The Mechanism Me, as should be obvious from the title, pays homage to Asimov’s classic I Robot series. It is my respectful attempt to update the venerable “positronic brain” with a robotic system that reflects current trends in science and technology.

Asimov’s prodigious foresight in envisioning a “positronic brain” anticipated the field of computational neuroscience by half a century. Only now can we start to fill in some of the details on how it might actually work.

There is a tremendous amount of work going on today with the goal of building an artificial brain, i.e., The Human Brain Project. A lot of the previous work in this area seems to have overlooked a key understanding coming out of the neurosciences: The human brain is not an isolated organ. Intelligence, sentience and consciousness are all the product of an integrated human knowledge system that includes the whole body. Building an artificial brain will not lead to something that thinks like us. An artificial brain needs to be housed in an artificial body before anything like human intelligence, sentience or consciousness can emerge.

Human-like artificial general intelligence requires the sentience that can only be provided by a body. Developmental neuropsychology tells us that the neurological substrates of logic and reason, primarily located in the cerebral cortext, are not yet functional in the first few years of life. Despite this, infants and toddlers learn at a prodigious rate. If their intellects are not even working yet, how are they learning? They are learning with their entire nervous systems, not just their brains. Bodies have their own separate memory systems. What are they learning? They are learning the foundational knowledge upon which all other knowledge will later be based.

How do we know what we know?

From day one, we learn from experience. Specifically, we learn from feeling our bodies as they experience their environments. Through repeated and ongoing exposure to stimuli our bodies learn associations, that is, what goes with what. Some forms of stimulation are associated with good feelings, some with bad. The parts of our knowledge system that control our bodies, our body-brains, are designed to learn to make movements that produce desired effects (comfort, pleasure) and inhibit those that produce undesired effects (discomfort, pain).

As infants, our limbs randomly move about and encounter things. We discover that some things move when touched and some don’t, some things are graspable and some aren’t. The things that move can be within our reach or move out of it. Through efforts to reach, we learn to distinguish between near and far, the core concept of the near-far dichotomy. As we explore whatever comes within reach, we learn that things have differing qualities, requiring different sorts of interactions. We learn distinctions, the easiest always involving opposite poles of a dichotomy. Some things feel warm and some cold. Soft things are safe against our skin but hard things can hurt. We learn the concept of the soft-hard dichotomy. Some things we can lift or move, others we can’t: The light-heavy dichotomy.

We gradually figure out that through our own muscle movements we can change our orientation to the world around us. We can roll over, push our eyes away from the ground and gain a higher perspective. Higher still and we’re sitting up, but at constant risk of falling down again. Now we know up-down. All of this learning is done by the subcortical regions of our nervous systems, as our cerebral cortex and hippocampal memory systems are not yet functional. In other word, our foundational knowledge is not the conscious knowledge of the reasoning brain, but rather the sensory, emotional and procedural knowledge acquired by the deeper body-brain regions through felt experience.

Through our body’s experience of its environment we learn all the core dichotomies that form the foundation for all the knowledge we will ever possess. Hunger-satiation, pleasure-pain, hot-cold, each dichotomy creates the raw material for analogy. Something can be not physically hot but have a quality that evokes the experience of hot, and we understand what that means. Something with no mass can be described as “heavy” and the description makes sense because we know what heavy feels like. Over time our dichotomies become more sophisticated and complex and form the basis for increasingly abstract analogies. Something new must be like something we already know, grounded in primal sensory experience, before we can make any sense of it. This is the contribution of the body-brain to human knowledge, and without this body-based knowledge, no machine can ever know the world as a human does.

It used to be thought that if a database of useful information about the world was extensive enough, it would enable a computer to understand things. There is no magical threshold of complexity at which consciousness spontaneously arises. We now know that there are specific conditions that must be met. Consciousness is both embodied and relational. Self can only be known from the experience of being-in-the-world provided by a body, and self can only be recognized in relation to other. Similar bodies produce similar experiences, and so create the ground for a common experience of consciousness, a commonality that enables us to know ourselves by reflection and to relate to each other as beings. No matter how extensive the database, all a computer can do is regurgitate the data. It can’t understand the data in the human sense. Artificial Intelligence, as originally conceived, can never acquire consciousness.

Strong A.I. and Sentience

Artificial General intelligence, or strong A.I., will require sentience, which requires a sensor-rich body and a brain. The body is needed to accumulate and feed real-time sensory data to the brain. Attaching sensors to robots is as old a robotics, but human-like sentience requires and enormous amount of sensory data. A lot of good work is going on in the field of machine sensing, at least with the primary senses.

To complete the system, the brain must be able to process sensory data into meaningful perceptions that can be remembered, compared and contrasted; things that A.I. happens to do very well. In order for an android to be intelligent in a way that we can relate to, it must have a fully integrated brain-body system. Like us.

Next: biomimetics.