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 an Information Framework of Intelligence (IFI) that applies across all systems from physics to biology, humans and AI. Central to this framework is the "intelligence niche", which provides a conceptual basis for understanding constraints on intelligence and the evolution of intelligence. IFI likens intelligence to a real-time calculus, differentiating, correlating and integrating information, and anticipating or predicting future contingencies. Intelligence operates at many levels and scales and IFI distills these into quantitative indicators centered on solving and planning to accomplish goals. Importantly, intelligence can be expressed in informational units, either relative to goal complexity, or to the related concept of goal difficulty, or to an arbitrary reference such as a benchmark. I conclude with predictions and implications of IFI.
Michael Hochberg (Fri,) studied this question.