Science is the search for regularity.
That is what I would have said a few months ago, and I still think that’s a good definition for science before 150 years ago.
Even today most science would be best defined, and approached, as a search for regularity. It’s not that the search for regularity is invalid, its just that science has gone past this in some circumstances.
Science as a whole mechanism wants to abstract, and model things, that’s the idea I get anyways. A search for regularity would be an improvement in that regard. As a lot of the so called “science of” doesn’t seek regularity but some kind of “significance” in stats. A lot of it is still searching for a theory!
This means we get a whole lot of junk from the scientific community and no one knows where the regularity is. Presumably it’s buried deep under the statistical significance. Something is there but it’s not worth going to find when you can make a conclusion, write a paper, and go back to believing what everyone else does.
Karl Popper said that what scientist do is “solve problems” and that may be a part of the issue. What problem is the scientist first trying to solve? Is it even something that regularity found in nature could possibly solve?
Perhaps Popper is on to something important, not just in being critical of science, but in answering the questions of why does technology produce more science than the scientist.
The technologist is trying to solve a real problem and the scientist is making a model, solving no real problem other than the social problems that are present in every field and profession.
Science, then, starts with a problem and not a theory. Solving for theory takes the scientist into a totally different direction than he would have gone in solving a problem.
One could model all sorts of things and not solve a single problem in science. Maybe you are doing something that is valuable to the profession of science but that’s doing no more doing science than the janitor sweeping the floor at night in the laboratory is doing science.
Science is also said to be universal, if it is universal than it must be regular.
So what about scientific theories? And does this mean there can be no science of the mind?
A scientific theory is only scientific if it can become science. That is, it can be tested and has the potential to be proven wrong.
So the scientist is trying to solve problems by finding science. The scientist searches for science. And he usually finds it by technology since the technologist found it solving a problem.
Thus scientist need problems and yet solving the problem may not always be science.
This is a confusing point to the public, media, and politicians, not to mention the science community.
And yet we have the vocabulary to sort this out. We can say “it’s medicine” instead of “it’s science.” As a lot of medical science isn’t science at all.
This would leave us in doubt of any science with the word “science” in it being science.
And yet the leading fields in science started telling us something different, something different below the quantum level.
Quantum physicists are telling us things that may be impossible for us to observe but that must be a part of the universe and thus universal and thus science.
Much expense and years toiling below the surface in Switzerland have been unable to find the extra dimensions these models assume.
So is this all a waste? Has science ran out of room to run until some technologist makes a way forward?
The discovery of quantum mechanics would not have been possible without the technologist invention of the amplifier.
Perhaps the answer is that science theory needs a lot more time than we want to tell us whether we are right or wrong. And theory is still the job of science but please give us a way to prove and disprove your theories or get out.
The scientist appears now more like an artist. He dreams something up but faintly and then he takes to the tools and tries to complete the picture.
But what is the scientist dreaming of but a solution to a problem?
The artist has no problem to solve, per se, other than the problem of making his imagination into a reality that can be observed by others and a part from himself.
The scientist must then believe that some natural regularity can be applied to solve the problem
and yet takes the approach of the artist in creating a solution from natural regularity.
Once that solution is found, tested, and experimentally proven to the point that it is accepted then the science moves to the engineer.
The engineer uses known science to design (model) and build things. The engineer, while needing to know the conclusions of science, is not a scientist, he uses known regularity, and is not in a search for something new.
The engineering report uses SCIENCE! not theory to show the bridge isn’t going to collapse and kill everyone on and underneath it. Einsteins are not welcome here.
So doesn’t it look like we have a lot of “near science” and “almost scientist”?
I think so and that’s not a bad thing, in fact I think it’s unavoidable. The study of X can lead to knowledge that humans find useful.
Many people have asked if there could be a science of history and many great minds have answered in the affirmative.
I’m not so sure a science of history could ever live up to what we are talking about here.
People have come up with all sorts of theories of history. Can they be proven false? Can they make predictions? Will the predictions still work if this science is shared with the world? Can people get rich from it?
In yet this sounds a lot like what political strategist do or hedge fund managers, or dictators and the great generals.
And yet here is no science as luck surely plays such a large event. This is why the study of X can be of value even if it can’t clear the bar of SCIENCE! Positivist be damned!
So you and me aren’t so far from scientist in whatever problems we try to solve, scientific thinking about X, though it probably won’t yield any science that makes it into the textbook, it’s still a valid way of thinking when solving problems.
And other ways of thinking confirmed by science are valid as well; 80/20 thinking, computational thinking, and possibly more such as Bayesian thinking, probabilistic thinking, mathematical thinking, etc.