Show jumping: Real Algorithm
On last week’s discussion group, we were discussing the concept of algorithms as presented by Daniel Dennett in his book Darwin’s Dangerous Idea: Evolution and the Meanings of Life. We discussed various examples of algorithms, such as Dennett’s example of the tennis tournament and Dennet’s depiction of algorithms as “substrate neutral”. After a long discussion as to what substrate neutrality meant and what exactly was an algorithm and if it was applicable to daily-life examples, we still found ourselves in an abyss. With this paper, I will try to bring in a daily-life example to help illustrate the concept of algorithms, as described by Dennett, in a more concrete manner.
The example I chose to present as an explanation of the concept of an algorithm is show jumping. Show jumping has been part of my life for fifteen years now, so I know it well and feel that it will be a satisfactory example for explaining the confusion that has been raised in class.
Dennett defines algorithms as “simple, straight-forward steps that are part of a logical structure, that when followed correctly will yield guaranteed results.” (Dennett 50-51) It is in other words, “a foolproof recipe” (Dennett 51). Show jumping has a very basic recipe for success: get to the jump at the correct distance and you are guaranteed a clear jump.
First, let me explain how show jumping works. It is an individual sport, in which you are in a ring with a horse, with the objective of going through the course without knocking any jumps down. Pretty simple right? But in order to clear a jump, you must go through a series of steps. First you start to canter, then you look at the jump you want to take, and once you are headed for the jump you have to measure the distance for the horse to jump. The distance is the spot from where you want to take-off so the horse has enough space that he can pick up its front legs, but it should not be big enough so as the horse has the option of refusing the jump. If you start off with good rhythm, center the horse and find the correct distance, you are guaranteed a clear jump.
So far, show jumping is looking like a fool-proof recipe. But what does it mean that it is a substrate neutral algorithm? As discussed in class, if you have a tennis tournament divided up into brackets, there will inevitably be a winner and a loser regardless of who you put in it. The substrate neutrality refers to the logic behind the process, not on the subjects taking part in the logical process. Some may argue that this would not apply to show jumping. What if you follow the algorithmic steps correctly but the horse just didn’t feel like jumping that day and refused the jump? This would veto the depiction of show jumping as an algorithmic process. This is a random occurrence that can, indeed, affect the outcome of the process, but it in itself is not part of the algorithmic process because it is unpredictable or random. Dennett uses the example of the stock market motto: “Buy low, sell high”. Anyone who follows this should and would be rich, but the problem is that the market is so random that we don’t know when it is going to be low or high. Therefore, you can follow the motto (algorithmic process), but the randomness of the stock market can alter the expected outcome, in this case, cashing in. This is the same in show jumping; the recipe is correct and will work effectively, but random factors such as the horse’s temperament might influence the outcome.
I have hopefully provided a good depiction of a daily-life algorithmic process in a way that may be more approachable and understandable. Now that we can grab a hold of the idea of an algorithmic process, I invite you to explore and look around you and question if everything can be an algorithmic process. We perform basic steps every day, like making a bed or driving, but are these algorithmic processes? What exactly determines if a series of basic steps get to be called an ‘algorithmic process’?
Dennett, Daniel C. Darwin's Dangerous Idea: Evolution and the Meanings of Life. New York: Simon & Schuster Paperbacks, 1995.