Special Issue on Collective Intelligence: Journal of Information Sciences

Description

Since the first formal specifications of modern computing machinery 
as laid out by Alan Turing and his contemporary fellows, we have 
been witnessing, during the last three decades, an evolutionary 
path in computing towards more personalized and contextualized 
data and knowledge artefacts. 

The optimal usage of distributed computing, data and knowledge 
resources has always been the means in order to tackle hard 
problems in fields, such as science, engineering and medicine. 
The SETI (Search for Extra-Terrestrial Intelligence, Berkeley, USA) 
project is one prominent example in this category followed by the 
Human Genome project. 

It is no surprise that projects like e-Science, as recently launched 
by the UK government, and the GRID computing are meant to 
create a computing paradigm, where "the computer is the network". In all these approaches, 
however, the problem seems to be well defined and no synergies 
across participants from different cultural and professional 
backgrounds are requested in order to create a solution.

In the early 21st century with the rise of the Social and Semantic 
Web, however, the answer of "what is a network" has been 
relaxed by the inclusion of users and user communities, which 
form social networks via computerized means. Ecosystems of 
humans and machines have been created where the involvement 
of human beings as creators and consumers of data and 
knowledge as well as in problem solving and learning tasks 
has been of paramount importance. Clusters of computers have 
been enhanced by clusters of humans.
 
Formation of social groups follows the same principles of 
social behaviour, common interests, e.g., studies, hobbies, 
games. Wikipedia has been a success story of a collaborative 
environment for knowledge creation and sharing. Facebook, 
MySpace, del.icio.us, Flickr have been further success stories 
of social networking with digital media.

This special issue explores the notion of this human-machine model 
of Collective Intelligence (CI) and its potential to become a new 
computing paradigm for creating solutions or strategies to tackle 
difficult problems, where the synergistic interactions of a group 
of people with diverse cultural and professional backgrounds are 
requested.

This issue aims at studying the move from (system-) collected 
knowledge and intelligence, to collective knowledge and 
intelligence and exploring the challenge of boosting the collective 
IQ of organizations and society where both human and machine 
contribute actively to the resulting intelligence with each doing 
best what they do best.

Original URL

http://www.elsevier.com/authored_subject_sections/P05/CFP/cfp_collectiveintelligence.pdf

http://www.elsevier.com/authored_subject_sections/P05/CFP/cfp_collectiveintelligence.pdf