Towards a Theory of Intelligences

Intelligence is a human construct to represent the ability to achieve goals. Given this wide berth, intelligence has been defined countless times, studied in a variety of ways and represented using numerous indicators. Understanding intelligence ultimately requires theory and quantification, both of which have proved elusive. I develop a framework for a Theory of Intelligences (TIS) that applies across all systems from physics, to biology, humans and AI. TIS likens intelligence to a real-time calculus, differentiating, correlating and integrating information and at higher levels, anticipating or predicting future contingencies. Intelligence operates at many levels and scales and TIS distills these into a parsimonious macroscopic framework centered on solving and planning to accomplish goals. Notably, intelligence can be expressed in informational units or in units relative to goal difficulty, the latter defined as complexity relative to an arbitrary standard, such as individual ability or a benchmark. I present general indicators for intelligence applicable across system types, based on goal-relevant information, and a simple expression for the evolution of intelligence traits. I argue that “proxies” such as environment, technology, society and collectives are essential to a general theory of intelligence and future study should address population processes including the emergence and evolution of intelligence traits. I conclude with predictions and implications of TIS.