Collective Intelligence
In philosophy, reductionism,
seen as the opposite of holism, states that it is possible to explain a complex
system by reduction to its
fundamental parts. If applying this idea to the rather holistic
concept of Web 2.0, without a doubt, collective intelligence
would emerge as the fundamental pattern of the new web.
The newly founded MIT
Center of Collective Intelligence defines collective intelligence as “groups of individuals doing things
collectively that seem intelligent“. Now, thanks to the
Internet, huge numbers of people all over the planet can work together in ways
that were never before possible in the history of humanity and create new
things. Hence, it must be the main object of every Web 2.0 application to
harness such collective intelligence by creating sophisticated architectures of partcipation. Succeeding
in this era begins with understanding two key principles, namely that users add value and network effects can magnify this
value.
Either as a side effect of
their actions or through active participation, people add value to every web
application they use. This could be by directly creating content, such as
contributing to a Wikipedia article or by linking websites, tagging content,
recommending products or by commenting on a blog post.
The discussion about network
effects traces back to Robert Metcalfe and his famous law, which states that the
value of any telecommunications network is
proportional to the square of the number of users of the system. Originally
applied to LAN networks, today Metcalfe’s law convincingly explains the network
effects occurring on the Internet. Metcalfe’s law has been
partially extended by Reed’s law, which, in addition, considers the group
forming capabilities of the Internet.
Any value generated by
users today is therefore vastly amplified by the network effects of the
Internet. Consider for example an article from the Internet encyclopedia
Wikipedia: From an isolated viewpoint a Wikipedia article already embodies real,
user generated value. But only through the network effects caused by the high
level of interlinking, the power of collective intelligence becomes clearly
obvious. Moreover, via network effects, any user-initiated word-of-mouth can
lead to dramatic user growth. By the end of 2006, more than 500,000 users
visited Digg every day, yet the company never spent any money on advertising. Setting network effects by default enables viral
marketing, a best practice of harnessing collective intelligence.
But the concept of
collective intelligence has its critics as well. First and foremost there is
the issue of privacy and liability. People being active on the new web
increasingly reveal their private details, including opinions, relationships,
political views, media, personal history, and so on. These data can be mined by
third parties, including employers or government agencies. The
fact that research has already picked up the topic, shows that such concerns
are real. Consider the paper Semantic Analytics on Social Networks by Boanerges
et al. (2006) that reveals how data from online social networks and other
databases can be combined to uncover facts about people.
To sum up, the best Web 2.0 software must be inherently designed to harness collective intelligence through an architecture of participation. This is accomplished by actively involving users, minimizing the barriers to product adoption and use, and by designing products and features that encourage viral network-driven growth.




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