Collective intelligence

Definition
Collective intelligence, as characterized by Tom Atlee, Douglas Engelbart, Cliff Joslyn, Francis Heylighen, Ron Dembo, and other theorists, is a working form of intelligence which overcomes "groupthink" and individual cognitive bias in order to allow a collective to cooperate on one process&mdash;while maintaining reliable intellectual performance. In this context, it refers to robust consensus decision making, and may properly be considered a subfield of sociology.

Another CI pioneer, George Pór, author of The Quest for Collective Intelligence (1995), defined this phenomenon in his Blog of Collective Intelligence as "the capacity of a human community to evolve toward higher order complexity thought, problem-solving and integration through collaboration and innovation."

A less anthropomorphic conception is that a large number of cooperating entities can cooperate so closely as to become indistinguishable from a single organism, achieving a single focus of attention and standard of metrics which provide an appropriate threshold of action. These ideas are more closely explored in Society of Mind theory and sociobiology, as well as in biology proper. Another approach builds on work in sociology and anthropology of science as a foundation, e.g., Scientific Community Metaphor.

General concepts
While group and artificial intelligence have something to offer, collective intelligence is at its roots a human enterprise, in which mind-sets, a willingness to share, and an openness to the value of distributed intelligence for the common good, are paramount. Individuals who respect collective intelligence are confident of their own abilities, and recognize that the whole is indeed greater than the sum of any individual parts.

Maximizing collective intelligence relies on the ability of an organization to accept and develop "The Golden Suggestion", which is any potentially useful input from any member. Groupthink often hampers collective intelligence by limiting input to a select few individuals or filtering potential Golden Suggestions without fully developing them to implementation.

Knowledge focusing through various voting methods has the potential for many unique perspectives to converge through the assumption that uninformed voting is to some degree random and can be filtered from the decision process leaving only a residue of informed consensus. Critics point out that often bad ideas, misunderstandings, and misconceptions are widely held, and that structuring of the decision process must favor experts who are presumably less prone to random or misinformed voting in a given context.

History
Collective intelligence, which has antecedents in Pierre Teilhard de Chardin's concept of "noosphere" as well as H.G. Wells's concept of "world brain," has more recently been examined in depth by Pierre Levy in a book by the same name, by Howard Bloom in "Global Brain," by Howard Rheingold in "Smart Mobs," and by Robert David Steele Vivas in "The New Craft of Intelligence". In the latter, the concept of all citizens as "intelligence minutemen," drawing only on legal and ethical sources of information, are able to create "public intelligence" that keeps public officials and corporate managers honest, coming together to turn the concept of "national intelligence" (previously about spies and secrecy) on its head.

Collective intelligence is an amplification of the precepts of the Founding Fathers, as represented by Thomas Jefferson in his statement, "A Nation's best defense is an educated citizenry." During the industrial era, schools and corporations took a turn toward separating elites from the people they expected to follow them. Both government and private sector organizations glorified bureaucracy and, with bureaucracy, secrecy and compartmentalized knowledge. In the past twenty years, a body of knowledge has emerged which demonstrates that secrecy is actually pathological, and enables selfish decisions against the public interest. Collective intelligence restores the power of the people over their society, and neutralizes the power of vested interests that manipulate information to concentrate wealth.

Examples of collective intelligence
The best-known collective intelligence projects are political parties&mdash;which mobilize large numbers of people to form policy, select candidates, and to finance and run election campaigns. Military units, trade unions, and corporations are focused on more narrow concerns but would satisfy some definitions of a genuine "C.I."&mdash;the most rigorous would require a capacity to respond to very arbitrary conditions without orders or guidance from "law" or "customers" who constrain actions tightly. One interesting proponent of the rigorous view is Al Gore, the United States Democratic Party candidate for President in 2000, who noted that "the US Constitution is a program that lets us all do together what we could not do separately."

Another example of such a "program" is the Four Pillars of the Greens, which together constitute the grounding of a consensus process to form policy within a green party or allied movement. This has proven highly successful in organizing the Global Greens to compete in elections with more established parties appealing to interest groups.

Mathematical techniques
One measure sometimes applied, especially by more artificial intelligence focused theorists, is "collective intelligence quotient" (or "cooperation quotient"), which presumably can be measured like the "individual" intelligence quotient (IQ)&mdash;thus making it possible to determine the marginal extra intelligence added by each new individual participating in the collective, thus using metrics to avoid the hazards of group think and stupidity.

In 2001, Tadeusz (Ted) Szuba from AGH University in Poland proposed the formal model for phenomenon of Collective Intelligence. It is assumed to be an unconscious, random, parallel, and distributed computational process, run in mathematical logic by the social structure. This theory was fully published in the book Computational Collective Intelligence by Szuba T. (Wiley book series on parallel and distributed computing, 420 pages, Wiley NY, 2001).

In this model, beings and information are modeled as abstract information molecules carrying expressions of mathematical logic. They are quasi-randomly displacing due to their interaction with their environments with their intended displacements. Their interaction in abstract computational space creates multithread inference process which we perceive as Collective Intelligence. Thus, a non-Turing model of computation is used. This theory allows simple formal definition of Collective Intelligence as the property of social structure and seems to be working well for a wide spectrum of beings, from bacterial colonies up to human social structures. Collective Intelligence considered as a specific computational process is providing a straightforward explanation of several social phenomenon. For this model of Collective Intelligence, the formal definition of IQS (IQ Social) was proposed and was defined as "the probability function over the time and domain of N-element inferences which are reflecting inference activity of the social structure." While IQS seems to be computationally hard, modeling of social structure in terms of a computational process as described above gives a chance for approximation. Prospective applications are optimization of companies through the maximization of their IQS, and the analysis of drug resistance against Collective Intelligence of bacterial colonies.

Opposing views
Skeptics, especially those critical of artificial intelligence and more inclined to believe that risk of bodily harm and bodily action are the basis of all unity between people, are more likely to emphasize the capacity of a group to take action and withstand harm as one fluid mass mobilization&mdash;shrugging off harms the way a body shrugs off the loss of a few cells. This strain of thought is most obvious in the anti-globalization movement and characterized by the works of John Zerzan, Carol Moore, and Starhawk, who typically shun academics. These theorists are more likely to refer to ecological and collective wisdom, and to the role of consensus process in making ontological distinctions, than to any form of intelligence as such, which they often argue does not exist, or is mere cleverness.

Harsh critics of artificial intelligence on ethical grounds are likely to promote collective wisdom-building methods, e.g. the new tribalists, the Gaians. Whether these can be said to be collective intelligence systems is an open question. Some, e.g. Bill Joy, simply wish to avoid any form of autonomous artificial intelligence and seem willing to work on rigorous collective intelligence in order to remove any possible niche for AI.

Recent developments
Growth of the Internet and mobile telecom has also highlighted "swarming" or "rendezvous" technologies that enable meetings or even dates on demand. The full impact of such technology on collective intelligence and political effort has yet to be felt, but the anti-globalization movement relies heavily on e-mail, cell phones, pagers, SMS, and other means of organizing before, during, and after events. One theorist involved in both political and theoretical activity, Tom Atlee, codifies on a disciplined basis the connections between these events and the political imperatives that drive them. The Indymedia organization does this in a more journalistic way, and there is some coverage of such current events even here at Wikipedia.

It seems likely that such resources could combine in future into a form of collective intelligence accountable only to the current participants but with some strong moral or linguistic guidance from generations of contributors - or even take on a more obviously political form, to advance some shared goals.

At a practical level, the skill of group facilitation has developed since the 1990s into a profession for people who specialize in assisting a group in optimizing its processes, creativity, and decision making. Research has shown that groups with a facilitator consistently achieve better decisions than unfacilitated ones.