Knowledge, Economy, Technology and Society: The Politics of Discourse

David RooneyUQ Business School and Centre for Social Research in Communication, University of

Queensland

11 Salisbury RdIpswich, Qld 4350

d.rooney@business.uq.edu.au(07) 3381 1042

or(07) 3378 7534

Knowledge, Economy, Technology and Society: The Politics of Discourse

Abstract: The WSIS is centrally interested in knowledge and has defined for itself a mission that is broadly humanitarian. Its development ‘talk’ is, rightly, replete with notions of equity, preserving culture, justice, human rights and so on. In incorporating such issues into knowledge society and economy discussions, WSIS has adopted a different posture towards knowledge than is seen in dominant discourses. This study analyses the dominant knowledge-related policy discourse using a large corpus of knowledge-related policy documents, discourse theory and an inter-relational understanding of knowledge. I show that it is important to understand this dominant knowledge discourse because of its capacity to limit though and action in relation to its central topic, knowledge. The results of this study demonstrate that the dominant knowledge discourse is technocratic, frequently insensitive to the humane mission at the core of the WSIS, and is based on a partial understanding of what knowledge is and how knowledge systems work. Moreover, I show that knowledge is inherently political, that the dominant knowledge discourse is politically oriented towards the concerns of business and technology, but that an emancipatory politics of knowledge is possible.

Keywords: culture, technocratic discourse, information, knowledge society, knowledge economy, political economy

1.1 Introduction

Since the 1950s Development Communication has taken as it primary goal improving

the use of communication processes and the media to foster development within

emerging economies (see for example, Dissanyake 1986; Freire 1983; Lerner 1958;

Rogers 1976; Schiller 1969). In more recent years Development Communication and

The World Summit on the Information Society (WSIS) have become interested in the

role of information and knowledge in development. This new set of concerns means

that new research is needed in Development Communication and the WSIS to

promote an understanding of knowledge for researchers, policy professionals and

practitioners who serve the needs and concerns of developing nations (Rooney et al.

2003a). This article therefore outlines a sociological theory of knowledge (or

knowing) and discusses the discursive formations and politics of the dominant

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knowledge discourse to demonstrate troubling aspects of the construction of

knowledge policy globally.

This study analyses a large corpus of knowledge-related policy documents sourced

from a range of industrialised and industrialising countries, and demonstrates that the

global discourse on knowledge is technocratic (McKenna et al. 2000). I show that the

central concerns of the dominant knowledge discourse are about business and

technology rather than knowledge (and culture and society). This discourse is

significantly different to the central concerns and indeed the emancipatory agenda

(Habermas 1972) of WSIS participants and UNESCO more generally (see Rooney in

press). I seek to explore this technocratic discourse and lay bare its politics, values

and assumptions about knowledge and the development process.

2.1 KNOWLEDGE, DISCOURSE AND DISCURSIVE STRUCTURES

Knowledge is an elusive thing and the precise nature of it has been earnestly debated

for at least three millennia. Salient for Development Communication is that

knowledge has very clear links to development and language (Chomsky 1968;

Graham in press; Rooney et al. 2003a; Welbourne 2001). Foucault argues that the

‘approved’ knowledge of the day is a key means of exercising power to mobilise

various economic, social and cultural resources, and that this power becomes manifest

in the language of the dominant discourse (Foucault 1972; Foucault 1979). Thus, if

knowledge is related to power then ideas about knowledge, expressed in discourse,

must be researched to render visible how power is being exercised in knowledge

discourse and in whose interests it is being exercised (Habermas 1972).

Within discourse, discursive formations are the cultural codes and ways of organising

thought (including values) – in written and unwritten codes – that shape how we

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communicate and our attitudes; allowing some thoughts and actions but occluding

others (Foucault 1972). Discursive formations are about how what we communicate is

presented and read as likely, desirable, important, permissible, surprising, serious or

comprehensible (that is, evaluations) (Halliday 1985; Lemke 1998). In short, if we

understand the discourse we understand its authors’ values, what they aspire to and

the (taken for granted) assumptions they make revealing any unacknowledged

political or ideological agenda in the discourse.

Fuller (1995) argues that knowledge societies are not industrial societies permeated by

knowledge, but that knowledge societies are permeated by industrial values. Those

industrial values are inexorably associated with commercialised technology and

assumptions about the ability of technology to bring about change. Discourse theory

suggests that discursive formations in the dominant knowledge discourse will serve to

foreground the interests of those who benefit from that technical and commercial

expertise, the technocrats (McKenna et al. 2000). It also suggests that the values of the

technocrats will be expressed in discourse to effect particular ways of thinking and

behaving that promote their interests. This discourse is technocratic discourse

(McKenna et al. 2000). Discourse theory also predicts that insofar as power and

authority is exercised through discourse, the interests and values of ‘other’ groups will

simultaneously be rendered silent and their members unable to act to fully advocate

and implement their values and preferred practices. In technocratic discourse this is

done by invoking the authority, prestige and mystique of science. Discourse analysts

argue that specific value choices are ignored and undiscussed (Habermas 1972;

Lemke 1995, pp. 69-70). In addition, Lemke (1995, p. 71) shows that the value of the

outcomes of technocratic prescriptions are not adequately discussed either.

Technocrats only argue that what they claim is necessary not why it is necessary.

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In the context of this study it is relevant to note that technocrats are specifically those

who adopt “discourses of expert knowledge” and transform them into exhortations in

policy (Lemke 1995, p. 58), and to acknowledge the critique that while technocrats

are aligned with functionalist and instrumental values, aspirations and practices, they

tend to construct knowledge to primarily have commercial or industrial forms and

values, and to be an object that must be commodified (Gee et al. 1995, p. 10; Graham

in press). In terms of the WSIS it is the inclination and tendency of technocrats to

occlude and be insensitive to world-views and value systems outside their purview,

and to leave themselves politically, intellectually and ethically unchallenged to pursue

narrowly instrumental economistic outcomes that is of most concern (McKenna et al.

2000). I argue that under these conditions the full scope of what might be possible in

knowledge societies cannot be seen or realised.

3.1 KNOWLEDGE

Before returning to the topic of a narrow technocratic discourse, it is important to

spend some time discussing the sociological nature of knowledge. The social

epistemology of Fuller, and discourse theory discussed above clearly links

knowledge, language and power. In doing this it is suggested these things inter-relate

as a living system (Graham et al. 2001). More specifically, they demonstrate that

discourse (and therefore knowledge) arises from sets of social relations. An explicitly

inter-relational approach to the sociology of knowledge is therefore relevant to the

analysis of knowledge discourse. In doing this, the inter-relational approach is

concerned to demonstrate the generative mechanisms that create and diffuse

knowledge (Rooney et al. in press).

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In what follows I explain knowledge in a way that treats knowledge as inter relational

in which the inter relations provide the generative mechanisms for knowledge. These

elements are the points at which knowledge systems can be assessed and evaluated,

and where interventions can be made. To this end, I make four important observations

about the nature of knowledge.

First, a fundamental and inescapable observation about human knowledge is that it

necessarily implies the existence of people and societies. However, if knowledge is

fundamentally dependent on the existence of societies, societies are also dependent on

knowledge. The coherence of societies requires ideational and conceptual processes

between interacting agents (Hay 2001). A sociology of knowledge, therefore, must

account for the effects on knowing of the structures and organisation of social

relations and vice versa. What results in these interactions is some form of social

organisation and structure (e.g. hierarchies, social networks, communities, etc.). These

hierarchies, networks, and other forms of relations and positions are the social-

relational context of knowing.

Second, ideas are associative by nature and necessity. Ideas, theories, beliefs,

propositions, understandings, memories, etc. are connected to and depend on other

ideas, theories, etc. to be meaningful. The inter relational processes of knowing,

therefore, also occur at the intertextual and intersubjective level in which a

background of ideas, cognitions and hermeneutics held collectively by a set of

interlocutors is critical

Insofar as ideas, theories and beliefs form a shared phenomenological background in

which people think and act, this context is decidedly cultural. Culture can be defined

as a shared pattern of beliefs that lead to relatively stable patterns of behaviour and

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attitudes of groups held together by taken for granted assumptions about things such

as value, necessity and power. Knowledge, theories, beliefs, etc., therefore, are not

only phenomenological and social but are cultural, political and ideological.

Third, knowledge is often said to be situated (Lave et al. 1991) with its own

situational logic (Archer 1996). Moreover, knowledge has meanings and purposes that

are sensitive to the physical location of the knowers, the time in which they exist and

the history from which they have emerged. Importantly, therefore, the situation is a

place plus its associated history and physical objects (built and natural). In this way,

the physical aspects of situations include technology, and other elements of the built

environment including buildings, religious and cultural objects, furniture and even,

such things as the design and colour of those objects, and the natural environment or

geography (Burke 2000). Objects are of great importance to knowledge because at the

very least we develop beliefs about those objects (Bhaskar 1989, p.101), but also

because of them.

Finally, we must consider enactment, the process of acting on our knowledge,

intuitions, memories and so on. The ways in which we enact knowledge are

predictable and unpredictable, intentional and unintentional, rational and irrational.

Enactment focuses attention on the contradictions and paradoxes associated with the

use of knowledge, and it foregrounds the messy and in which we act with our

knowledge. For example, enactment is done more or less intentionally and

purposively. However, the degree to which one can be intentional is dependent on

ones conscious, intuitive, reflexive and strategic mental powers. Moreover, any

intentional decisions will likely involve both intuitive and explicit strategies; and that

both intuitive and explicit strategic choices are likely to also rely on incomplete or

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misleading information and imperfect knowledge. Also at issue is that the human

mind is boundedly rational (Simon 1955; 1991), and has finite biological limits to

how much it can learn, understand and use (Campbell 1974). The commonplace

results of these limitations are such things as errors of judgement and fact, indecision,

misinterpretation and so on. Enactment, therefore, is the fallibly intentional and

purposive political application of knowledge.

In addition, purposes are strongly directed by roles and positions (however voluntary

or involuntary they are) (Archer 1995, p. 201-3). Different people, because of their

different positions and roles, are also imbued with vested interests and different

degrees of power.

The picture of knowledge presented here is one that encompasses the full range of

human experience. To think of knowledge without considering memory, beliefs,

intuition, ideas, ideology, etc. is misguided and unrealistic. In addition, while

knowledge is important to creating and sustaining society and culture, society and

culture are important to creating and sustaining knowledge. Consequently, the links

between knowledge, society and culture must be considered. Moreover, when

knowledge is to be fostered to aid development, its political economy cannot be

ignored. It is also critical to observe that in this framework technology and economy

are important but encompass only a narrow part of the spectrum of factors that

animate knowledge systems. A knowledge policy that focuses only on this limited

part of the spectrum of knowledge’s generative mechanisms is at best incomplete, and

at worse incompetent and dangerous. Because of the complexity and infallibility of

enacting knowledge, it is not simply knowledge that is needed to create a knowledge

society but wisdom. Against a technocratic background, wisdom is needed because of

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its transcendent nature, its insightfulness and ethics (Baltes et al. 2000; Rooney in

press; Rooney et al. 2003b) are the critical human faculties for a knowledge society.

4.1 Computer Assisted Text Analysis

The data analysed in this study comes from a 1.3 million word corpus of knowledge-

related policy documents compiled from local, state, national, and supranational

institutions throughout the industrialised and industrialising world. Documents were

placed in the corpus because they relate to any of the inter-related topics of the

knowledge economy, knowledge society, information economy, information society

or the creative economy. Individual documents in the corpus were obtained from a

range of countries, including the United Kingdom, Australia, New Zealand, Canada,

USA, Greece, Denmark, Finland, France, Germany, Holland, Switzerland, South

Africa, Japan, Korea, Malaysia and India, and supranational policy organisations like

the OECD and the European Union. While the corpus was subjected to a grounded

analysis using computer assisted text analysis software, as each document was

sourced, the investigator read it for appropriateness and understanding. A deeper

understanding of the corpus has been developed since collection because it has

previously been analysed by the investigator using different techniques and theory,

and to answer other questions as part of a larger program of research into knowledge-

based economy discourse (Graham et al. 2001). Interpretation was also aided by the

investigators theoretical knowledge in relation to knowledge itself, political economy,

social theory and communication theory. The analytical method used in this study is

in degrees therefore both inductive and deductive.

The knowledge-related policy corpus was analysed using Leximancer. Leximancer is

a computer assisted text (content) analysis application that uses a machine-learning

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technique. The machine-learning process learns in a grounded fashion what the main

concepts in a corpus are and how they relate to each other. Content analysis can be

done as either conceptual (thematic) analysis or relational (semantic) analysis.

Leximancer does both, identifying concepts in the corpus and how they interrelate. In

identifying concepts and showing how they interrelate, Leximancer uses word

frequency and co-occurrence counts as it basic data. Leximancer builds its analysis by

using the frequency data and data about the co-occurrence of concepts to produce a

concept co-occurrence matrix. Once a concept has been identified Leximancer then

builds a thesaurus of words that are closely related to the concept thus giving the

concept its semantic or definitional content.

A picture of the relational (semantic context) characteristics of the concepts is created

in two important ways. First, data is created relating to the direct co-occurrence of

concepts. Direct links between concepts are measured establishing the strength of

relations between concepts. The more times a concept occurs directly with another,

the stronger the relationship. Second, a more complex picture emerges when data

about what is semantically related to a concept is related to other concepts and their

co-occurring words. Thus Leximancer can compare a concepts thesaurus with other

concepts’ thesauri. In this way indirect links between concepts are accounted for,

meaning that a significant semantic relationship can exist between concepts even

when there are, in the main, only indirect relationship between them. Overall, then,

Leximancer rank orders concepts, and tells the investigator about the strength of

association between concepts and semantic similarity between concepts.

Finally, Leximancer stochastically calculates a map of the concepts in the corpus.

This visualisation technique enables the investigator to see, in a global representation,

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what are the important concepts in the corpus and relationships between these

concepts. Hence, concepts that are directly related but are not necessarily strongly

semantically linked and can be far apart on the concept map while concepts that are

strongly semantically related will be close to each other on the concept map.

Therefore, concepts that occur in very similar semantic contexts tend to form clusters.

The map is then used by the investigator to present an overall representation of the

corpus and to guide interpretation.

The investigator can also ‘drill’ down through a concept, into its thesaurus of words,

and then directly into the chunks of text where those concepts and words are found.

This allows the investigator to easily interrogate the text and interpret it in light of his

or her own reading of the corpus and to apply various linguistic analytical techniques

such as discourse analysis.

In using machine-learning to do the above analysis, Leximancer builds a library of

concepts in the text in a grounded fashion according to a set computational criteria.

Leximancer was asked to find 80 concepts; stop words were removed automatically;

three sentence blocks were set as the boundaries for measuring contextual

relationship; bi-gram sensitivity was set at moderate (4); and the threshold for

establishing if a word is admissible as an additional concept seed (the learning

threshold) was set at normal (14).

An important feature of this kind of analysis is its reliability. Leximancer addresses

reliability in two ways. First, it affords stability and second, reproducibility. Stability

in Leximancer is equivalent to intercoder reliability. That is, the automated and

deterministic machine-learning phase will be highly consistent no matter how many

times a corpus is processed and reprocessed (coded and recoded) by the application. It

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can therefore be said that Leximancer has a high level of coding stability.

Reproducibility in the context of Leximancer is seen in its consistency in classifying

text given the same coding scheme. Consistent classifying manifests in a consistently

constructed stochastic concept map. In other words if the map is calculated and

recalculated a number of times the researcher can inspect the each new map for its

consistency with previous maps. If maps are dissimilar the researcher can alter any of

the computational criteria being applied to the corpus in an endeavour to make the

map consistently reproducible. Leximancer produced highly stable maps for this

study.

Additional analysis was performed using Pajek social network analysis software. The

Leximancer map data file was fed into Pajek to create a network map that displays the

direct links between concepts in greater detail than does Leximancer. Pajek was set to

draw a network with all links with a value of less than 0.2 removed. This was done to

remove the weakest links making the network more easily readable.

5.1 Representing the Corpus

Because public policy (including economic policy) should contribute to making a

better society and because knowledge-related policy (including that with an explicit

economic or technological agenda) should seek to make a better society through

knowledge, it is reasonable to expect that any knowledge-related policy aims to

address a broad range of social, cultural, environmental and economic issues and

interests. In general terms, then, achieving knowledge society or economy status

might be found by, for example, making a society more knowledgeable and wise

about business, culture and the environment. This position is reinforced in light of the

sociology of knowledge presented above. However, based on such assumptions and in

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light of the questions that discourse theory raises it is reasonable to assume that the

knowledge-related policy corpus should be inspected thematically (conceptually) and

relationally (semantically) to determine if a broad agenda like this exists within it.

Using Leximancer, thematic analysis is facilitated by inspecting the rank ordered

concept list and then spending some time reviewing the thesauri of words that define

the concepts identified (Table 1). The thesaurus for a concept shows the most strongly

(directly and indirectly) related words to the concept they are defining.

Table 1. Top 20 ranked concepts

Concept Absolute count

Relative count

Thesaurus

 service 2585 100% networks, information, telecommunications, e-commerce, internet, infrastructure, access, government, public, provision,

 information 2561 99% technology, service, society, government, development, public, internet, e-commerce, networks, communication

e-commerce 2276 88% service, internet, government, should, business, information, networks, access, public, development

 internet 1842 71.2% service, e-commerce, networks, information, access, government, public, should, technology, business

 technology 1535 59.3% information, research, regulations, medical, reproductive, development, related, science & technology, service, should

 government 1307 50.5% information, e-commerce, service, should, internet, public, online, industry, technology, development

 should 1281 49.5% e-commerce, service, technology, government, public, information, internet, related, law, medical

 networks 1200 46.4% service, telecommunications, internet, information, infrastructure, access, e-commerce, public, provision, development

 public 914 35.3% service, information, networks, should, technology, e-commerce, internet, government, policy, telecommunications

 development 847 32.7% information, technology, service, research, e-commerce, networks, government, internet, science & technology, public

 business 792 30.6% e-commerce, information, service, assets, intangible assets, internet, reporting, government, industry, should

 access 778 30% service, internet, networks, information, e-commerce, public, telecommunications,

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government, should, infrastructure industry 774 29.9% industries, sectors, market, products, rate,

service, e-commerce, information, countries, , manufacturing

 market 736 28.4% service, industry, products, sectors, countries, industries, goods, rate, manufacturing, basic

 telecommunications 632 24.4% service, networks, infrastructure, provision, public, access, regulatory, market, competition, member

 research 543 21% technology, information, development, science & technology, should, medical, regulations, networks, studies, related

 products 543 21% industry, market, industries, rate, sectors, goods, service, countries, manufacturing, basic

 policy 522 20.1% information, public, government, technology, should, competition, service, development, case, framework

 infrastructure 511 19.7% service, telecommunications, networks, provision, should, public, information, access, regulatory, development

international 490 18.9% e-commerce, internet, should, law, service, information, countries, rules, networks, government

Of the 20 most important concepts, governance (government, law, regulation, public,

policy), technological (e-commerce, networks, telecommunications and infrastructure)

and commercial (business, industry, market, products, service) concepts feature most

prominently, and are clearly central to the concerns of the authors in the corpus, while

less room is given to cultural and social concerns (public, access). Given that it is a

corpus of policy-related documents, the emphasis on governance is not surprising.

However, the rather sharp focus on technology and business is notable and is

consistent with arguments about technocratic discourse. Service, e-commerce,

internet, technology, networks, telecommunications, infrastructure, business, industry,

market and products are all highly ranked concepts and also feature in the thesauri.

Concepts that appear to be social policy oriented such as access, public and medical

occur in the thesauri and concept list, and so they are important but they are not the

most prominent. Concepts that might relate to culture, intellection and education also

appear outside the top 20 concepts (intellectual, communication, environment,

cultural, learning). Some concepts that at face value look social policy oriented are not

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unambiguously so. For example, the concept, access, is primarily about access to

ICTs (internet, networks, information, e-commerce, infrastructure) rather than directly

about access to, for example, education, welfare and cultural activities, all things a

theory of knowing suggest might also be of concern in knowledge-related policy. I

will return to this point below.

A perspective on how concepts are semantically contextualised is obtained by

interpreting the relational (semantic) representation of the data using Leximancer’s

concept map. To make the concept map more understandable in the first instance, the

proportion of concepts displayed has been reduced from 100% (of 80 concepts) to the

top 8% (Map 1). This is the lowest level at which a number of discernable semantic

clusters has formed. Reduced to this level, only the 27 most important concepts are

shown. While more clusters will emerge at a higher level of resolution (Map 2), these

clusters can be considered indicative of the most important discursive semantic

markers in the corpus.

Map 1 (at 18%)

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By virtue of their proximity to each other, we can say that clusters A, B and C are

closely semantically related, while cluster D is semantically distant from the others.

Cluster D is clearly concerned with business and commercial issues (business,

products, industry, markets). Cluster A appears to be concerned with innovation

policy (research, technology, policy), and cluster B is concerned with policy and

government (policy, regulation, government, law). Cluster C is concerned with

telecommunications infrastructure (telecommunications, infrastructure, networks).

Based on this, we can confirm that the primary semantic categories of the corpus are

business, governance, and technology. In addition, we can say that the Business

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D

A

B

C

cluster is less meaningfully (less semantically) connected to the other clusters. At this

level of resolution there is no cluster that has knowledge as its central focus.

Much more can be discerned from the concept map when the resolution is set to 54%

(Map 2).

Map 2 (at 54%)

At this level of resolution much more of the data is represented on the map and it

therefore provides a more detailed view of the corpus and the opportunity to refine

interpretations. To this end, not only are there more concepts on the map but there are

three new semantic clusters; (e) Internationalisation (country, internationalisation); (f)

Knowledge & Skills (knowledge, skills, education); and (g) Finance (finance, capital,

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f Knowledge & Skills

g Finance

A Innovation Policy

B Law & Policy

C Telecoms Infrastructure

D Business

e Internationalisation

Business ICT

GovernanceEnactment

assets). It is also possible to label the original clusters; (A) Innovation Policy, (B) Law

and Policy, (C) Telecommunications and (D) Business. With the additional data it is

now possible to characterise the general orientation of each of the four quadrants of

the map. The top left quadrant is concerned with issues of Business (business,

finance), the top right quadrant is concerned with issues related to ICTs (e-commerce,

internet, online, telecommunications), the bottom right quadrant is concerned with

Governance (policy, law, rules, government), and the bottom left quadrant is

concerned with Enactment (skills, work, science and technology, progress, creation).

This characterisation of the concept map says much about the key concerns of policy

makers in relation to knowledge, reinforcing the view that they privilege a business

and technology agenda. Clearly, policy makers see an important role for technology in

achieving their goals. This is well illustrated if we look at the ICT, Governance and

Enactment quadrants where there is considerable overlap between the Innovation

Policy, Law and Policy, and Telecommunications Infrastructure clusters. Governance

concerns are semantically linked to ICT concerns (communications, infrastructure,

intellectual property, market, regulation), and science and technology more generally

(science_technology, technology). It is suggested again that policy makers see

technology as the conduit for delivering benefits to their communities. This raises

concerns about assumptions based on an attitude resembling technological

determinism (Feenberg 1991). This will become more evident below when I examine

specific excerpts from the corpus.

Enactment covers what the corpus regards as the most important way to enact

knowledge. Tellingly, this quadrant is heavily biased towards vocational skills

training and to technological development in the economy. It is concerned with

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research but more particularly industrial research and development. This feature of the

corpus will become more obvious as I deal with specific examples of text from the

corpus. It is also important to note that while medical research is featured, social

scientific and humanities research is not. It is also important to note the semantic

distance between the Knowledge and Skills cluster to the other clusters.

In understanding semantic distance, it is instructive to consider how concepts and

concept clusters are inter-linked. Considering how concepts are linked demonstrates

much about how the authors’ of the corpus have reasoned the connections between

concepts. Indeed, it says much about how they (fail to) argue their cases, and what

they assume and ask us to take for granted. To do this I have employed Pajek social

network analysis software to specify the details of the links between concepts. Apart

from a 90 degrees axis rotation, the Pajek network graph (Map 3) is broadly consistent

with the Leximancer concept map and it amplifies several critical features of it. The

most important Leximancer semantic clusters can be discerned in the graph and links

between concepts are plotted.

Map 3. Conceptual Network (links valued at less than .2 removed)

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The first of the amplified features is the considerable level of cross linking between

the Telecommunications Infrastructure, Law and Policy, and Innovation Policy

clusters. This is indicative of the level of direct association between these clusters

made in the text. Specifically, repeated claims are made that government has a role to

play in fostering the development, provision and use of technology. This attitude can

be explored by examining exemplars in the corpus. The following excerpt illustrates

some of the consistently made claims in the corpus.

Looking to the near future, we can envisage an Australia where: The processes of work, commerce, learning, education and training, social interaction and government are being transformed by communication and information technologies; in which all Australians are able to take part in the opportunities brought home by the global information economy. All Australians, particularly those outside the major cities, have unprecedented access to communications, information, government services such as health and education, entertainment and culture, goods and services from around the country and the world; and have the skills and knowledge to access what they need online, and to make creative contributions to the stock of ideas and products available. (CITA1.txt~1.html#S1_112)

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Telecoms Infrastructure

Business

Innovation

Knowledge & Skills

Finance

Law & Policy

Demonstrated here is the view that government must work harder for technologizing

the community. Specifically, technology transforms the community, creates

opportunities and access, and makes people creative. This is highly technologically

deterministic; the claim is that it is technology that stimulates desirable outcomes.

How technology does this is not explained and what else is needed to achieve these

outcomes is not seriously considered. It assumes that technology’s importance is self-

evident. The same document makes claims about the role of technology in more

specific terms. It sees the role of education policy largely in terms of providing ever

changing technology skills for the information economy.

Vocational education and training is a key hub into the Australian community and into industry. Its challenge is to harness its significant potential to provide flexible responses for constantly changing learning environments. To be effective and provide a foundation to foster the information economy, training organisations will require the advanced information infrastructure to develop, trial and deploy applications, content and services for new technology and communications. (CITA1.txt~1.html#S1_195)

The basic assumption, that vocational training is good for the community and

industry, is highlighted in the opening sentence. This is followed by a nebulous

statement about potential, flexibility, change and learning, which has an unexplained

connection to the next sentence that advocates the necessary deployment of new and

advanced technology. The vagueness of the argument notwithstanding, it can be

interpreted as a case where we are asked to take for granted that vocational training,

particularly if it employs new technology, will make creative employees for the

information economy. Again, it is taken for granted that one thing leads to another.

The same strategy is evident in the next excerpt.

In order for the education system to be adapted to the requirements of the 21st century, the government promotes the familiarisation of students with computers and multimedia, in all education levels, and trains teachers in the new technologies. (GREECE1.txt~1.html#S1_45)

The document continues by claiming:

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In the digital age, economic competition is increasingly based on technology and knowledge. (GREECE1.txt~1.html#S1_45)

The technological imperative is repeated here. Knowledge of computers, multimedia

and new technologies provided by the education system are required because

competitiveness (in business) is based on technology and knowledge. Much is left

unstated here. What are the grounds for making these assertions? What else could the

education system be concerned about? Why is economic competition so important?

And why are technology and knowledge regarded as essential factors for improving

competitiveness?

The Business cluster is notable for the fact that the concepts in it are tightly

interlinked suggesting that claims being put forward here are internally consistent.

However, judging by the moderate level of outlinking to other clusters we are being

asked to accept the central role of business in a knowledge society using a limited

range of claims that provide even less explanation of how benefits are delivered than

other clusters do. The following excerpt is quite matter of fact about the necessity for

government to support business needs and promote the idea that competition and

market forces are intrinsically good.

[T]he Administration successfully concluded the WTO Basic Telecommunications negotiations, which will ensure global competition in the provision of basic telecommunication services and will address the many underlying issues affecting online service providers. During those negotiations, the U.S. succeeded in ensuring that new regulatory burdens would not be imposed upon online service providers that would stifle the deployment of new technologies and services. As the WTO Agreement is implemented, the Administration will seek to ensure that new rules of competition in the global communications marketplace will be technology neutral and will not hinder the development of electronic commerce … The Administration will also seek effective implementation of the Information Technology Agreement concluded by the members of the WTO in March 1997, which is designed to remove tariffs on almost all types of information technology. Building on this success, and with the encouragement of U.S. companies, the administration is developing plans for ITA II, in which it will to seek to remove remaining tariffs

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on, and existing non-tariff barriers to, information technology goods and services. (USframe.txt~2.html#S1_274)

Global competition to assist U.S. companies to sell technology, telecommunications

services and conduct e-commerce by deregulating global markets are the central

concerns here. The core of the argument is that the rules of the global marketplace

should be technology neutral (to aid the development of new US technologies for

electronic commerce). While we are being asked to accept the possibility of some

kind of value-free rules (a logical impossibility), we are also being asked to accept the

authors’ values (competition, deregulation, market economics). The tenor of argument

here is therefore far from neutral. Indeed, this excerpt is exemplary of the market and

globalisation mantras of neoliberal ideology. This excerpt demonstrates a strident and

rigid ideological stance that competition, deregulation and technology go hand in

hand, and that unfettered technological change, driven by business is desirable.

Specifically, it argues for change to be driven exclusively by market forces as a

simple and straight forward and certain way forward. There is no tolerance of a messy

enactment, filtered through cultural, social and situational contingencies; such things

are simply written out of reality. It is a supreme example of technocratic discourse.

The third main feature is the relationship of knowledge to other concepts. Knowledge

is decidedly unlinked in the map. It should be of concern that concepts in the

Knowledge and Skills cluster are only weakly inter linked, and it is also of concern

that the Knowledge and Skills cluster is not highly linked to the other clusters. This

suggests that the ways in which knowledge relates to other concepts is not explained

and perhaps is not understood. This lack of explanatory commitment and ability is a

concern and is well illustrated in the following:

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As their careers unfold, high-school teachers should also return periodically to the non-academic workplace to keep abreast of changing work and skill requirements. (canada1.txt~6.html#S1_1058)

The use of the word, should, is instructive here. Precisely why all teachers should do

this is not canvassed. However, the implication that teachers would learn more about

the needs of business by doing this is clear and so too is the assumption that the main

purpose of schooling in a knowledge-based economy is to train people for work. It is

taken for granted that this kind of thing is necessarily good and that it is all that is

necessary for schools to have adequately contributed to knowledge. However, that

teachers might also be well served learning other things to do with non commercial

spheres of life is not presented. Neither is the possibility that students might also be

well served learning non vocational things or that it is business that should conduct

vocational training presented. Non commercial elements of education are not seen to

be the most important. The taken for grantedness and the degree to which the

underlying claims are implied by the authors’ is quite extreme. The next excerpt

displays a higher order of implied logic still, to the point that even the implication is at

best a perfunctory one and an even narrower view of knowledge.

Cyber Korea 21 aims to create the framework of a knowledge-based society and to improve national competitiveness and the quality of life to the level of the advanced nations. By 2002, the proportion of the knowledge-based industry in GDP will be similar to that of OECD member nations and Korea will become one of the top ten advanced information societies in the world. Early completion of information infrastructures is essential to the solid foundation of the information society. By 2002, the speed of the Internet services throughout Korea will be accelerated by one hundred times than it is available now. Every information system will be based on the Internet to pursue the global standard. In order to make Koreans the best computer users in the world, opportunities for computer classes will be widened to include all members of the society. The number of Internet users will pass ten million by 2001. (korea2.txt~1.html#S1_15)

According to the logic of this excerpt becoming a knowledge-based society involves

no more than having many skilled computer users and information infrastructure. The

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agenda is about being an advanced nation and this is measured only in terms of

technological capacities. Knowledge is given no meaning outside a purely

instrumental framework. Again, it is not made clear what the logic of this argument is.

Indeed, this excerpt resembles a very rudimentary sketch of a recipe. The thinking is

superficial and technocratic in the extreme, and displays a serious lack of explanatory

commitment that is almost a caricature of taken for grantedness.

This analysis shows that the Knowledge and Skills cluster is semantically isolated

suggesting that the authors of the corpus have not seriously considered the nature of

knowledge and how it is linked to the social, cultural and economic realms. Going

further, while knowledge might be the espoused central concern, the real concerns of

the corpus are technology and business. Knowledge is simply a convenient vehicle to

convey vested interests. The corpus is also interesting for its lack of accommodation

of social and cultural aspects of knowledge. Even if one justifiably seeks economic

benefits from knowledge, because knowledge is profoundly based in social and

cultural processes the economic benefits will be dependant on those social and

cultural foundations. In this situation even the economic planner who recognises the

economic importance of knowledge must consider and discuss the social and cultural

fundamentals.

6.1 Implications for the WSIS

While there are examples in the corpus of concern for issues such as culture, art, the

environment and social policy that are normally outside the scope of technocratic

discourse, it is clear that its central focus and its general concerns are nevertheless

technocratic in nature. It is also important to specifically note that the corpus does not

see knowledge as valuable in its own right and that presents no clear understanding of

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what knowledge is. The value and nature of knowledge is presented as a function of

its ability to contribute, instrumentally, to technology and the economy. What are

WSIS members to make of this and how can it help them make their case for

development along knowledge economy and knowledge society lines? There are three

ways in which this research is important to WSIS objectives.

First, knowledge is political and we must make a choice about what politics we want;

the politics of emancipation or the politics of technocracy. Politics and power cannot

be ignored when one is developing policy to foster the development of a knowledge-

based economy or knowledge society. I argue that a policy agenda for knowledge

must make an explicit choice about what kind of politics will infuse it. Knowledge-

related policy is well positioned to adopt a politics of emancipation, of equity, cultural

enrichment and of wisdom. It is also important to emphasise the view that adopting

such a political stance is not to necessarily exclude important concerns in relation of

economics, commerce and technology. While it may often seem that one must choose

between culture and commerce, there is no reason to do so. What is clear is that the

dominant discourse has as one of its effects to encourage us to see the world in black

and white thus channelling resources in a particular direction rather than in many

directions (Graham in press). My analysis cautions that technocratic discourse

threatens democracy and national (cultural) sovereignty in a globalising world by

occluding that which is beyond its immediate narrow interests. Technocratic politics

is therefore problematic for participative and representative democracy because it

represents the interests of business and technology rather than wisdom, culture, the

environment and the ‘other’.

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Second, a sociological theory of knowing can impose a discipline on policy analysis

and formulation that renders what is occluded by the dominant discourse more visible

and more discussable. WSIS members can better position themselves is through the

possession of a sound and comprehensive conceptual framework describing the

sociology and political economy of knowledge. Such a framework provides a

discipline to guide policy analysis, formulation and implementation, one that enables

us to test knowledge-related policy for its completeness of perspective and its politics.

If we are serious that knowledge is important in its own right we must deal with it in

its own right, not as an epiphenomenon or a smokescreen as it is treated in the

dominant discourse. Using the framework presented here we are reminded that social

networks and other social structures, and interpersonal and intergroup relations must

be considered when thinking of knowledge and society. We are also reminded that

reflexivity, creativity and culture are essential aspects of knowing and that the nature

of individual knowers’ skills, wants, and ethics must be considered. Furthermore,

while it is clear that it is easy to see a role for technology in knowledge-related policy,

what is more difficult to see is that such things as the nature of places, history,

landscapes and cultural objects are critical to knowledge.

Third, the theory set out here makes clear the messy nature of enacting knowledge and

cautions us that the implementation of knowledge-related policy is no simple task. It

is also useful to be reminded that how knowledge is enacted remains unacknowledged

in the dominant knowledge-related policy discourse. That the enactment of knowledge

is unacknowledged for its messy and paradoxical (intentional/unintentional,

rational/irrational) character; its problems in relation to imperfect knowledge and

bounded rationality; and the effects of the voluntary/involuntary nature of roles,

positions and power on it is problematic. Importantly, this messiness actually enriches

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life and should be valued rather than narrowed, confined and limited to the concerns

of technocrats. Discourse about knowledge in the WSIS is not technocratic and

unbalanced, it possesses more wisdom than that, and WSIS members have, therefore,

an opportunity to progress towards a knowledge society if they do not succumb to

technocratic discourse. This is an opportunity that developed nations may not now

have. They appear to be on a trajectory towards a technocratic society that eschews

wisdom. Moreover, developing countries may find they are better positioned than

developed countries to draw on wisdom as a resource for creating a better future.

In summary, WSIS members can avoid the failures of technocracy and better

articulate their arguments against technocratic imperatives if they have a conceptual

framework that explains the dynamics of knowledge and of technocratic discourse

while providing a yardstick against which knowledge discourse can be assessed.

Moreover, such a framework enables WSIS members to explain their positions, needs

and strategies, and remind them that they should make the explanatory commitment

that is missing (for ideological reasons) in technocratic discourse. A knowledge

politics that is emancipatory in nature is more likely to result if it is informed by a

framework such as that presented here.

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