Very good point from the masterminds behind the Grey Thumb blog. It's a link to Dr. Deborah Gordon's lecture on how ants know to do what they do, see here.
Understanding the inner working of ants' behaviour - and others swarms too - may be important to further the current state of those bio-inspired methods relying on that.
I read her book Ants at Work: How an Insect Society is Organized. She even applied neural networks to model the way that ants interact.
Maybe, the main lesson we may learn from those little insects is directly linked to the fact that ants (and other kinds of swarms) do what they do without a central control and the nest works fine. Sure, when it comes to the evolutionary computation realm, it is always sensible to remember that ants' nests own a very big population and in optimization (and machine learning in general) the population size may be a drawback if set up so big in some problems. Let alone that keeping a small population is very useful when dealing with expensive fitness/objective function evaluations.