I have noticed a common semantic stop-sign in physics: “But it doesn’t predict anything.”
This is often used whenever discussions of the foundations of a subject come up. I’m not saying that it’s always bad to use this stop-sign; searching for predictive theories is definitely the most useful exercise in science.
But, thinking about the foundations of a subject can also be a very fruitful enterprise, even though you can’t immediately see how it leads to predictive models. For example, Bell inequalities and quantum computing owe their origin, in part, to people debating the foundations of quantum mechanics. Also, the mathematical field of ergodic theory owes its origin to people thinking about the foundations of statistical mechanics.
Instead of saying “It doesn’t predict anything” and then proceeding to ignore it, a more productive attitude would be to ask questions like: “So can we think of some kind of consequences that different foundational pictures point to?” or ask: “Can we build a nice mathematical framework in which we can talk about these questions?” or ask: “Do different pictures help me solve different kinds of problems?”.
Instead of saying “It doesn’t predict anything” and then proceeding to ignore it, a more productive attitude would be to ask questions like: “So can we think of some kind of consequences that different foundational pictures point to?”
Reworded: instead of saying “it doesn’t predict anything”, [we should] ask “does it predict anything?”
In other words: don’t say a theory doesn’t predict anything unless you have an actual argument that shows that it doesn’t predict anything.
I have noticed a common semantic stop-sign in physics: “But it doesn’t predict anything.”
This is often used whenever discussions of the foundations of a subject come up. I’m not saying that it’s always bad to use this stop-sign; searching for predictive theories is definitely the most useful exercise in science.
But, thinking about the foundations of a subject can also be a very fruitful enterprise, even though you can’t immediately see how it leads to predictive models. For example, Bell inequalities and quantum computing owe their origin, in part, to people debating the foundations of quantum mechanics. Also, the mathematical field of ergodic theory owes its origin to people thinking about the foundations of statistical mechanics.
Instead of saying “It doesn’t predict anything” and then proceeding to ignore it, a more productive attitude would be to ask questions like: “So can we think of some kind of consequences that different foundational pictures point to?” or ask: “Can we build a nice mathematical framework in which we can talk about these questions?” or ask: “Do different pictures help me solve different kinds of problems?”.
Reworded: instead of saying “it doesn’t predict anything”, [we should] ask “does it predict anything?”
In other words: don’t say a theory doesn’t predict anything unless you have an actual argument that shows that it doesn’t predict anything.