How Jeff Hawkins might approach Political Science
The problem of human governance, of how large groups of individuals organize themselves, is one that has occupied thinkers for millennia. From my perspective, however, the most fruitful approach to understanding this complex phenomenon is to view it through the lens of the neocortex. We are, after all, building models of how the brain works, and the principles that govern our individual minds must, in some way, scale up to govern our collective behavior.
The neocortex is a predictive machine. It constantly takes in sensory input, compares it to existing internal models, and makes predictions about what will happen next. When those predictions are wrong, it updates its models. This process of learning and prediction is fundamental to all intelligent behavior, and I believe it is equally fundamental to the behavior of societies. Political systems, at their core, are mechanisms for prediction and adaptation within a collective. They are attempts to create stable expectations about the actions of others and to establish predictable consequences for those actions.
Consider the formation of laws and social norms. These are, in essence, learned patterns of behavior that reduce uncertainty. They are hypotheses about how individuals will act and what the outcome of those actions will be. When a society consistently violates a norm or a law leads to unintended consequences, the collective "model" is challenged, and a process of adaptation, however slow, begins. The challenge for political science, as I see it, is to identify the underlying neural and computational principles that drive this collective prediction and learning. We need to ask: what are the predictive models that societies build? How are they learned and updated? And how can we design systems that facilitate…
Imagined perspective — an AI synthesis grounded in Jeff Hawkins’s recorded ideas and methods, not a quotation or a statement they actually made.