An Information Framework of Intelligence

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 present 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 realtime calculus, differentiating, correlating and integrating information, and anticipating or predicting future contingencies. I propose a classification of the levels and scales at which intelligence operates. Focussing on measurable macrosopic phenomena, I develop quantitative indicators of intelligence based on abilities to identify and resolve subgoals. Intelligence is reflected by acquired goal-useful information 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.