Actually, neither do Rationalists, but instead they cosplay at being rational.
What do you mean? The biologists I've had the privilege of working with absolutely do try to. Obviously some work at a higher level of abstraction than others, but I've not met any who apply any magical thinking to the actual biological investigation. In particular (at least in my milieu), I have found that the typical biologist is more likely to consider quantum effects than the typical physicist. On the other hand (again, from my limited experience), biologists do tend to have some magical thinking about how statistics (and particularly hypothesis testing) works, but no one is perfect.
Reasoning from first principles cannot span very far in reality, as for starters the complexity of the argument quickly overwhelms our capacity for it. Its numerous other limits have been well-documented.
Logicomix, Gödel Escher Bach are some common entry points.
I'm kinda new here but am surprised I haven't seen this book mentioned more. Maybe I just haven't seen it or it's old news but it seems right up HNs alley.
Biologists stand out because they have already given up on that idea. They may still seek to simplify complex things by refining principles of some kind, but it's a "whatever stories work best" approach. More Feyerabend, less Popper. Instead of axioms they have these patterns that one notices after failing to find axioms for a while.
The largest of the finite simple groups (themselves objects of study as a means of classifying other, finite but non-simple groups, which can always be broken down into simple groups) is the Monster Group -- it has order 808017424794512875886459904961710757005754368000000000, and cannot be reduced to simpler "factors". It has a whole bunch of very interesting properties which thus can only be understood by analyzing the whole object in itself.
Now whether this applies to biology, I doubt, but it's good to know that limits do exist, even if we don't know exactly where they'll show up in practice.
Examples that come to mind: statistical modelling (reduction to nonparametric models), protein folding (reduction to quantum chemistry), climate/weather prediction (reduction to fluid physics), human language translation (reduction to neural networks).
Reductionism is not that useful as a theory building tool, but reductionist approaches have a lot of practical value.
I am not sure in what sense folding simulations are reducable to quantum chemistry. There are interesting 'hybrid' approaches where some (limited) quantum calculations are done for a small part of the structure - usually the active site I suppose - and the rest is done using more standard molecular mechanics/molecular dynamics approaches.
Perhaps things have progressed a lot since I worked in protein bioinformatics. As far as I know, even extremely short simulations at the quantum level were not possible for systems with more than a few atoms.
If you're looking for insults, and declaring the whole conversation a "culture war" as soon as you think you found one, (a) you'll avoid plenty of assholes, but (b) in the end you will read whatever you want to read, not what the thoughtful people are actually writing.
What you are mentioning is called western reductionism by some.
In the western world it does map to Plato etc, but it is also a problem if you believe everything is reducible.
Under the assumption that all models are wrong, but some are useful, it helps you find useful models.
If you consider Laplacian determinism as a proxy for reductionism, Cantor diagonalization and the standard model of QM are counterexamples.
Russell's paradox is another lens into the limits of Plato, which the PEM assumption is based on.
Those common a priori assumptions have value, but are assumptions which may not hold for any particular problem.
Reduce a computer's behavior to its hardware design, state of RAM, and physical laws. All those voltages make no sense until you come up with the idea of stored instructions, division of the bits into some kind of memory space, etc. You may say, you can predict the future of the RAM. And that's true. But if you can't read the messages the computer prints out, then you're still doing circuits, not software.
Is that reductionist approach providing valuable insight? YES! Is it the whole picture? No.
This warning isn't new, and it's very mainstream. https://www.tkm.kit.edu/downloads/TKM1_2011_more_is_differen...
This is true for science and rationalism itself. Part of the problem is that "being rational" is a social fashion or fad. Science is immensely useful because it produces real results, but we don't really do it for a rational reason - we do it for reasons of cultural and social pressures.
We would get further with rationalism if we remembered or maybe admitted that we do it for reasons that make sense only in a complex social world.
Thanks, I might actually go do this :) I recently got exposed to a very persuasive form of "rationalism is a social construct" by reading "Alchemy" by Rory Sutherland. But a theme in these comments is that a lot of these ideas are just recycled from philosophers and that the philosophers were less likely to try and induct you into a cult.
Both advocate the principle of putting out a bold conjecture, test, learn, adapt.
I originally came to this critique via Heidegger, who argues that enlightenment thinking essentially forgets / obscures Being itself, a specific mode of which you experience at this very moment as you read this comment, which is really the basis of everything that we know, including science, technology, and rationality. It seems important to recover and deepen this understanding if we are to have any hope of managing science and technology in a way that is actually beneficial to humans.
Both our biology and other complex human affairs like societies and cultures evolved organically over long periods of time, responding to their environments and their competitors, building bit by bit, sometimes with an explicit goal but often without one.
One can learn a lot from unicellular organisms, but won’t probably be able to reason from them all the way to an elephant. At best, if we are lucky, we can reason back from the elephant.