>
At one point, it was mechanical automata. Then it was hydraulics. Then it was electrical circuits. Now it is computers.Those analogies aren't equivalent. At each step, they got more accurate.
Computing analogies may be flattering to programmer's ego, but it doesn't change the fact that they're also qualitatively different than what came before, because computer science is effectively a branch of physics now.
First, computer science gives us fully abstract mathematical framework that describes calculation independent of the medium - the same CS applies to silicon-based computers, meat-based distributed systems (aka. bureaucracy, societies), neural compute, biochemical compute, substance-less compute implemented using photon interference, whatever. Whatever something is, if we can identify a few patterns we care about, we can view it as a computer. And, like with every math-backed science, as long as the assumptions hold, results of our calculations apply to real-world systems.
Secondly, researchers also found fundamental connection between information and energy, computing and thermodynamics. That means we can take an abstract computer and establish bounds on its energy use - like how much energy it takes to flip a bit - conditioned on some environment (IIRC it's temperature-dependent, at least). This is the part where CS becomes effectively a branch of physics.
Science and mathematics made qualitative jump in the last 100-200 years; we're not making crude analogies to other observed processes now, but rather abstract models with known preconditions and a set framework for reasoning within them. This makes viewing biology through lens of computing a good, useful thing. The important bit is to remember that "all models are wrong, some are useful". If we see that our computing analogies are failing us, perhaps it's time to rethink how we map them to territory. Maybe the most useful computing systems are to be demarked differently, or elsewhere.