Awesome post!
It is very true: exploring and learning from risky strategies on a small scale (ostensibly resulting in losses) is a strategy for meta-winning. You provided good examples in your post. This is such an important idea, I would like to add two more.
Losing when stakes are low is a strategy for winning when stakes are high
A common real life scenario is that it easy to win when the stakes are low and harder to win when the stakes are high. If you are always winning in a low-stakes scenario, then you have information that your strategy is good, but only for that context. You would like to test and hone your strategy in more challenging contexts, but perhaps there it is more important to win (not practice winning).
The solution is to handicap yourself in the low-stakes scenario. Challenge yourself by not permitting full use of the winning strategy. You already knew your strategy was sufficient for winning but now you will learn: what aspects of your strategy were necessary for winning and what aspects can be modified for even more effective winning. You will have developed a better strategy for the high-stakes scenario.
An analogy from statistical mechanics:
A ball is passively rolling around a landscape of hills and valleys. The ball, being passive, will roll down valleys (but not roll up hills) until it finds itself in the “lowest” location. The ball is in the lowest location because if it were to consider moving in any direction it would have to move up. This is a local minimum. How does the ball know that there isn’t a lower valley just over the next hill? The ball will be much more effective at finding the absolute lowest valley if it is able to climb some hills to explore what’s on the other side. By allowing yourself to explore less effective strategies (climbing hills), you increase the probability of finding an even better winning strategy (a lower minimum) than your original one.
Fortunately, these ideas are very well developed in physics and guidelines are provided for determining how to choose your tolerance for losing (ability to roll up hills/temperature) in order to optimize finding the best winning strategy (verses exploring up and down indefinitely without net progress).
"To beat your opponent'" is only one form of the idea of winning - "to get the most valuable thing" may be a more useful one.
If what you could learn from taking an unusual strategy or playing against a harder opponent is more valuable than whatever you get from just beating your opponent, then yes, the first option is the better one. There are probably other examples of this kind of thing, too - the things that society defines as 'good' or 'winning' are not always going to match what we value most.
Sirlin makes this point himself in his book:
http://www.sirlin.net/ptw-book/love-of-the-game-not-playing-to-win.html
Now it’s time for what appears to be the opposite point of view: “playing to win” at all times is counter-productive. If you want to win over the long term, then you can’t play every single game as if it were a tournament finals. If you did, you wouldn’t have time for basic R&D, you’d never learn the quirky nuances that show up unexpectedly at tournaments, and you are likely to get stuck honing suboptimal tactics.
If losing is a soul-crushing defeat to be avoided at all costs and winning is The Delicious Cake, not the icing, there is a much stronger incentive to win.
See the OB article on Lost Purposes- there's a distinct chance that a process optimized for fact-finding or interesting-fact gathering won't be optimized for winning. Sometimes our map needs to reflect the territory just enough for us to find the treasure.
In the real world where games have consequences, there is specialization, insofar as it is possible, in exploration and winning. Defense R&D is a function very separate from combat, and engineering is mostly separate from physics. Because there are limits to the scope of human attention, our sense of "this might be useful elsewhere" comes into conflict with the drive to start and finish projects.
If losing is a soul-crushing defeat to be avoided at all costs and winning is The Delicious Cake, not the icing, there is a much stronger incentive to win.
Soul-crushing is a bummer but is technically optional. If you can train yourself away from soul-crushing it may make losing better for you. The same goes for winning: if winning holds no intrinsic value other than "Haha! I won!" I would argue that the incentives are purely emotional. This is not necessarily a bad thing, but I like to get more of my contests than feeling good about winning or feeling bad about losing. Personally, I get more emotional satisfaction from learning something new or cool.
See the OB article on Lost Purposes- there's a distinct chance that a process optimized for fact-finding or interesting-fact gathering won't be optimized for winning. Sometimes our map needs to reflect the territory just enough for us to find the treasure.
Here is a link to Lost Purposes for those who need one.
I agree with your point. Most of what I talked about is only terribly relevant for contests such as board games where the rewards for winning are easily measured. When losing holds a significant loss factor such as a generation of children not learning science, playing to learn makes no sense and it is time to play to win.
In the real world where games have consequences, there is specialization, insofar as it is possible, in exploration and winning. [...]
Agreed. The big gap in my article that I left out for brevity are examples of physical contests. If someone stabs me with a sword, I die. Playing to learn would make no sense in a sword fight and losing is most decidedly not good.
(Edit) After thinking a little more, I would relate "Lost Purposes" to this article with the following question: "What is the purpose of winning?" Don't win just because you are supposed to win. Win because it has value.
Fun fact - better strategy for memory: You play memory 1 vs. 1, and it's your move.
People don't do step 4 right usually.
"Take a tile known to both of you (if there is doubt, take one your oponent knows)."
I don't understand the parenthetical comment: it seems to be saying "If you are not sure both of you know what a tile is, then choose a tile your opponent knows." How could you know your opponent knows what a tile is but not be sure you know? Or maybe I'm just not understanding?
If you flip over a tile that matches some other tile that has already been revealed, your opponent gets to make the match first.
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 you can already win consistently, why do you seek new strategies? I would seek a new game (or at least new competitors) where you don't yet consistently win.
More generally, I think this is an example of exploration (learning) vs. exploitation (winning) strategies. Personally, I think that people are more risk adverse than is otherwise optimal, so we should attempt more exploration than we normally do before settling into an exploitation routine.
If you can already win consistently, why do you seek new strategies? I would seek a new game (or at least new competitors) where you don't yet consistently win.
Curiosity is one excuse. Learning more about the game-space can also generate better strategies. Strategies in a game such as Go can always be improved.
The point about playing to learn is a stepping stone to the point that losing is not something to avoid at all costs. I would rather lose and learn than win and not learn. This drives me to do exactly what you suggested. Seeking new competitors or new games is roughly equivalent to playing to learn since you are putting yourself in a position where losing is more likely. In both of these cases, losing is good because you can learn from the losses. Winning is still better but winning against losers is useless. (Unless there are prizes on the line.)
More generally, I think this is an example of exploration (learning) vs. exploitation (winning) strategies. Personally, I think that people are more risk adverse than is otherwise optimal, so we should attempt more exploration than we normally do before settling into an exploitation routine.
The major point I was trying to make is that attempting to exploit and failing at it will automatically provide a source for exploration. The idea of playing to learn is exploration, but if your exploitation routine is consistently providing exploration, why bother with the exploration routine? Play to win and use the losses to learn how to win.
Good post. My second post on my blog covered much the same ground from a somewhat different angle - http://williambswift.blogspot.com/2009/03/value-of-mistakes-mistakes-and-learning.html
I find the best members of the Competitive Conspiracy treat as a loss any game or competition in which they felt they were capable of doing better whether or not they managed to come out of it a winner. There is no better way to identify the best competitors than to ask them how they are performing, and the ones you're looking for will tell you about what they are learning and all the mistakes they are making, whether or not they are winning. The weaker ones won't talk that way even when they are losing.
Losing can provide valuable motivation, and there is nothing wrong with losing, but it is putting yourself in a position where you can either win or lose that is most valuable.
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.
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 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: