Imitating humans

A lot of people get confused what the goal of the field of artificial intelligence is. The first thought that can come to mind is to make an intelligence that can pass the Turing test- that is to say: imitate humans. Of course, the Turing test is not almighty, but I digress.

So, why study artificial intelligence? What do artificial intelligence researchers do? First, let’s take a step back and think about other fields.

The quest for “artificial flight” succeeded when engineers and inventors stopped imitating birds and started using wind tunnels and learning about aerodynamics. Aeronautical engineering texts do not define the goal of their field as making “machines that fly so exactly like pigeons that they can fool even other pigeons.”

Artificial Intelligence: A Modern Approach, page 2

The quest for “artificial intelligence” has indeed seen a lot of success from imitating humans. However, the deeper you go, the less interpretable things become. It’s often said that machine learning creates black boxes: huge neural networks that can’t be analyzed due to their complexity.

I think (and hope) that one day methods will improve in this particular area. Perhaps, a way to generalize the analysis of intelligent networks?