Thinking about Occam’s Razor

While watching an episode of Madame Secretary the other night, I was interested to hear the main character mention Occam’s Razor as she wrestled with a complex issue and the need to get at the variables, understand them and make decisions about how to proceed. Knowing my interest in complexity and complex adaptive systems (CAS) theory, a friend told me about Occam’s Razor awhile ago. I had never come across it before, despite lots of reading about complexity and complex systems – obviously not reading the right things, Ann! Thanks.

Wikipedia tells us that Occam’s Razor (which is also sometimes written as Ockham’s Razor) is a problem-solving principle devised by William of Ockham in the 13th C – believe it or not. William was a respected English Franciscan friar, philosopher and theologian.

The principle of Occam’s Razor states that among competing hypotheses which predict equally well, the one with the fewest assumptions should be selected. Other, more complicated solutions may ultimately prove to provide better predictions, but—in the absence of major differences – the fewer assumptions that are made, the better – according to the theory.

Called also the Law of Parsimony, it tells us to KISS or keep it simple, and not over-complicate. This of course makes a lot of sense and it also reminds us to quantify, qualify and verify our assumptions. Wikipedia goes on to say “ For each accepted explanation of a phenomenon, there is always an infinite number of possible and more complex alternatives, because one can always burden failing explanations with ad hoc hypothesis to prevent them from being falsified; therefore, simpler theories are preferable to more complex ones because they are better testable and falsifiable.”

The fact that we are still considering William of Ockham’s ideas, 7 centuries later boggles the mind, and makes me question how much more we know or don’t know today than we did centuries ago.

It also makes me wonder about the fit between Occam’s Razor and complex adaptive systems’ theory. This is for another time.