Distributed intelligence is an aspect of collaborative intelligence which supports the fact that human cognition could be enhanced in a social context. According to Parker, (2007) it refers to systems of entities working together to reason, plan, solve problems, think abstractly, comprehend ideas and language, and learn. The entities in this order include humans, robots, intelligent systems etc which work in different areas of specialty to accomplish a particular task at hand.

Donald (2004) opined that distributed intelligence is a fundamental framework by which to marry the raw intellectual power of the human mind with appropriate technologies. Fischer (2006) added that it is anchored in the basic assumption that the human mind cannot reach its potential unless it is immersed and embedded in a distributed communication network (with other humans and with artifacts) supported by socio-technical environments.

These definitions support the popular assertion that “knowledge is shifting from individuals minds to a collective social product only imperfectly represented in any one mind.” More so, no single mind or head has all that is required with disregard to environments and technologies. Humans are empowered and intrinsically motivated using artifacts, tools and socio-technical environments as bases for enhanced performance beyond individual capacity. This in no doubt supports the saying of Einstein that “My pencil is cleverer than I”, which gives credence to tools or aids by which accomplishments are achieved.

However, Fischer (2006) outlined numerous claims and arguments which indicate the necessity for a distributed intelligence perspective, including:

- human mental activity is neither solo nor conducted unassisted, even when it goes “inside the head” [Bruner, 1996];
- “how the mind works” is itself dependent on the tools at its disposal (analogous to “how the hand works” not being fully appreciated unless one takes into account whether it is equipped with a screwdriver, a hammer, or a pair of scissors) [Bruner, 1996];
- brain-culture symbiosis, which states that the human brain cannot realize its potential unless it is immersed in a distribution network [Donald, 2004]. This brain-culture symbiosis can lead to “higher intelligence” with the support of “mind tools” that allow people to think previously unthinkable thoughts by integrating the raw intellectual power of the human brain with appropriate technologies; and
- material culture, which externalizes memory and greatly amplifies the permanence and power of distributed cognition, and frees the symbolization process from the limitations of biological memory [Donald, 2004].

In the figure below, Fischer shows the extent to which distributed intelligence has helped in the development of the human mind. 

It can be applied into any area of speciality. For instance in a class where the teacher introduces a new topic/concept (from the trending issues in building technology) say Green Building. The concept of Distributed Intelligence can be employed by asking everyone to make a research and write a five page article on the topic. The submitted articles will be presented and reviewed peer-to-peer. 

The opportunity given to the students will leave them being producers of knowledge each in his/her capacity. Those with abilities to write will focus on writing amazing discoveries, while those who are good with technical details could end up concentrating on the things in that line. But assuredly, at the end of the exercise, it will be amazing how much artifact that could be produced from each person's contribution. This will in no small measure validate distributed intelligence where unity of mind/abilities stands stronger than alone. 

Furthermore, artifacts have been identified as a proof of learning. These artifacts which result from internal motivations (such as proving oneself) present external representations (a show of how better we have become). Fischer (2006) suggests that in order to support distributed intelligence effectively, we need criteria to assess the quality, learnability, and effectiveness of external representation, including the following attributes:

- long-lasting (not ephemeral), allowing incremental improvements over time;
produced, modified, reproduced, and evolved not only by experts or technologists, but by the owners of the problem;
- communicable over spatial, temporal, and conceptual distances;
- possessing computational capabilities (e.g., support for multimodal representations, or context-awareness of users, tasks, and situated environments); and
- exploiting and complementing the strength of humans (e.g., sometimes visualizations make a big difference and sometimes they do not).

It is worth noting that collaborative intelligence which distributed intelligence tends to achieve has the above mentioned criteria. It is imperative therefore to state that ‘every one of us is something but none of us is everything’. It suffices to say that our natural diversity, differences, specialization etc can be utilized genuinely through the use of technological support and management in order to make the best out of the system.

References:

Donald, M. W. (2004) "Is a Picture Really Worth a 1,000 Words? Review essay of David S. Staley, Computers, Visualization and History: How New Technology Will Transform Our Understanding of the Past." History and Theory: Studies in the Philosophy of History, 43(3), pp 379-385.

Bruner, J. (1996) The Culture of Education, Harvard University Press, Cambridge, MA.

Parker, L. E. (2007). Distributed Intelligence: Overview of the Field and its Application in Multi-Robot Systems. Association for the Advancement of Artificial Intelligence (www.aaai.org). Available at http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.75.7008&rep=rep1&type=pdf

Fischer, G. (2000) " Distributed Intelligence: Extending the Power of the Unaided, Individual Human Mind," available at http://l3d.cs.colorado.edu/~gerhard/papers/avi-2006.pdf