The issue is the overall complexity and untestability of such a system: The (human) organism is very very complex and we don't have a model that accurately de

The issue is the overall complexity and untestability of such a system: The (human) organism is very very complex and we don't have a model that accurately describes it in its entirety or even sufficiently enough to do any kind of complex testing. This means that we instead look at the part of the organism that is usefull and we can reasonably model. Systems like AlphaFold2 only solve a tiny tiny part of the problem (i.e. the question "given this amino Acid sequence: how does this Protein look like in 3d"), but it doesn't adress any of the other problems (like: "how does X structure behave in Y environment", "how are the interactions between these N Protein structures", "How do Proteins form complexes?", "how do proteins interact with RNA?", "How do you determine the location of Amino Acid side-chains?" and, most importantly, "what does X do?" ) I liken this to the problems we have in automatic theorem proving: We have formal logics/Type theories that allow for automatic theorem proving, but we still need computer scientists or mathmaticians even for sometimes very trivially complex tasks, because the scale of the problems is way to big to handle automatically. My AI-professor framed it like this "If you have a problem that would take you 10 minutes to solve, a theorem prover will solve it in 50ms. If you have a problem that takes you 20 minutes, the theorem prover won't solve it". We are at a similar, if not worse position, in Biology: We don't even know the system we're working in, yet.