Talk:Nomological machine

How about this for a theory: the scientific method is to build normal logical machines and they are to paired down, filter, abstract, and simplified – 2 reduce all parameters in an environment until it is predictable. This is a process of constraint and mechanization. The scientific exercise is to force the natural world by the use of legislation to behave in a certain way. To remake the territory until it resembles the map. To build models.

This is somewhat consistent with my concern about technologization and financialization, which is to persuade humans to behave in ways that suit the model will stop this seems to get things just about backwards.

The controls are different, though: if the world in broad strokes refuses to conform to the scientific model, the model needs to be changed. If the world imports for refuses to conform to the technology, the world needs to change full stop one of these things seems profoundly liberal, the other profoundly illiberal.

Hence the despair at the contemporary distrust of science is misplaced and possibly confuses science and politics. And it may be in turn driven by scientists confusing their role with those of politicians.

There's no general skepticism about science; it's skepticism about new science that makes generalised long-range predictions. It's a skepticism born from disappointment with the experience. If science proves to be bad at making long-range predictions about things come out then asking hard questions and holding authorities to account is no bad thing that's just perfectly ordinary, sensible common pragmatic skepticism.

Science is the business of making predictions. A scientific theory that makes extremely short term predictions is easily tested and validated or rejected. No one doubts a theory that makes frequent short-term predictions, like basic Newtonian mechanics, you can see the repeated accuracy and judge for yourself. However if the science makes long range, vague generalized predictions, it's a lot harder to see tangible outputs, there is a lot more scope for skepticism and we should hardly be surprised.

So what other things that we routinely hear we are “tired of experts” about? Brexit, covid, climate change —these are all phenomena involving the long range behavior of complex systems in respect of which there are multivariate causal factors, generalised statistical extrapolations requiring sophisticated chains of logical inference. these are exactly the sorts of things where scientific certainty is weakest and skepticism is most justified.

Generalised statistical extrapolations are one thing when dealing with physical phenomena; quite another when took dealing with the social behavior of humans.

Visa exactly the fields in which weak logic, suspect inference could easily give rise to profoundly missed and sieved theories, and we should welcome criticism that makes these hypotheses more robust.