I’m skeptical of the concept as presented here. Anything with the phrase “how perfection is achieved” sets up a strong prior in my mind saying it is completely off-base.
More generally, in evolution and ecosystems I see that simplicity is good temporarily, as long as you retain the ability to experiment with complexity. Bacteria rapidly simplify themselves to adapt to current conditions, but they also experiment a lot and rapidly acquire complexity when environmental conditions change. When conditions stabilize, they then gradually throw off the acquired complexity until they reach another temporary simple state.
The Occam ideal is “simplest fully explanatory theory”. The reality is that there never has been one. They’re either broken in “the sixth decimal place”, like Newtonian physics, or they’re missing bits, like quantum gravity, or they’re short of evidence, like string theory.
The Occam ideal is “simplest fully explanatory theory”. The reality is: sometimes you don’t have a fully explanatory theory at all, only a broken mostly-explanatory theory. Sometimes the data isn’t good enough to support any theory. Sometimes you have a theory that’s obviously overcomplicated but no idea how to simplify it. And sometimes you have a bunch of theories, no easy way to test them, and it’s not obvious which is simplest.
So maybe, to rephrase the idea then, we want to strive, to achieve something as close as we can to perfection; optimality ?
If we do, we may then start laying the bases, as well as collecting practical advices, general methods, on how to do that. Though not a step by step absolute guide to perfection, rather, the first draft of one idea that would be helpful in aiming towards optimality.
edit : also, that’s a st Exupery quote, that illustrates the idea, I wouldn’t mean it that literally, not as more than a general guideline.
I’m skeptical of the concept as presented here. Anything with the phrase “how perfection is achieved” sets up a strong prior in my mind saying it is completely off-base.
More generally, in evolution and ecosystems I see that simplicity is good temporarily, as long as you retain the ability to experiment with complexity. Bacteria rapidly simplify themselves to adapt to current conditions, but they also experiment a lot and rapidly acquire complexity when environmental conditions change. When conditions stabilize, they then gradually throw off the acquired complexity until they reach another temporary simple state.
The Occam ideal is “simplest fully explanatory theory”. The reality is that there never has been one. They’re either broken in “the sixth decimal place”, like Newtonian physics, or they’re missing bits, like quantum gravity, or they’re short of evidence, like string theory.
The Occam ideal is “simplest fully explanatory theory”. The reality is: sometimes you don’t have a fully explanatory theory at all, only a broken mostly-explanatory theory. Sometimes the data isn’t good enough to support any theory. Sometimes you have a theory that’s obviously overcomplicated but no idea how to simplify it. And sometimes you have a bunch of theories, no easy way to test them, and it’s not obvious which is simplest.
So maybe, to rephrase the idea then, we want to strive, to achieve something as close as we can to perfection; optimality ?
If we do, we may then start laying the bases, as well as collecting practical advices, general methods, on how to do that. Though not a step by step absolute guide to perfection, rather, the first draft of one idea that would be helpful in aiming towards optimality.
edit : also, that’s a st Exupery quote, that illustrates the idea, I wouldn’t mean it that literally, not as more than a general guideline.