Collaborative intelligence

Collaborative intelligence characterizes multi-agent, distributed systems where each agent, human or machine, is uniquely positioned, with autonomy to contribute to a problem-solving network. Collaborative autonomy of organisms in their ecosystems makes evolution possible. Natural ecosystems, where each organism's unique signature is derived from its genetics, circumstances, behavior and position in its ecosystem, offer principles for design of next generation social networks to support collaborative intelligence, crowd-sourcing individual expertise, preferences, and unique contributions in a problem-solving process.

Collaborative intelligence is a term used in several disciplines. In business it describes heterogeneous networks of people interacting to produce intelligent outcomes. It can also denote non-anonymous multi-agent problem-solving systems. The term was used in 1999 to describe the behavior of an intelligent business ecosystem where Collaborative Intelligence, or CQ, is "the ability to build, contribute to and manage power found in networks of people." When the computer science community adopted the term collective intelligence and gave that term a specific technical denotation, a complementary term was needed to distinguish between anonymous homogeneity in collective prediction systems and non-anonymous heterogeneity in collaborative problem-solving systems. Anonymous collective intelligence was then complemented by collaborative intelligence, which acknowledged identity, viewing social networks as the foundation for next generation problem-solving ecosystems, modeled on evolutionary adaptation in nature's ecosystems.

Collaborative intelligence traces its roots to the Pandemonium Architecture proposed by artificial intelligence pioneer Oliver Selfridge as a paradigm for learning. His concept was a precursor for the blackboard system where an opportunistic solution space, or blackboard, draws from a range of partitioned knowledge sources, as multiple players assemble a jigsaw puzzle, each contributing a piece. Rodney Brooks notes that the blackboard model specifies how knowledge is posted to a blackboard for general sharing, but not how knowledge is retrieved, typically hiding from the consumer of knowledge who originally produced which knowledge, so it would not qualify as a collaborative intelligence system.

In the late 1980s, Eshel Ben-Jacob began to study bacterial self-organization, believing that bacteria hold the key to understanding larger biological systems. He developed new pattern-forming bacteria species, Paenibacillus vortex and Paenibacillus dendritiformis, and became a pioneer in the study of social behaviors of bacteria. P. dendritiformis manifests an intriguing collective faculty, which could be viewed as a precursor of collaborative intelligence, the ability to switch between different morphotypes to better adapt with the environment. Ants were first characterized by entomologist W. M. Wheeler as cells of a single "superorganism" where seemingly independent individuals can cooperate so closely as to become indistinguishable from a single organism. Later research characterized some insect colonies as instances of collective intelligence. The concept of ant colony optimization algorithms, introduced by Marco Dorigo, became a dominant theory of evolutionary computation. The mechanisms of evolution through which species adapt toward increased functional effectiveness in their ecosystems are the foundation for principles of collaborative intelligence.

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