What We Can Never Know About Michael Phelps
Like millions of other sports fans across the globe, I seem to be constantly watching the 2016 Olympic Summer Games in Rio, Brazil these days. As a result, I’ve seen what felt like an unusual number of ties in the swimming events. Swimmers have tied 12 times in Olympic history, and it’s happened 3 times just in the Rio games. Turns out there’s a wonderful Internet of Things reason for this: Nobody can measure competitive swimming with enough precision to prevent the ties.
FINA, the international organization in charge of swimming, diving, and water polo, allows for a tolerance of up to 3 centimeters in pool length variance. And in fact, pool length can be affected by variables like air temperature, water temperature, and even having people in the pool itself. As such, there’s no way to know that the lane Michael Phelps was swimming in was the same length as those that Laszlo Cseh of Hungary and Chad le Clos of South Africa were swimming in when they tied for a silver in the 100-meter butterfly this past weekend.
Since the dawn of computing, we’ve struggled with the problem of “garbage in, garbage out” — poor quality inputs result in poor quality outputs. The Internet of Things is particularly susceptible to this problem. Sensors designed to measure particular quantities of particular aspects of a particular physical attribute depend on uniformity of the things. In the case of Olympic swimming, we already know that the length of each swim lane is probably slightly different from one another. Today our only “solution” is to ignore milliseconds of time, so we’ll never know how fast Michael Phelps really is. But solutions are on the way. Machine intelligence is eliminating the problem of “garbage in, garbage out.” Perhaps in future Summer Olympics, we’ll never see another swimming tie again, but it may be too late for the greatest male Olympic swimmer of all time.
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