A defining feature of complex systems is their ability to encode, store, process, and employ functional information. This feature encompasses the elementary gradient sensing capabilities of single cells to the large-scale perceptual and decision-making abilities of large populations of neurons.
Intelligent systems employ both intrinsic and extrinsic mechanisms of storage and processing to efficiently solve adaptive challenges. These solutions include volatile chemical signals supporting ant foraging, beehives coordinating collective navigation, through to a vast variety of human inventions.
The ecologically grounded limitations of organically evolved natural intelligences has led to pressures in favor of the development of culturally evolved artificial intelligences. The most obvious examples of these limitations are the constraints of working memory and the shortcomings of rudimentary mental arithmetic.
In technological settings, many features associated with intelligent behavior are outsourced to artifacts that serve as a community resource. These include language, mathematics, calculators, modern digital computers, and a growing library of inferential software.
Possible discussion topics for this meeting include:
- What are the economic implications of new forms of newly emerging forms of intelligence?
- How should we think about the differences and commonalities among natural perceptual, motor, and “analytical” intelligence?
- Is there a general intelligence that supports all of these functions or is intelligence modular in a fundamental sense?
- What are the strategic and competitive implications of newly emerging forms of intelligence?
- Which features of organic intelligence and its modules lend themselves to artifactual and artificial amplification and replacement?
- What novel forms of AI can be derived from a careful consideration of the full diversity of Natural Intelligences?