Intelligence as information processing: brains, swarms, and computers
This work addresses the foundational issue of defining and comparing intelligence for researchers in AI and cognitive science, but it is incremental as it builds on existing informationist approaches.
The paper tackles the problem of comparing intelligence across different systems by proposing an information-based framework to measure cognitive organization, rather than focusing on substrates like brains or computers. It applies this perspective to analyze the brain-computer analogy and discuss the evolution of intelligence.
There is no agreed definition of intelligence, so it is problematic to simply ask whether brains, swarms, computers, or other systems are intelligent or not. To compare the potential intelligence exhibited by different cognitive systems, I use the common approach used by artificial intelligence and artificial life: Instead of studying the substrate of systems, let us focus on their organization. This organization can be measured with information. Thus, I apply an informationist epistemology to describe cognitive systems, including brains and computers. This allows me to frame the usefulness and limitations of the brain-computer analogy in different contexts. I also use this perspective to discuss the evolution and ecology of intelligence.