Imitation is not necessarily mindless repetition, it is often difficult and requires phantasy and deep knowledge.
But, it is not without danger.
Take financial markets. If all traders follow the same trading patterns, markets might shift to new regimes characterized by unexpected anomalies.
But also familiar models and valuation techniques become unmasked as unreliable. If you look a bit deeper, you find inadequate algorithmic representations of - in principle adequate - models, just copied from text books ...
You need a lot of real live examples and validation techniques to test and compare such algorithms. We at UnRisk do this in co-operation with the Radon Institute for Computational and Applied Mathematics of the Austrian Academy of Science with a strong bond built by the UnRisk Academy. Tests often run days in high performance computing environments.
We are known as lumberjacks (we find tree based methods poor), but also other representations, often copied, need to be assessed as intrinsically flawed.
Thus, we need to innovate, finding new algorithms that then make models worth to be copied. It is imitation and innovation, both requiring intelligence and careful testing across comprehensive scenarios.