from the contest I have to find someone stronger to play or start losing creatively so that I can start learning again. Both of these solutions set up scenarios where I am increasing my chances to lose. Mathematically, this starts to make sense if the value of knowledge gained and the penalty of losing combine into something greater than winning without learning anything. (c—b > a) My hunches tell me that I value winning too little and curiosity is starting to curb my desire to win. I am not playing to win; I am playing to learn.
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Losing is good
To be fair, I am specifically talking about winning within organized systems of competition. This generally means something like Magic: The Gathering, Go, or Mafia. Translating this onto Life is harder because I have more emotional investment in the outcome. The penalty of losing is stronger. If I lose a Game I know that the next round is entirely independent of this loss and there are minimal long-term effects to worry about. The consequences of losing will be much more severe if I screw up an investment portfolio or fail at attempting the perfect murder. To draw a finer line between life and gaming: If the win or loss means placing in a tournament with cash prizes the incentive for winning jumps well beyond the incentive to learn something new and I start playing to win. But is the pain of a loss inversely proportional to the value of a win? No, not necessarily.
To map a tournament into payouts, say it costs $10 for entering and the prize for winning is $20. Losing at any point in the tournament has no monetary costs assigned to it. The $10 is a sunk cost and the $20 is only eligible to winners. Losing has some intrinsic emotional penalty but, other than feeling icky, the loss simply gives another opportunity to learn. The value of winning is greater than that of losing, but losing still has value. Because it has value, losing is good.
Life works the same way. If I am applying for a competitive job I should be playing to win because the payouts are enormous. Losing is a bummer, but the value in the loss is learning new information within the game-space of applying for jobs. Namely, this could mean properly building past experience or learning to sell yourself well. Because you learned something, you are better off than when you started even though you lost. Therefore, losing is good. Winning is better, but losing is still valuable. The cost of losing is not the same as flipping the value of winning negative. You did not “lose” the job because you never had it. You failed simply failed to win.
Irrational winning
Winning is great, but if there is no value in winning other than simply being the winner, losing may be worth more. Winning for the sake of winning is noble but useless. In such a scenario, playing to win may not be the most beneficial course. Playing to learn can result in a gain even if it means you “lose” the game. Looking at it rationalistically, “losing” is winning.
If I play Carcassonne against my opponents and whomp them thirty times in a row by repeating my best known strategies I will have gained nothing. If I decide to use the game as a learning experience to test new strategies I can create an opportunity to learn, but am no longer playing to win. If I play just strong enough to win I can learn and win but this is less valuable than simply learning as much as you can because the win still means nothing. And if it did than you should have played to win.
A better example would be a movie ticket that you purchased for $10. The game-space revolves around whether or not you get more value out of watching a movie than what you spent on the ticket. If you purchase a non-refundable ticket in advance but, on the day of the movie, you do not feel like going to the movie the “win” would be staying home which is actually a “loss” in the original game. The losing scenario has changed because “losing” now has more value.
Note: This example is directly borrowed from Z_M_Davis’s Sunk Cost Fallacy article.
Minor point: In this example, the value of “losing” could be learning to not prepay for tickets or checking the weather first or learning from whatever caused you to mispredict your mood.
Rationalistic losing
Rationalistic losing is essentially acknowledging and playing a super-game so that no matter what happens, you win. In this super-game, playing to win does not mean winning the contest. It means getting something valuable from the contest. In the above examples, even though the contests were lost, the rationalist should still win by learning the information available. Losing should be good. If it wasn’t, something went wrong before you got to this point. Do not rob yourself of the value of losing by focusing on the lost win.
This principle is hard to see when it applies to something you really, really wanted to win. If you really, really wanted that job than losing feels like losing the job. If you skip the movie it feels like losing $10. But you never had the job and you already spent the $10. The only thing left to lose is information. You can still win the super-game if you are able to gather this information. This is rationalistic losing.
There are many examples of, and exceptions to, this principle but the whole point can be boiled into this:
Assume a contest where you can win or lose.
If there is value in winning the contest, play to win, otherwise play to learn.
If you play to win and lose, learn why you lost.
If you already knew why you lost, you were not playing to win.
Learning why you lost is valuable.
Learning after a loss means the loss was valuable.
If the loss was valuable, the loss was “good”.