TOWARD COLLECTIVE INTELLIGENCE OF ONLINE ... - Springer Link

J Syst Sci Syst Eng (Jun 2009) 18(2): 203-221 DOI: 10.1007/s11518-009-5095-0

ISSN: 1004-3756 (Paper) 1861-9576 (Online) CN11-2983/N

TOWARD COLLECTIVE INTELLIGENCE OF ONLINE COMMUNITIES: A PRIMITIVE CONCEPTUAL MODEL∗ Shuangling LUO1

Haoxiang XIA2

Taketoshi YOSHIDA1

Zhongtuo WANG2

1

School of Knowledge Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1292 Japan {slluo,yoshida}@jaist.ac.jp 2

Institute of Systems Engineering, Dalian University of Technology, Dalian, 116024, China [email protected] ( ) [email protected]

Abstract Inspired by the ideas of Swarm Intelligence and the “global brain”, a concept of “community intelligence” is suggested in the present paper, reflecting that some “intelligent” features may emerge in a Web-mediated online community from interactions and knowledge-transmissions between the community members. This possible research field of community intelligence is then examined under the backgrounds of “community” and “intelligence” researches. Furthermore, a conceptual model of community intelligence is developed from two views. From the structural view, the community intelligent system is modeled as a knowledge supernetwork that is comprised of triple interwoven networks of the media network, the human network, and the knowledge network. Furthermore, based on a dyad of knowledge in two forms of “knowing” and “knoware”, the dynamic view describes the basic mechanics of the formation and evolution of “community intelligence”. A few relevant research issues are shortly discussed on the basis of the proposed conceptual model. Keywords: Community intelligence, online community, knowledge supernetwork, knowing, knoware

1. Introduction

colony, highly-intelligent collective activities of

In recent years, the concept of collective

the whole colony may emerge from the local

intelligence has been widely discussed from

interactions between the individual ants, which

various aspects. One series of related work is

embody very limited intelligence per se.

inspired

Intelligence”

Accordingly, various bio-inspired algorithms

phenomena that can commonly be observed in

have been developed to solve different social

the biological world. For example, in an ant

and technical problems (e.g. Bonabeau et. al.

by

the

“Swarm

∗

This work is supported in part by National Natural Science Foundation of China under Grants No. 70431001, No. 70620140115, and No. 70871016, respectively. H. Xia would also appreciate the financial support from Chinese Scholarship Council to conduct this international collaboration. Part of the paper was presented in the conference of IEEE SMC 2008.

© Systems Engineering Society of China & Springer-Verlag 2009

Luo et al.: Toward Collective Intelligence of Online Communities: a Primitive Conceptual Model J Syst Sci Syst Eng

204

1999, Kennedy & Eberhart 2001). Inspired by

Second, some groups like business organizations

such Swarm Intelligence, an interesting question

may be well-structured, while some other groups

may be raised: what the collective activities

like

would be in case that the individuals are smarter

weakly-tied. Therefore, a way of research is to

and more knowledgeable than the individuals of

respectively

those biological swarms. In another word, it

collective intelligences with respect to the

would be curious to study the collective

characteristics of the groups, e.g., to study the

intelligence of human groups.

collective intelligence of a team, of a business

Similar with the Swarm Intelligence concept,

online

discussion study

forums

different

are

more

categories

of

organization, and of a special interest group.

underpinning the collective intelligence of

The study of the team-level collective

human groups is the idea that a human group

intelligence or “team intelligence” (e.g. Akgün

may

of

et al. 2008) can be shown in many research

manifest

higher

capabilities

problem-solving

efforts, basically at the intersection of group

than any individual participant of that group

cognitive psychology and teamwork. At the

does, especially when the participants densely

business level, “business intelligence” has

interact

the

become one of today’s buzzwords since it was

computerized communication channels such as

firstly coined in the 1950s (Luhn 1958). Today

the Internet and the World Wide Web. Various

most of the

related endeavors have already been reported as

intelligence” is focused on developing “smart”

a subject of interdisciplinary research at the

IT applications to support business work, whilst

intersection of sociology, psychology, business,

the

and computer science (e.g. see Levy 1994,

intelligence”

Brown & Lauder 2000, Segaran 2007, Szuba

“organization learning” (Argyris & Schon 1978),

2001, MIT CI Center 2008, Johnson 1998).

“collective mind” (Weick & Roberts 1993), etc.

However, despite all those endeavors, the

To enlarge the research scope, some researchers

collective intelligence of the human groups is

have also studied the global-level collective

much more complex than that of the biological

intelligence or the “Global Brain” (Russell 1983,

swarms, and we are now merely at the beginning

Mayer-Kress and Barczys 1993, Heylighen

stage

1995), making an analogy between the network

information-processing

with

of

the

each

inquiry

and

other

of

through

such

collective

intelligence.

work entitled as “business

human-centered are

studies generally

on

“business

branded

as

of billions of individual human beings and

One critical issue for the study of human

computers in the entire human society and the

collective intelligence is to clarify the universe

network of billions of neurons within one single

of discourse. Generally speaking, all types of

human brain.

human groups or collections can be regarded as

The studies on collective intelligence at the

the subject of research. However, human groups

team level, the business level and the global

may significantly differ from one another. First,

level are no doubt important. Besides, the

the size of a group may range from a small team

collective intelligence within another category

to the entire human society of billions of people.

of human groups is also worthy of investigation,


205

i.e. the collective intelligence at the community

theoretical framework from the knowledge and

level, or “community intelligence” as we may

intelligence perspective is still missing in

term. Conceptually, this community intelligence

community studies. There is hence an academic

is located in the middle of a spectrum of

need to construct such a theoretical framework,

collective intelligence from team intelligence

and it may have profound practical implications.

and business intelligence to global intelligence.

Based on the prior considerations, the major

Informally speaking, a “community” refers

focus of the present paper is to incorporate the

to any human group in which the members have

idea of collective intelligence into the studies of

some common characteristics or share some

human communities so as to give an attempt to

interests; for example, it can be formed around

sketch out the basic conceptions of community

the people who have similar hobbies, who share

intelligence. Especially, due to the rapid growth

specific academic interests, or who participate in

of the online communities in which the

a same BBS forum. Such communities are

computer-mediated communications (CMC) are

playing an increasingly important role in our

the prominent means for the community

society.

the

members to interact with each other, in this

explosion of the World Wide Web is the rapid

paper more attention is paid to the intelligence

growth of the different categories of online

of these online communities. With the support of

communities or virtual communities (Rheingold

the

2000), and the collective activities of those

technologies (ICT), the online communities may

virtual

exhibit

Especially,

communities

accompany

often

with

manifest

high

information

and

communication

higher intelligent features than a

problem-solving capabilities. For example, in

traditional community does since ICT firstly

the

a

provides an effective communication channel for

loosely-connected community of programmers

massive exchange of data, information and

who don’t even know each other can collectively

knowledge

develop very complex software products like the

capabilities of the modern ICT may be of great

Linux operating system. In this sense, the

help for the information processing tasks within

exploration of such community intelligence is

the entire community.

Open Source

Software

movement,

and

secondly

the

computation

doubtlessly of practical value. As an academic

This paper is organized as follows. In

response to the increasing role of communities

Section 2 the concept of community intelligence

to human society, a number of relevant research

will be explored under the backgrounds of

efforts have been conducted from various

community

disciplines; and many of the recent efforts on

Thereafter, a theoretical model of community

communities, particularly those around the

intelligence will be described in Section 3,

“community of practice” (Lave & Wenger 1991),

which contains a static or structural view and a

the “community of interest” (Fischer 2001) and

dynamic view. We will shortly discuss the

the like, are closely related to the concept of

corresponding research issues in Section 4 and

community intelligence. However, a clear

conclude the paper in the final section.

and

intelligence

researches.


206

2. Community Intelligence under Backgrounds of Community and Intelligence

leads to the increasing interests on the online communities over the Internet and the Web. Third, the growth of communities and the

One major aim of this paper is to make a

development on the supportive information

plea for the attention to the research subject of

technologies greatly stimulate the corresponding

community intelligence or collective intelligence

studies in the pedagogical and managerial fields,

of online communities. The phrase “community

resulting in the extensive discussions on a bunch

intelligence”

of

is

literally

comprised

of

topics

like

“learning

communities”

“community” and “intelligence”, each of which

(Gabelnick et al.1990), “community of practice”

has been a hot research topic for a long history.

(CoP) (Lave & Wenger 1991), “community of

Therefore, in this section we attempt to discuss

interest” (Fischer 2001), and “knowledge-

the essential characteristics of community

building communities” (Scardamalia & Bereiter

intelligence by examining the basic concepts

1994). The latter two aspects have a close

behind “community” and “intelligence”.

conceptual

connection

to

community

intelligence presented in this paper.

2.1 Community Intelligence in the Context of Human Communities

Underlying the endeavors related to learning communities and CoPs is a shift about the focal

Let’s first try to conceive community

point of learning research, from focusing on

intelligence by observing the “communities”. As

individual information-processing and cognitive

informally defined in the prior section, a human

development to emphasizing “situated learning”

community is any human group in which the

(Lave & Wenger 1991) within the context of

members have some common characteristics or

communities and other social groups. Since

share some interests; the participants of the

learning is one key facet of intelligence, the

community generally have some identity to the

concept of community intelligence is actually a

community. Since German sociologist Ferdinand

natural extension of this “situated learning”

Tönnies’ (1887) conception of Gemeinschaft

viewpoint;

(usually translated as “community”), human

community intelligence is that intelligence is

communities have long been a subject of

inherently social rather than something inside an

research in various disciplines such as sociology,

individual’s brain. Associated with this social

anthropology, and psychology. More recently, as

aspect is an “emergence” aspect of intelligence,

a reflection to the increasingly vital role that

which is the key aspect that differentiates our

they play in society, communities have caught

concept of community intelligence from the

wider attention, most significantly in three

well-discussed “situated learning” concepts. In a

aspects. First, with the rising of the complex

community, the participants exchange their

network research, communities have become

opinions and expertise during the collaborative

one key subject of social network analysis (e.g.

learning and problem-solving processes. The

Wellman & Wortley 1990, Girvan & Newman

collective-level intelligence may then emerge

2000). Second, the rapid growth of the Internet

from such knowledge exchange activities,

and

the

central

point

behind


207

analogous to the emergence of the collective

“memory” system. Third, incorporating all sorts

intelligence of the biological swarms.

of

Thus, the efficient and effective knowledge

computing

technologies

and

(e.g.

information the

processing

Semantic-Web-based

exchange is critical for the formation of

reasoning tools, Web Services and other

community intelligence. The rapid development

Web-based applications), the Web platform has

of the Internet and the Web may greatly facilitate

obtained some capability of intelligence in its

the inter-personal knowledge exchange within a

own right, and such Web intelligence (Zhong et

community; consequently, the virtual and online

al. 2003) may be furthermore combined with

communities are of particular importance.

participants’

Following Porter (2004), “a virtual community

higher-level community intelligence.

human

intelligence

to

form

of

To sum up, the rapid development of ICT has

individuals or business partners who interact

boosted great research interests on human

around a shared interest, where the interaction is

communities, in particular on virtual and online

at least partially supported and/or mediated by

communities.

Under

this

technology and guided by some protocols or

learning-based

view

on

norms.” The virtual community and the online

furthermore be combined with the emergence

community are usually treated as synonyms.

aspect as is in the case of Swarm Intelligence in

However in this paper we would refer an “online

natural systems; and the communities can hence

community” to the community that uses the

be regarded as a collective intelligent system

computer network (and in particular the Web) as

that is comprised of human beings and the

the

supporting

is

defined

primary

herein

as

an

aggregation

communication

media,

while

ICT

background,

the

communities

can

systems.

The

basic

regarding “virtual community” as a more

characteristics of such community intelligence

general phrase referring to the community that is

can then be discussed from the “intelligence”

mediated via all sorts of telecommunication

point of view.

technologies. The discussion of community intelligence

is

then

focused

on

the

Web-mediated online communities as the Web

2.2 Community Intelligence from the “Intelligence” Aspect

has shown great advantages to become the base

In accordance with the prior description, we

platform to enable “true” intelligence. First,

may furthermore try to characterize community

nowadays the Web has grown to be a pervasive

intelligence by comparing it with some other

platform for wide-area communication and

types of “intelligence”.

collaboration,

facilitating

Intelligence is an everlasting topic of

knowledge (and information) exchange and

philosophical debate and scientific inquiry. It is

fusion (i.e. consensus building) between the

beyond the scope of this paper to give a

community members. Second, the Web itself has

thorough discussion on the Intelligence-related

become a massive distributed inventory of

researches. Instead, we give a simplified

information and knowledge so that it partially

4-part-division for the intelligence research field,

fulfills

as shown in Figure 1, trying to “position”

the

hence

greatly

functionality

of

a

distributed


208

community intelligence in the landscape of

intelligence within the intelligence research

“intelligence” researches.

space, as also shown in Figure 1. Therewith, the essential characteristics of

Collective Intelligence Community Intelligence (CI) Biological Intelligence

community intelligence can further be discussed by comparing it with other related categories of

Machine Intelligence

“intelligence”;

and

three

distinctive

characteristics may be identified as to be discussed below.

Individual Intelligence

1) Community Intelligence IS Mixed Collective Intelligence

Figure 1 Community intelligence in the

At the first glance, community intelligence

two-dimension-space of intelligence research

belongs to “Collective Biological Intelligence”, In Figure 1, the intelligence research field is

and this differentiates community intelligence

divided by two axes. The first axis divides the

from Web intelligence and the like, which

field

into

“Biological

Intelligence”

and

belong to the category of “Collective Machine

Intelligence”.

Intelligence

was

Intelligence”. However, community intelligence

the

is not purely biological intelligence. In a

problem-solving capabilities of living creatures,

Web-mediated online community, various ICT

in particular of human beings. We term this type

technologies that may be branded as Web

of intelligence as “Biological Intelligence”, in

intelligence play a critical role to support the

contrast to the “Machine Intelligence” which

collective human intelligence of that community.

was introduced since the blooming of artificial

In this sense, community intelligence is the

intelligence in the 1950s. In the second axis, the

mixed intelligence of “Biological Intelligence”

intelligence research can be classified into

and “Machine Intelligence”.

“Machine

conventionally

Individual

considered

Intelligence

as

and

Collective

Intelligence. This division reflects the shift of the

underlying

assumption

of

intelligence

2) Community Intelligence Is Emergent Intelligence

research from “cognition is something inside an

The second key feature of community

individual’s head” to “mind is social” (see

intelligence is that it is self-organizing and

Preface of Kennedy & Eberhart 2001). Taking

“emergent”; and this may be the distinctive

both axes into account, the intelligence research

feature of community intelligence from “team

field can then be grouped into four parts, i.e.

intelligence” and “business intelligence”.

Individual Biological Intelligence, Individual

Community

intelligence

shares

some

Machine Intelligence, Collective Biological

important characteristics of team intelligence,

Intelligence,

Machine

especially in the sense of shared mental models

Intelligence. Keeping these four parts in mind,

(Cannon-Bowers et al. 1993, Klimoski &

we may give a rough positioning of community

Mohammed

and

Collective

1994).

However,

the

major


209

difference is that team intelligence usually

to model the entire human society as a “brain”.

involves a small group of people and thus it

Comparatively, community intelligence is more

lacks the “swarm effect” that the higher-level

investigable for two reasons: first, the size of a

intellectual

community is usually much smaller than that of

capabilities

emerge

from

the

the entire human society so that the evolution of

interactions of massive participants. One critical difference between a human

“community intelligence” is more traceable;

community (particularly an online community)

second, the members of a community usually

and an institutional organization (e.g. a business

have shared interests and this makes the

company or a governmental agency) is that the

knowledge structure at the aggregate level more

community is more open and flexible. In

focused and more utilizable to actual problem

contrast to the fixed structure (commonly

situations. For this reason, it is the authors’

hierarchical) of an institutional organization, the

contention

community boundary is somehow vague and

intelligence might be a first step to reify the bold

people have more freedom of joining and

vision of the “global brain”.

that

the

study

of

community

leaving the community. As a result, fresh new

In general, the studies of team intelligence,

source of ideas and knowledge may then be

business or organization intelligence (namely the

brought in together with the recruitment of the

human

new members; and this continual flowing-in of

community intelligence and the global brain

new ideas and knowledge is beneficial for

may form a full spectrum of human collective

knowledge innovation inside the community. In

intelligence research. Community intelligence is

this sense, the collective intelligence of an

located somewhere in the middle of this

institutional

better

spectrum. Such middle position may be an

designed and structured, while community

appropriate position in order to study the

intelligence is more dynamic, and better fitted

complexity and the emergent properties of

the characteristics of self-organization and

collective intelligence.

organization

might

be

aspect

of

business

intelligence),

“emergence” as being broadly discussed in the context of complex adaptive systems. In another word, community intelligence is more suitable

3) Community Intelligence Is Knowledgebased Intelligence

to be modeled as a “neural network” of the

The “emergence” property is the common

individual participants, analogous to a human

feature between community intelligence and

brain that is a network of the biological neurons.

Swarm Intelligence in the biological world. The

This feature is generally absent in the current

major difference of these two types of collective

discussions about the organizational intelligence.

intelligence is twofold. First, the participants or

As being mentioned in the introduction

individuals within a human community are

section of this paper, the neural-network

humans, who are knowledgeable and intelligent

metaphor is also adopted in the vision of the

by themselves, while the elemental entities of

“global brain”. However, the study of the global

Swarm Intelligence are usually with very limited

brain may encounter great practical difficulties

intellectual capabilities. Thus, the community


210

intelligent system is essentially a system of

intelligence is based on the shared knowledge

massive intelligent systems (i.e. human beings);

structure of the entire community. Accordingly,

on the contrary the Swarm Intelligence system is

our modeling effort in this paper basically

an emergent intelligent system of massive

involves two parts. The macroscopic structure of

unintelligent entities.

community intelligence is firstly discussed.

Second, the interaction modes in a biological

Then, we try to describe how such macroscopic

swarm are different from the modes in a human

intelligent system forms and evolves through the

community.

microscopic

The

emergence

of

Swarm

Intelligence is usually from the stigmergy-based

knowledge-based

interactions

between the participants.

interactions between the individuals (Balis et al. 1967, Bonabeau et al. 1999). In contrast, the interactions in a community intelligent system

3.1 The Structural Model of Community Intelligence

are knowledge-centric; and the emergence of

Regarding the community intelligent system

community intelligence is essentially due to the

as a knowledge-based intelligent system, our

knowledge exchange and knowledge fusion

contention is that a Web-mediated online

activities. Therefore, as the key research theme

community may self-grow to have at least three

of Swarm Intelligence is to study how the

essential characteristics. First, the community

micro-level stigmergy-based interactions give

should, generally in a distributed fashion,

rise to the emergence of intelligent activities at

contain a memory system that stores information

the macro-level, a fundamental theme of

and knowledge, analogous to the memory

community intelligence is how the community-

system

level intelligence may generate from the

community should have the capability of

knowledge-related activities of the participants

“intelligent” problem-solving, i.e. the capability

or the community members.

of utilizing the stored knowledge to solve

in

a

human

brain.

Second,

the

problems; and the community should commonly

3. A Knowledge-based Model of Community Intelligence

exhibit higher-level intelligent capability than any community member per se. Third, as we

A bunch of related research issues may be

will explain in Section 3.2, this memory system

raised from the prior discussions on community

dynamically evolves, analogous to the cognitive

intelligence. One key issue is to develop a

development of an individual human mind.

theoretical model to answer what the community

Comparing to the human brain which is

intelligence is and how it develops. An attempt

comprised of the interconnected neurons, the

is given in this section to build such a model.

community intelligent system can also be

As discussed in the previous section, our

viewed as a neural network in which the

basic view is that community intelligence is the

“neurons” are the community members (i.e.

emergent collective intelligence based on the

human participants) together with the underlying

local knowledge exchange activities of the

computer systems. Furthermore, this “neural

participants; and the emergent community

network” is not just a network, but a network of


211

networks or a “supernetwork” (Nagurney &

support human communications and interactions.

Wakolbinger

2005).

This Web-based media network is interwoven

supernetwork

basically

This

knowledge triple

with the human network in that it provides a

interwoven networks, namely a technological

cyberspace to promote human communications

network or

consists

of

supports

and collaborations. The nodes of this media

information and knowledge transfer (in a

network (i.e. the Websites) are created by

Web-mediated online network, the Web is the

humans (i.e. the nodes of the human network)

major component of this technological network),

and accessed by other nodes of the human

a human network of community members, and a

network (i.e. other community members).

content network of knowledge and information

Through the Web-mediated communications,

(called the “knowledge network”) which is

knowledge creation, sharing and fusion happen

hosted in humans and computer systems. The

within the human network or the human

structure of such knowledge supernetwork is

community. The collective activities of the

illustrated in Figure 2.

community member would then give rise to the

media

network

that

Knowledge Network

Human Network

emergence of the third network, i.e. the “knowledge network”. The knowledge

network embodies the

collective knowledge of the community. As having been widely discussed in Knowledge Engineering, knowledge may essentially be represented as a networked structure, for example, a semantic network of concepts and Media Network (primarily the Web)

predicative relations, a linked structure of a set of reasoning rules, or elements interconnected

Figure 2 Illustration of the supernetowrk of

by a cognitive schema or a mental model. Thus

community intelligence

the overall knowledge content of a community can naturally be viewed as a network of

In this supernetwork, the media network

“knowledge elements”, or the “knowledge

itself is a two-tier supernetwork comprised of

network”. This knowledge network is an abstract

the physical network of the computers (i.e. the

network with its components (or fragments)

Internet) and the logical network of Websites (i.e.

being actually embedded in the human brains

the Web). To simplify the discussion, here we

(i.e. the nodes of the human network) and the

just consider the logical level structure of this

Websites (i.e. the nodes of the media network).

technological network, i.e. the Web (or more

The overall knowledge network is structured by

strictly a fraction of the Web that is connected to

the conceptual and logical connections of these

the specific human community) and we call it as

knowledge components.

media network since it is the primary media to convey knowledge and information and to

Some components or fragments of the knowledge

network,

which

are

basically


212

classified as codified knowledge, are contained

Individual with Personal Knowledge

in the nodes of the technological network (i.e. the Websites). One Website may connect to

Web-mediated Interactions Knowledge network

multiple nodes of the knowledge network; and one node of the knowledge network can vice versa be stored in multiple Websites. The connections between the Websites and the

Mapping

fragments of the knowledge network exhibit the basic means to link the technological network and the knowledge network. The knowledge network is also connected to the human network

Figure 3 Virtual “memory” structure of the community

in that the largest proportion of the overall

may emerge by interconnecting of the personal

knowledge of the community is still stored in

knowledge of the members. In general, there

human brains although the media network may

exist two basic ways to interconnect the personal

help

codified

knowledge. First, through communications and

knowledge. A single member of the human

interactions, one community member may get

community connects to a sub-network of the

the “know-who” knowledge of some other

entire knowledge network, which actually maps

members; thus he or she may direct seek help

to the personal knowledge structure residing in

from them when encountering problems. By

the member’s brain. The whole knowledge

such

network is then the union of all these

knowledge links may be established between

sub-networks, indicating that the knowledge

these members. The second way of knowledge

network as a whole serves as the “memory” of

interconnection is an indirect way. The members

the intelligent system of the community, which

can “externalize” their personal knowledge to

can furthermore be regarded as the collective

the media network by, for example, posting

“memory”

Such

articles in some Web-space. By reading the

“memory” structure can further be illustrated by

articles, some other members may assimilate the

Figure 3.

embedded knowledge into their own knowledge

contain

of

some

all

amount

the

of

participants.

As shown in Figure 3, the community

direct

knowledge

exchange,

virtual

structure. In this way, the media network then

members have their own knowledge residing in

intermediates

their personal memory systems. Furthermore,

structures of the different community members.

collective knowledge creation, transmission, and

By these direct and indirect connections, the

fusion

take

place

through

to

connect

the

knowledge

Web-mediated

knowledge network of the whole community,

interactions amongst the community members.

which is actually a virtual network embedded in

Through these collective knowledge activities,

the human network and the media network, may

on one hand the community members update

form from the individual knowledge structures

their personal knowledge; on the other hand, a

of all the community members. The structure of

virtual knowledge network at the collective level

this knowledge network is the logical union of


213

the knowledge structures of all the community

and transferred between the individual and the

members.

organization levels. Despite this salient work

The

previously-described

networked

and many further developments thereafter, e.g.

“memory” structure of the online community

Wierzbicki and Nakamori’s (2005) “trefoil”

also implies the utilization of knowledge in the

knowledge creation model, the very basic

solving of the real-world problems. Analogous

notions behind knowledge and knowledge-

to

integrating

related activities and processes are still under

different knowledge sources in human memory,

human

problem-solving

debate in academia. Cook and Brown (1999)

the basic process of “intelligent” problem-

criticize that in the models proposed by Nonaka

solving in the community is accomplished by

as well as other organization-learning advocators

integrating different knowledge sources from the

what is taken into account is “knowledge” being

collective “memory” of the community. Such

regarded as something that people “possess”

knowledge integration and utilization is further

whilst the actions people do during epistemic

accomplished

by

direct

by

indirect

work are largely neglected. Therefore, regarding

communications between the participants or

and

“knowing” as “the epistemic work that is done

community members.

as part of action or practice”, they draw a distinction between knowledge and knowing,

3.2 The Dynamic View of Community Intelligence Based on the prior structural view of

and argue that the actual organizational learning process is a “generative dance” between knowledge and knowing.

“community intelligence”, we can go a further

We agree with Cook and Brown’s ideas with

step to a more dynamic view, to study the

reservations. One of our reservations is that their

evolution

knowledge

concept of “knowing” is somehow confusing. If

network, or in other words to study the cognitive

“knowing” were just a process or “action itself”

development of the community as an intelligent

as they argued, it would be of no necessity to

“living creature”.

conceptually

of

the

community’s

distinguish

“knowing”

from

The development of the knowledge network

knowledge, since it has been a commonsense

is essentially based on the creation, transmission

that knowledge is achieved and used in the

and fusion of knowledge within the community.

process of “knowing”. What makes “knowing”

This subject has been

in the

comparable with “knowledge” is that “knowing”

knowledge management arena for years. For

can also be regarded as some “entity” in its own

example, a well-noted contribution is the

right. From an epistemological view, all an

“knowledge conversion model” or the SECI

individual knows is from his or her experiences

model proposed by Nonaka (1994) in the

or practices; in return, any action of learning and

organizational context. In that model, a learning

doing of an individual is based on what he or she

spiral is presented in which knowledge is

knows. Thus, to an individual, the action of

transformed between the tacit and explicit forms

knowing and the “entity” of what he or she

discussed


214

knows cannot be separated. Furthermore, what

external knowledge sources into an individual’s

an individual knows is intrinsically dynamic

personal “knowing”. Following the pattern of

because of the continuing action of knowing of

the words “hardware” and “software” being

that individual. In this sense we can term what

created, we use a term “knoware” to refer to this

an individual knows as “knowing”, which can

external form of knowledge, in hope to stress

not be apart from the individual’s action of

that

is

some

ontological

“substance”

learning and doing. Another characteristic of this

independent

from

any

individual’s

“knowing” is that it cannot be apart from the

consciousness.

individual who holds it; in another word, here “knowing”

refers

to

personal

knowledge

it

single

This dyad of “knowing” and “knoware” of knowledge implies

a

generic

process

of

endogenously embedded in one’s consciousness.

inter-personal knowledge transfer, as shown in

Thus the development of personal cognition

Figure 4.

essentially means the development of personal “knowing” in the process of learning and doing. The previous understanding of “knowing” implies

that

“knowing” is one

form of

knowledge. Our second contention is that there is another form of knowledge, which is

Personal knowing

Knoware

Externalize Knowledge sender

something “out there” or something existing independent of any individual’s mind. For

Personal knowing

Internalize Knowledge Media receiver space

Figure 4 Generic knowledge transfer process

example, we usually acknowledge that books this

The argument behind the knowledge transfer

“knowledge” contained in a book is very much

process depicted in Figure 4 is that there is no

different from the above-mentioned “knowing”

direct channel to transfer one individual’s

residing in one’s mind. If one individual dies,

personal knowledge (i.e. the personal “knowing”)

the “knowing” of his or her disappears

to the other, since the “personal knowing”

accordingly. Nevertheless, if he or she writes a

adheres to its owner. Instead, the knowledge

book, the “knowledge” contained in the book

sender has to externalize a part of his or her

would remain even after the author’s death. Thus

“knowing” toward some media space (e.g. audio,

the “knowledge” contained in the book can be

video, or texts) to generate some sort of

viewed as some “being” out there. In addition,

“knoware”. Such “knoware” can then be

there is no direct mapping from the knowledge

acquired by another individual; and through a

in the book to an individual’s mind. A book

series of internal cognitive activities, the second

about the superstring theory would mean

individual

nothing to an individual without the knowledge

“knoware” to his or her internal “knowing”; and

background of modern physics. That means,

such assimilation process from knoware to

cognitive endeavors are required to absorb

knowing can also be termed as “internalization”.

contain

“knowledge”.

However,

may

assimilate

the

external


215

With the mediation of “knoware”, in this process

network, or personal “knowing” through the

it would look like that the sender’s “knowing” is

personal cognitive processes. What’s more, the

transferred to the receiver. To conclude, every

collective “cognitive” processes may emerge

interpersonal knowledge transfer process is

from

inherently

interactions amongst the community members.

a

knowing-knoware-knowing

all

sorts

of

communications

and

In the collective cognitive processes, knowledge

transformation process. transfer

is transmitted between the community members

process is then the elementary micro-process

through different types of “knoware”, which is

that eventually leads to the formation and

conveyed by the “media network”. Figure 3

evolution of the collective intelligence at the

illustrates the general picture how the parallel

community

and

This

interpersonal

level.

aforementioned

knowledge

In

other

supernetwork

words,

the

structure

of

community intelligence generates and evolves

repetitive

“knowing-knoware-knowing”

transformation processes lead to the formation and evolution of community intelligence.

through the parallel and repetitive actions of

In Figure 5, the human network and the

such micro-level “knowing-knoware-knowing”

media network is explicit; but the knowledge

transformation processes.

network is virtual. This virtual knowledge network manifests the memory system of the

Virtual knowledge network of knowing and “knoware” Personal knowing

Human Network

Generates Personal knowing

Communications and interactions Virtual space of “knoware”

“intelligent” community, which is comprised of the personal knowing of the community members and the external “knoware” conveyed by the media network. In the case of a Web-mediated online community, much of such “knoware” resides in the Web-space. The evolution of the knowledge network or the “memory” of the community is the result of the

Internalization

Externalization


transformation

and the consequent knowledge transmission, Supports

Media network as human-network-supporter and “knoware”-conveyor

Figure 5 The overall process of community intelligence development

integration (fusion) and creation. Following the dynamic processes of the knowledge network evolution, the community’s collective “memory” is more than the summation of the personal memories of the community members by themselves. Analogous to personal cognition which is built on schemas (Marshall 1995) and mental models (Johnson-Laird 1981), it would

At the individual level, each community

be natural to expect that the formation of the

member develops his or her personal knowledge

collective “schemas” and “mental models”


216

the

inevitably lead to the study of the dynamic

community intelligent system. The emergent

processes of a supernetwork. Such study can be

collective “mental models” may reside in the

respectively carried out at the micro- and

member’s personal minds, as being discussed by

macro-levels following a generative research

various authors in the context of teamwork

fashion (Epstein 1999). At the micro-level, one

(Klimoski & Mohammed 1994). This idea that

key research issue is the deeper analyses of the

community intelligence is generated upon the

knowledge transfer model between human

shared mental models reflects the conceptual

beings,

connection between community intelligence and


team intelligence, as we have discussed earlier.

Further

The community “mental models” may embody

analyses, which may be rooted on social

as the shared understandings which basically

psychological and communicational studies, are

reside in the community members’ minds and

necessary to pursue better understandings of

which

actual knowledge-transfer mechanics through

would

be

an

often

emergent

attribute

property

some

of

degree

of

intangibility or tacitness; but they can also be exhibited in more tangible forms such as the

based

on the

conceptual,

currently proposed

logical

framework. and

empirical

human communications and collaborations. Based on the exploration of the microprocess of interpersonal knowledge transfer, the

written norms and regulations.

macro-level community intelligence may be

4. Some Relevant Research Issues

investigated. We suspect that the Swarm-

In the preceding section we try to develop a

Intelligence-like dynamics may take effect so

conceptual model of “community intelligence”.

that the community would evolve to be an

However, this model is still primitive at the

“intelligent being” from local interpersonal

current stage. Especially, the elaborate dynamics

interactions. However, comparing with any

of how the micro-level knowledge activities lead

process in which Swarm Intelligence emerges,

to the macro-level evolution of community

additional complexity has to be handled to

intelligence has not been well-addressed in the

model the formation and evolution of the

proposed

collective intelligence in human communities.

model

and

extensive

theoretical

explorations are deserved.

Two reasons can instantly be identified. One

Essentially, the generation and evolution of

reason is the inherent structural complexity of

community intelligence rely heavily on the

the involved system. We have to handle the

development

“knowledge

complexity of the structural development of a

network” of the community, as being discussed

supernetwork which contains heterogeneous

in the structural modeling part in the preceding

relationships, as at the center of community

section. This knowledge network is furthermore

intelligence is the idea of a knowledge

dependent on the associating human network

supernetwork of triple interwoven networks. The

and media network; therefore, the study of the

second reason is the complexity of knowledge

knowledge

itself. To explore the dynamics of the formation

of

the

network

virtual

development

would


217

and evolution of community intelligence, we

alleviate the difficulties of “knowing-knoware”

must set the focus on the knowledge processes

transformation. The “knowledge organization”

such as knowledge transmission, integration and

(Hjørland 2003) and “knowledge visualization”

creation,

intangible.

(Eppler & Burkard 2004) technologies may be

Modeling of such knowledge movements in the

of great help in this respect. More computing

social and technological environments would be

tools

a big challenge. Despite the difficulties, we are

comprehensions of group and social cognitions

not pessimistic in conducting researches in this

would also be worthy of pursuing. At the macro-

direction. Various researches on knowledge

level, the problem is how the Internet/Web

diffusion, especially those on agent-based

technologies to support the knowledge activities

modeling of knowledge diffusion patterns, for

in a community, for example in a community of

example what has been done by Cowan and his

e-learning groups. Due to the evolutionary

collaborators (Cowan & Jonard 2004), may give

nature of community intelligence, the emphasis

implications to the study of the knowledge

should be paid on using computing tools to

network evolution in our settings.

promote participation and to facilitate more

which

are

essentially

The second category of research efforts that

that

dynamic

are

and

developed

under

“democratic”

deeper

knowledge

catches our attention is stemmed from a

dissemination, integration, and creation. From

practical and technological point of view. As

this aspect, various technologies under the

discussed

and

umbrella of “Web 2.0” (O’Reilly 2005) and

communication technologies are critical for the

social computing (Wang et al. 2007) may set the

formation

technological cornerstones for further research

earlier, of

the

information

community

intelligence.

A

subsequent question would then be how the

and development.

community and community intelligence can be supported

by

the

information

and

5. Conclusion

communication technologies. More specifically,

In literature, “intelligence” has become a

in our Internet age, how can the Internet and

widely-discussed metaphor to describe various

Web technologies be adopted to facilitate

social entities. The discussions are generally

smoothening

focused on the team and organization levels,

knowledge

transmission,

integration and creation in an online community?

aiming at developing models of the “collective

Again this question may be respectively

mind” (Weick & Roberts 1993), the “knowledge

answered at the micro- and macro-levels. At the

creating

micro-level, the problem is to exploit IT

“organizational learning” (Argyris & Schon

technologies to bridge the knowledge gaps

1978), etc. Another stream of inquiry is on the

between individuals. Conceptually, knowledge is

vision of the “global brain” (Russell 1983). The

transferred from one person to another through a

attention of the present work, nevertheless, is to

“knowing-knoware-knowing” procedure, thus

some extent between the prior two research

the key to smoothen knowledge transfer is to

streams. In comparison with the organizational

company”

(Nonaka

1994),

and


218

level researches, the research on “community

Reading MA

intelligence” would basically focus on larger-

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With

the

observation

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From this aspect, in this paper we call for attention to the possible academic field of community intelligence, by examining it from the

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221

Taketoshi Yoshida Professor at Japan Advanced

Zhongtuo Wang Professor at Dalian University

Institute of Science and Technology, Nomi,

of Technology, Dalian, China. He obtained B.S.

Ishikawa, Japan. He received his Ph.D. degree

from the department of Electrical Engineering,

from the department of Systems Engineering,

Tsinghua

Case Western Reserve University in 1984. He

Academician of the Chinese Academy of

worked for IBM Japan from 1985 to 1997. His

Engineering. His current research interests are in

research interests are in systems science and

knowledge management and knowledge systems

knowledge-handling information systems.

engineering.

University in 1951. He

is

an