This incessant interplay between cognition and feelings, which is to say between cortical and subcortical modules, produces what we call consciousnes… - Michael S. Gazzaniga

The tension felt in the modern world between those who look at the confluence of neuroscientific data, historical data, and other information illuminating our past and those who simply accept received wisdom as their guide in life is real and profound. Yet it may not be as divisive as one would think. It appears that all of us share the same moral networks and systems, and we all respond in similar ways to similar issues. The only thing different, then, is not our behavior but our theories about why we respond the way we do. It seems to me that understanding that our theories are the source of all our conflicts would go a long way in helping people with different belief systems to get along.

Split-brain patients act in a unique way. It appeared the left, speaking hemisphere initially offered a utilitarian response to all scenarios. Thus, if an act had mal-intent but no harm came from it, it was judged as “permissible.” And if an act did not have mal-intent, but resulted in harm, it was judged “forbidden.” Given the clarity of the stories used, this was a jarring result. What is going on? The disconnected left hemisphere is unable to take into account the intent of the person in the stories, acting as if it didn’t have a theory of mind.

The computer scientists Jeff Clune, Jean-Baptiste Mouret, and Hod Lipson did what computer scientists do: they designed computer simulations.23 They used well-studied networks that had sensory inputs and produced outputs. What those outputs were determined how well the network performed when faced with environmental problems. They simulated twenty-five thousand generations of evolution, programming in a direct selection pressure to either maximize performance alone or maximize performance and minimize connection costs. And voilà! Once wiring-cost-minimization was added, in both changing and unchanging environments, modules immediately began to appear, whereas without the stipulation of minimizing costs, they didn’t. And when the three looked at the highest-performing networks that evolved, those networks were modular. Among that group, they found that the lower the costs were, the greater the modularity that resulted. These networks also evolved much quicker — in markedly fewer generations — whether in stable or changing environments. These simulation experiments provide strong evidence that selection pressures to maximize network performance and minimize connection costs will yield networks that are significantly more modular and more evolvable.