Collective Intelligence

hive mind by Luke Ramsey

Collective intelligence is a shared or group intelligence that emerges from the collaboration and competition of many individuals and appears in consensus decision making in organisms (including some bacteria) and computer networks. The term appears in sociobiology, political science, and in context of mass peer review and crowdsourcing web applications (e.g. Wikipedia). This broader definition involves consensus, social capital, and formalism such as voting systems, social media and other means of quantifying mass activity.

Everything from a political party to a public wiki can reasonably be described as this loose form of collective intelligence. The notion of collective intelligence has also been called ‘Symbiotic intelligence.’ A precursor of the concept is found in entomologist William Morton Wheeler’s observation that seemingly independent individuals can cooperate so closely as to become indistinguishable from a single organism. Wheeler saw this collaborative process at work in ants that acted like the cells of a single beast he called a ‘superorganism.’

In 1912, French sociologist Émile Durkheim identified society as the sole source of human logical thought. He argued, in ‘The Elementary Forms of Religious Life’ that society constitutes a higher intelligence because it transcends the individual over space and time. Other antecedents are Soviet geochemist Vladimir Vernadsky’s concept of ‘noosphere’ (the sphere of human thought) and author H.G. Wells’s concept of ‘world brain.’ Peter Russell, Elisabet Sahtouris, and Barbara Marx Hubbard (originator of the term ‘conscious evolution’) are inspired by the visions of a noosphere — a transcendent, rapidly evolving collective intelligence — an informational cortex of the planet. The notion has more recently been examined by French media scholar Pierre Lévy.

American author Howard Bloom has discussed mass behavior – collective behavior from the level of quarks to the level of bacterial, plant, animal, and human societies. He stresses the biological adaptations that have turned most of this earth’s living beings into components of what he calls ‘a learning machine.’ In 1986 Bloom combined the concepts of apoptosis (programmed cell death), parallel distributed processing, group selection, and the superorganism to produce a theory of how collective intelligence works. Later he showed how the collective intelligences of competing bacterial colonies and human societies can be explained in terms of computer-generated ‘complex adaptive systems’ and the ‘genetic algorithms,’ concepts pioneered by American computer scientist John Holland. Bloom traced the evolution of collective intelligence to bacterial ancestors 1 billion years ago and demonstrated how a multi-species intelligence has worked since the beginning of life. Ant societies exhibit more intelligence, in terms of technology, than any other animal except for humans and co-operate in keeping livestock, for example aphids for ‘milking.’ Leaf cutters care for fungi and carry leaves to feed the fungi.

Ecological philosopher David Skrbina cites the concept of a ‘group mind’ as being derived from Plato’s concept of panpsychism (that mind or consciousness is omnipresent and exists in all matter). He develops the concept of a ‘group mind’ as articulated by Thomas Hobbes in ‘Leviathan’ and German experimental psychologist Gustav Fechner’s arguments for a collective consciousness of mankind. He cites Durkheim and French philosopher and Jesuit priest Teilhard de Chardin as a thinker who has developed the philosophical implications of the group mind.

Environmental activist Tom Atlee focuses primarily on humans and on work to upgrade what Howard Bloom calls ‘the group IQ.’ Atlee feels that collective intelligence can be encouraged ‘to overcome ‘groupthink’ and individual cognitive bias in order to allow a collective to cooperate on one process—while achieving enhanced intellectual performance.’ George Pór of the London School of Econmics defined the collective intelligence phenomenon as ‘the capacity of human communities to evolve towards higher order complexity and harmony, through such innovation mechanisms as differentiation and integration, competition and collaboration.’ Atlee and Pór state that ‘collective intelligence also involves achieving a single focus of attention and standard of metrics which provide an appropriate threshold of action.’ Their approach is rooted in Scientific Community Metaphor.

Atlee and Pór suggest that the field of collective intelligence should primarily be seen as 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, though group theory and artificial intelligence have something to offer. 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.

American activist and a former CIA officer Robert David Steele Vivas in ‘The New Craft of Intelligence’ portrayed all citizens as ‘intelligence minutemen,’ drawing only on legal and ethical sources of information, able to create a ‘public intelligence’ that keeps public officials and corporate managers honest, turning the concept of ‘national intelligence’ (previously concerned about spies and secrecy) on its head.

According to business strategists Don Tapscott and Anthony D. Williams, collective intelligence is mass collaboration. In order for this concept to happen, four principles need to exist: Openness (sharing ideas and intellectual property – though these resources provide the edge over competitors more benefits accrue from allowing others to share ideas and gain significant improvement and scrutiny through collaboration); Peering (horizontal organization as with the ‘opening up’ of the Linux program where users are free to modify and develop it provided that they make it available for others — peering succeeds because it encourages self-organization – a style of production that works more effectively than hierarchical management for certain tasks); Sharing (companies have started to share some ideas while maintaining some degree of control over others, like potential and critical patent rights — limiting all intellectual property shuts out opportunities, while sharing some expands markets and brings out products faster); and Acting Globally (the advancement in communication technology has prompted the rise of global companies at low overhead costs — the internet is widespread, therefore a globally integrated company has no geographical boundaries and may access new markets, ideas and technology).

Political parties mobilize large numbers of people to form policy, select candidates, and finance and run election campaigns. Knowledge focusing through various voting methods allows 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. Military units, trade unions, and corporations satisfy some definitions of CI — the most rigorous definition would require a capacity to respond to very arbitrary conditions without orders or guidance from ‘law’ or ‘customers’ to constrain actions. Online advertising companies are using collective intelligence to bypass traditional marketing and creative agencies. Improvisational actors also experience a type of collective intelligence which they term ‘Group Mind.’

One measure sometimes applied, especially by more artificial intelligence focused theorists, is a ‘collective intelligence quotient’ (or ‘cooperation quotient’)—which presumably can be measured like the ‘individual’ intelligence quotient (IQ)—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 Szuba from the AGH University in Poland proposed a formal model for the 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.

In social bookmarking (also called collaborative tagging), users assign tags to resources shared with other users, which gives rise to a type of information organization that emerges from this crowdsourcing process. The resulting information structure can be seen as reflecting the collective knowledge (or collective intelligence) of a community of users and is commonly called a ‘Folksonomy.’ Recent research using data from the social bookmarking website Delicious, has shown that collaborative tagging systems exhibit a form of complex systems (or self-organizing) dynamics. Although there is no central controlled vocabulary to constrain the actions of individual users, the distributions of tags that describe different resources has been shown to converge over time to a stable power law distributions. Once such stable distributions form, examining the correlations between different tags can be used to construct simple folksonomy graphs, which can be efficiently partitioned to obtained a form of community or shared vocabularies.

Games such as ‘The Sims Series,’ and ‘Second Life’ are designed to be non-linear and to depend on collective intelligence for expansion. This way of sharing is gradually evolving and influencing the mindset of the current and future generations. For them, collective intelligence has become a norm. In Terry Flew’s discussion of ‘interactivity’ in the online games environment, the ongoing interactive dialogue between users and game developers, he refers to Pierre Levy’s concept of Collective Intelligence and argues this is active in video games as clans or guilds in MMORPG constantly work to achieve goals. Henry Jenkins proposes that the participatory cultures emerging between games producers, media companies, and the end-users mark a fundamental shift in the nature of media production and consumption. The increase in user created content and interactivity gives rise to issues of control over the game itself and ownership of the player-created content. This gives rise to fundamental legal issues, highlighted by legal activist Lessig.

Because of the Internet’s ability to rapidly convey large amounts of information throughout the world, the use of collective intelligence to predict stock prices and stock price direction has become increasingly viable. Websites aggregate stock market information that is as current as possible so professional or amateur stock analysts can publish their viewpoints, enabling amateur investors to submit their financial opinions and create an aggregate opinion.

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