Using IT to quickly make a simulated brain
This is an incredibly broad question, but I admire your spark of curiosity so I'm going to give you a quick answer anyways.

Firstly, there is no defined steps for modelling parts of the brain. The laboratory I was a member of created Spaun. Spaun is the world's largest functioning brain model and uses biologically plausible neurons as the foundation for it's computation. The methodology for creating the most recent iteration of this model varies wildly from part-to-part. The vision system was adapted from Deep Learning Convolutional Neural Networks, the basal-ganglia and thalamus came from an anatomical model and the working-memory model came from engineering analysis of dynamical systems. None of these could have come from evolutionary algorithms or any other sort of algorithm known to humanity at this point.

Another way of modelling the brain (mostly the human behaviour part of it) is ACT-R, which doesn't use neurons at all. Once again, there's no algorithm for evolving this system and interestingly it's the foundation behind a lot of the intelligent systems you mentioned.

The search for evolution and learning methods for groups to gain intelligence is generally called Artificial Life (ALife).

You'll notice that there's a bunch of different levels to approach the problem of modelling the brain. Your friend was at the biological bottom-up level, ACT-R is at the behavioural top-down level and Spaun is the weird hybrid. Although all of these systems use IT in some way (Spaun was built with a Python library called Nengo, ACT-R is written in LISP), the processes for creating these systems cannot be automated and would require the creation of a general artificial intelligence.