My primary interest in robotics is modeling and exploring human intelligence. As I started on my study of Artificial Intelligence in the early 90’s, I decided that a box on a table couldn’t be intelligent because it is disconnected from physical reality. One can define a tree as a particular type of plant, or list its qualities such as shade production and carbon filtering, or one can list its uses such as lumbar and edible nuts. But all these qualities require their own further definition.  At the end of the day, this is just symbol manipulation and is ungrounded from meaning.  Early attempts at AI tried to build meaning from complex semantic dictionaries and failed to produce intelligence. Those approaches are used today for automated parsing of natural text, but the only “intelligence” they show is in the logic implicit in the complex set of relationships built into the symbol definitions.  To bring shared meaning to the symbols we use, it helps to physically connect them to the shared reality we experience.  If you want to know what a tree is, you have to be embodied in the world — you have to be able to hug it.

Hugging trees might sound like a silly basis for intelligence, but it stems from the basic cycle of autonomy: perception — thought — action.  The classic approach to AI that focuses on symbolic manipulation fails because it only expresses “thought.”  Connecting to the external shared reality through perception and action gives thought meaning.

We can define living beings by our ability to act — to create change in the world or ourselves. Stones do not act — they react — they are passive.  In contrast, all living things perform actions in some way.  We can easily see these actions in the higher mammals, but even the simplest bacteria or plant creates action.  Plants grow and change, transport fluids, mature and die.  These are all actions. Plants’ capabilities of perception and thought are more limited than ours — but not non-existent.  Consider the Venus Fly-Trap for perception and trivial decision making in a plant.

Just like thought by itself does not get one far in life, action on its own without perception or thought is not very functional.  Early industrial machines are a great example of action without perception — they do one thing very well and will keep doing it even to the point of destruction if the environment changes.  Charlie Chaplin perfectly captured the essence of action without perception or thought in his movie “Modern Times,” where he depicts an automated Feeding Machine:

And this Ketchup Dispensing Robot is an excellent example of a modern robotic system which lacks perception:

A theory held by many researchers is that the primary purpose of the brain is to control motion.  At first this might seem odd — the motor cortex is only a small part of the brain, and there are so many other functional aspects that don’t seem related.  But, as you can see from the above discussion, perception and thought are prerequisites for intentional motion. When we build autonomous robotic systems we find that simple motor controllers are not enough.  To move in the real dynamic world (not just a lab or factory) we need to sense and understand the environment we are moving through.  We need sensors — eyes, ears, noses, etc. But just sticking a camera on a robot is not enough either — that just gives you a bunch of colored dots. Interpreting that data might start by reconstructing a 3D scene from those dots — but even that is not enough.  What is the scene?  What dangers lie around you?  What opportunities?  Where should you move?  What might be tasty and good for you if you ate it?  What might eat you?  Every act we do, from eating to talking and emailing requires an intentionally coordinated set of motions.  In every moment, even when laying on the bed thinking, we have to choose from the infinite set of possible actions which of those actions we will manifest. That is what our brain does.  All the complex decisions, desires, motivations, social norms, emotions, habits, and other “higher level function” boil down to the simple question of deciding how our physical body will interact with the physical world. It all ends up being about motion.

And so my approach to understanding human intelligence is to start by understanding how we move.  Evolution is economical in reusing systems, so it seems fitting that the processes that developed to control simple physical motion get replicated and reused in more and more complex ways in order to orchestrate more complex and abstract forms and intentions behind our motion.  And this is what we find in the makeup of the brain:

Finally, in the most complex brains, a large portion of the cortical mantle, called the associational cortex, is devoted to generating and processing events that are not directly related to sensory inputs or motor outputs. Remarkably, the cortical modules in the associational areas are not fundamentally different from the sensory or motor cortical areas, an indication that local computation in cortical modules is quite similar. [Gyorgy Buzsaki, “Rhythms of the Brain” 2006, p 46.]

What I find really fascinating is that this connection between motion and our intellect and emotion goes even deeper than just reused cortical modules.  In fact, it is hard to really separate the brain from the body — as one explores physical healing (massage, energy work, etc) it is common to find that specific memories of emotional trauma are carried in the body for years.  There are many disciplines (motion therapy, Somatics, etc) that study the interplay of how the physical body carriers and holds thought and emotion patterns, and how to shift them. The interplay of the body and emotion and thought is a rich topic that we will be exploring here for a while.  For now, the key thought is that while we love and enjoy all the fancy experiences we can have with our brains —  the brain was made for motion.