Essay Abstract
Discreteness will be defined as the set of disconnected, independent, and non-overlapping events or objects. Truly discrete events in reality will have a very difficult time relating to any other event. "Events" can range from the excitation of an electron due to a photon or exchanges of energy that mark change and pervade both classical and quantum physics. If a discrete conception of reality is assumed, relationships, as humans perceive them, can and must be functionally added back into their models, because relation between events is the rule and not the exception in reality. Never the less, the contest question doesn't ask for a mathematical model of reality. It asks whether reality is analog or digital, which on its face is problematic, because these two signifiers mean different things in different contexts. Never the less, it is quite appropriate that the essay, whose subtext asks whether reality is continuous or discrete, frames the question as analog vs. digital. Throughout history, it is exactly because humans understand reality through their technical analogies that reality is not and will never be totally understood. This doesn't mean that reality can't be better understood. But refined understanding is as much a process of unlearning as it is a process of acquiring new knowledge. In showing how digital is a subset of analog, this essay will go on to challenge a two thousand year-old preconception that existence, reality, life, and the mind are functional, closed, and/or discrete-state machines. It will then place a more plausible and parsimonious conception of continuity in its place.
Author Bio
Augustus Bacigalupi studied science at UC Santa Barbara and completed upper division work in physical chemistry. In stead of continuing in academia for science, however, he went on to an architectural design masters. The two disciplines cross-fertilized to reignite a passion for system theory and mind. He started the Institute for Augmenting Minds as a research vehicle to investigate novel, yet rigorous and testable, approaches to synthetic cognition that will challenge and augment existing methodologies.