But to plug this fuzzy, professional knowledge into equations, call it science, and use it to make decisions in business and policy is at best naive and at worst fraud.
Throwing engineering in there with psychology and medicine is not a very good grouping of disciplines. At least not if "engineering" means the kind of engineering that professionals in the field have legal liability for (like the engineering that goes into designing bridges and buildings).
Engineering does have "best practices", but those practices have to operate within limits that are very well understood based on underlying physical science that has been thoroughly tested and for which we have mathematical models with excellent predictive capability. The "best practices" in psychology and medicine have nothing like that kind of support.
> the process seems to work allright
Engineering, at least the kind that designs bridges and buildings, seems to work all right, yes. I'm not sure I would say the same for psychology and medicine.
But it's also true that any of those engineers who say that a particular regulation doesn't make technical sense, will be able to explain to you in detail why it doesn't make technical sense, based on the kind of theoretical and practical knowledge I described, the kind that is backed by well-tested models with excellent predictive capacity.
You are right that these largely don't exist in the Social sciences, but this is at least partially due to the much more complex subject matter. Still, both the social sciences as well as the natural sciences are trying to approximate reality through models built on experiments, and are thus fundamentally different from deductive reasoning in closed systems.
Not trying to mince words here, but engineering is applying validated knowledge to solve real world problems, sure, you can call it profession, but the fields generally associated with engineering are still in the business of generating knowledge. Medicine and Psychology heavily rely on the scientific method to validate abstract concepts, while engineering adjacent disciplines like Computer Science heavily really on maths and deductive reasoning to solve problems in the space of algorithms and computers.
There is still an awful lot of engineering that is model-based without strong deductive proofs. (Mechanical failure theory comes to mind). But the actual origin of "profession" comes from professing an oath to the public good. Meaning the traditional professions (law, medicine, engineering) aren't necessarily aimed at creating new knowledge, but applying knowledge to the betterment (or profit) of society. Sometimes that butts up against problems without known solutions that requires adding knowledge to the field, but that's not really the primary goal, unlike something like mathematics.
I disagree strongly with this. To reduce mathematics (and philosophy in your next sentence) to not-a-science, just because it's based on deductive reasoning is doing it a major disservice.
It is especially because of its deductiveness that mathematics is such a valuable tool for science. It answers the fundamental question "assuming A, what can we prove to be true about A' and A''?". Without that deductive proof, many inductive scientific theories could not even be formulated, let alone disproven.
And then you go on stating that engineering is applying validated knowledge to solve real world problems. Do you realize that much of that validation of said knowledge has been done through mathematical models? That the only reason we have certainty in engineering is because of the deductive rigour of mathematics?
It’s still incredibly valuable and the basis of many good things.
I would also add that engineering isn’t only working with existing scientific knowledge; we were building steam trains and optimizing them long before we started doing scientific thermodynamics.
Treating science as gospel is stupid. But without personal experience (and frequently even with) stating something as true is largely meaningless. Stating something is true, while providing data to back it up, as well as evidence that other subject experts have checked that data may not be perfect, but that doesn't put it on equal footing with a gut check.