Sure, but it's helpful to compare our models of artificial intelligence with biological intelligence to see if there's anything to be learned.
We learned how to make airplane wings from the shape of a bird's wing. Of course we should not model our artificial wings so closely as to make a plane with wings that flap. But there was still plenty of stuff to learn by asking the question "why does a bird fly and my contraption doesn't?"
As an explicit example, winglets on airplanes were conceptualized from watching the way bird wings flap, observing the curl on the outer edge of the wing, discovering that it controls vortex formation, and then applying the same concepts to fixed wings.
That kind of thing happens all the time in aerodynamics, fluid dynamics, mechanics, etc — precisely because evolution is a pretty good optimization function, and so “natural” solutions can often be very close to optimal, but using hard-to-discover quirks of physics.
Labwork with as loosely defined goals as life ("reproduce", "accelerate rise of entropy") is costly. It's a robust, deep objective long-term, but extremely inarticulate with poor ROI short-term.
A species of spider nailing down how to live on a particular type of rock on a particular island, in a very particular environment over millions of years, is simply not articulate enough "lab work".
Which is of course not an argument for killing off species. But it's an argument against approaching that moral question from such utilitarian perspective. You might easily end up with results you don't like, once you do the cost/benefit analysis in a less hand-wavy manner.
