My wife is “kind of/sort of” retiring at the end of this month and has accordingly begun the process of identifying new activities to fill the leisure hours she hopes to discover. Her first of what I expect will be many new pastimes that she has endeavoured to master is the impossibly complex game of Contract Bridge.
To that end, she and a few friends signed up for a series of lessons on the grand old game at a local community hall. Fearing being left in the dust in this potential passion, I have begun revisiting and upgrading my knowledge of the game as well. It is not entirely new to me; in both her early days as a stay at home suburban Mom and then again later as a then active Senior, my mother had been quite keen on bridge, and through both a little osmosis and some actual instruction, the game is not entirely new to me.
Not only is it not new to me, but it is also an activity that is well suited to some of my more instinctive problem-solving skills. Having worked in Structured Finance for 30 years, using basic probability calculations to predict future events is not a new concept to me. When a few weeks ago I downloaded a very simple Bridge application for my iPhone and iPad, I quickly became addicted with the bidding and card playing strategies that it tested, and I began to think I was pretty good at it.
My wife, meanwhile, continued to attend her lessons, and was increasingly frustrated by the arcane and non-intuitive bidding conventions that she was not only being taught, but also asked to memorize. I understood her frustration; while some of them are obviously attempts to create rules to replace the basic math of predicting expected distributions of cards among four hands, others are simply inexplicably arbitrary. It seemed that the lessons were unduly complicating what was simply an exercise in dynamic probability calculations.
And then I got the new and more advanced app. The one that not only facilitated play, but also provided both instructions and evaluation of each and every hand that I played. That was when I discovered that I was not only not pretty good at it, I was in fact pretty bad. At the end of each game, even when I made my contract, the program would critique both the optimization of my bids and how I played each trick. And it invariably concluded that I fell well short of maximizing the points available to my computer partner and I by under- or incorrectly bidding, and that some obscene percentage of teams holding the same hands as my partner and I would have won at least one more trick than we had. It was humbling, frustrating and puzzling.
So I set out to understand why this was so. After all, although hardly a quant, I was pretty sure that I was properly evaluating the probable distribution of cards based on both math and the bidding process, and my ego could not accept that I was that far below average in my ability to do that. I then began playing games in which I was using the apps ability to critique each potential bid prior to locking in any such bid, thereby optimizing my bids to reflect the standard to which the post-play review of the hand would subject me. And that was when I discovered “the problem”.
Bridge is indeed about calculating probabilities and optimizing bidding and card play in the context of uncertainty as to the actual composition of the collective hand you share with your partner. You do get some transparency into your partner’s hand through the bidding process, but it is limited in its specificity. If your partner passes after your 1♣ bid , it is reasonable to assume that he has fewer than three clubs, because he almost certainly would have responded with 2♣ if that were not so. If he responds to that bid with a bid of 1♥, you can reasonable assume that he has five or more hearts and that that is his longest suit because that just makes sense. All helpful, and pretty much the best one could do in the context of the game.
Or so I thought. When I started using the program to evaluate my bids before locking them in, I discovered that the program suggested a far less intuitive bidding pattern. Each suggested optimal bid, I learned, has a meaning that is entirely untethered to any intuitive logic but rather to a convention that allows partners to effectively convey far more specific information about the composition of each other’s hands. As a result, the performance that the program compared me to after each game was that result that would be obtainable if I had complete transparency with respect to my partner’s hand, which is only possible on the basis of the full memorization of a complex array of bidding conventions.
An example is the Stayman convention. Where any player has opened with a bid of 1 no trump (NT), a player may respond with a bid of 2♣ that reflects nothing about what clubs may be in the bidding partner’s hand but is instead a coded question to his or her partner as to whether he or she has four or more cards in a major suit (♥or ♠). If the answer is no, the convention dictates that the partner bid 2♦; if yes, 2♥or 2♠, as the case may be.
This is only one of many such conventions, the use of which can allow partners to effectively establish a complete and specific understanding of the other’s hand and therefore optimize both their bidding and, since the other partner’s hand is only revealed to the players generally when they are the successful bidder, their card play when they are seeking to thwart a bid by their opponents. It is ingenious, but I hate it.
Why do I hate it? Because it lionizes and rewards in a harmless way the inescapable tendencies in our society that, in more critical contexts, warp the meritocracy that is critical to social cohesion and productivity. Bridge purports to be a game of skill in which players must use their calculation of probabilities in the context of high uncertainty to bid and fulfill contracts, but in fact it is far more critical to success to know the conventions that dramatically reduce those uncertainties and simplify those probability calculations. A more expert holder of the skills that this activity purports to test that is not aware of the conventions that negate that advantage will perform more poorly than one who is demonstrably less expert but more in the loop on the coded communications that have developed around the game.
And so it is in may contexts. Hiring decisions in business have long over-weighted a candidate’s knowledge of and comfort with social conventions above directly applicable subject matter expertise. These sorts of conventions are what contribute to the over-representation of white heterosexual able-bodied males in, well, pretty much everything. Like the Stayman convention, white males know that the question “what are your hobbies?” posed by another white male in a job interview generally means “do you golf?’, and that the response “I am an 8 handicap and I love to golf” really means “ I will be willing and able to assist you and our clients in justifying your and their golf outings during business hours”. This convention permits the applicant that knows the convention to gain an advantage in both getting the job (bidding) and being effective with clients once they get it (playing the cards).
You might ask where the harm is in all of this. I can learn and memorize the bridge conventions, and anyone can learn to play golf. But in both cases, that is not the skill set that the activity is meant to test and reward and is accordingly a drag on the utilization and development of the more relevant skills and knowledge that would best advance productivity.
I have stopped playing on my bridge app. The knowledge that I would need to master to perform better is too narrowly applicable to waste my time on any further. And when I am part of a hiring process, I will be more mindful of evaluating applicants solely on subject matter expertise and directly-relevant personal characteristics rather than their knowledge of and compliance with irrelevant conventions. Less bridge, more bridges.
