Why Knowledge has to be Social

Knowledge is a set of connected ideas that create meaning for people that is actionable. In other words, knowledge is about action or doing things in the social world. We cannot create meaning and do things in a social vacuum. Given this position, ideas are created and distributed, or become meaningful and the basis for action in the world in social space. Another way to think about this is to say that knowledge exists in the spaces between people and groups of people. These spaces are what really matters and so too do the structures that link between people and groups across that space. If it is important to promote a more knowledgeable society those who promote it have to consider how the spaces, links and people/groups work effectively to create that society. We need researchers, policymakers and citizens with the souls of architects who can create the knowledge economy and society policy frameworks to do this.

My Home Page

Knowledge or Wisdom?

If policy makers want to avoid constructing a savant economy instead of a humane society what else is needed, and is it a good idea to extend thinking beyond innovation and knowledge to also include wisdom? I argue that a primary goal of knowledge policy is not simply to accumulate large amounts of knowledge, expertise, and technology. Instead, the relational configuration of knowledge systems and how it leads to integration of ideas, values, and culture is more important in avoiding savantism. Finding ethical, workable, and dynamic balances between many variables is the real challenge. Wisdom is the ancient human quality that supports these goals. How this integration and inter-relating happens will be different in different communities of practice, and knowledge will fail businesses and communities that set tight limits on what is integrated into their discourse. Again, Enron serves as an example of this kind of failure. In this case, openness, diversity, and a democracy of ideas matter. Understanding the social dynamics of inter-relating ideas and values based on systems of trust and reciprocity (social  capital) is critical to managing knowledge systems for wise practice.

Policy professionals also need to understand other important theoretical issues related to wisdom and the limitations of knowledge. There are also cognitive limits to how much information people can remember and process, and people are boundedly (imperfectly) rational. All people therefore necessarily have imperfect knowledge of the world, even when inundated by information and knowledge. Wisdom and its attendant qualities like communication skill, experience, ethics, imagination, and judgement have much to do with successfully filling the gaps in knowledge and filling them despite what is often assumed to be ‘common sense’ or ‘received wisdom,’ but in reality are simply taken-for-granted assumptions of dubious validity. Wisdom is more than knowledge and brings a humane focus with it. The products of wisdom are badly needed and innovation policy should be under pinned by initiatives in various policy areas that promote the kinds of integrative processes in society that are characteristic of wisdom.

My Home Page

Services & Abstract Economies

Abstract innovations are central to the service industries that drive knowledge-based economies . In large degree knowledge-intensive service industries use abstract knowledge to trade and advise clients. Knowledge-intensive service providers tend to be advice givers (communicators), and therefore future oriented (abstract thinkers). Businesses that trade on various capital markets are good examples of the use of abstract knowledge. As suggested above, both the traded ‘commodities’ and the trading methods used in contemporary capital markets are themselves very abstract. New forms of derivatives and synthetic swing trading methods are examples of high-value abstract innovations in the finance industry. New research questions therefore surround the implications of a knowledge-based economy that is distinguished from older economies by the fact that abstract theoretical knowledge is growing in economic and social importance. Enron and Bear and Sterns were intensive users of abstract knowledge (and abstract ‘commodities’), and their intensive use of abstract knowledge contributed significantly to their downfalls. Enron and Bear and Sterns were at best savant businesses and ultimately destroyed rather than created wealth. Thus, national innovation systems need to avoid the adverse effects of the unexamined use of abstract knowledge in economic activity. This is not an argument against the use of abstract theoretical knowledge; it is an argument against the unchecked commoditisation of for example abstract financial thought (credit derivatives, collateralised debt obligations, credit default swaps, etc.). Many service providers are involved in giving clients advice about the future and have to explain complex phenomena, and abstract knowledge is essential to do these well. Abstract knowledge brings many advantages with it, but it is a ‘volatile substance’ that needs to be handled with skill, judgement, and care. 

James Wolfensohn, former president of the World Bank, in an interview with Kerry O’Brien on the 7.30 Report (1 April 2008), noted that an important causal factor in the current sub-prime loan crisis in the USA is the abstract nature of the industry. He said that those who do the innovating within banks are “a new breed of bankers with PhDs in mathematics” and they have made it possible to create wealth to an extent and in ways not seen before. On the strength of this, top managers have become over-confident in the extent to which the innovators can carry the prospects of the banks on the strength of clever ideas alone. Top managers, he suggests, have consequently abandoned sober and prudential thinking that might prevent some problems occurring, and did not see the problems the USA economy is now experiencing coming. Tellingly, Wolfensohn said the banks were trading using abstract knowledge-based methods that “frankly none of the top managers really understood”.


A knowledge communication perspective begins to illuminate how policy makers might respond to problems associated with high-value abstract innovation. At a number of levels there is a troubling lack of innovation and knowledge transparency related to these contemporary conditions. Lack of transparency is a knowledge communication failure issue. Top finance and banking managers are not adequately communicating with their innovators; regulators and policy makers are not adequately communicating with industry and consumers; and consumers caught in, for example, margin lending and sub-prime mortgage foreclosures have often not been adequately informed. There is a lack of talk between key stakeholder groups about these innovations that hinders transparency. The unasked question here is what processes will bring abstract commercial innovations into more meaningful (and transparent) communicative circulation in a knowledge-based economy or society? The answers to this question are unclear and the question poses significant commercial, policy, and research challenges.


My Home Page

Technocracy and Savant Economies

What kind of country do we want to live in and how will innovation and knowledge help to achieve our goals? For many reasons these questions should be the first questions asked when considering what innovation policy aims to achieve.

With the above questions in mind, an additional set of concerns rising from fundamental research is that in the absence of policy making knowledge about the fundamentals of knowledge itself there is a danger that knowledge-related policy, and particularly innovation policy, will simply contribute to the construction of what can be called savant economies and savant organisations: economies and organisations with abundant knowledge, expertise, and technology but which lack the wisdom to apply them well to create a more humane society and long-term sustainability. Historically, innovation policy seems to have been going in this savant direction. It is now time to acknowledge for example that technological innovation has been a long-term contributor to climate change and the innovation system has not had the wisdom to respond in a timely or comprehensive enough way to the challenges it has been part of creating. Part of the remedial action required is developing a better understanding of how knowledge and innovation are liked to each other and to a larger context.

In a semantic analysis of a 1.3 million word corpus of knowledge-related policy documents from around the world, knowledge itself is connected in only a very weak way to the larger discourse around it. In other words, it graphically shows an absence of an organising and guiding theory of knowledge. What is also shown is that conceptual frameworks about Telecoms Infrastructure, for example, are more detailed, coherent, and integrated than they are for knowledge. This is indicative of the technocratic attitude informing knowledge and innovation policy production. 

The spectre of savant economies resulting from technocratic policy is unpalatable, and the degraded environmental, social, and cultural amenity that is likely to eventuate in them is unacceptable in a civil and democratic society. Economies and societies that experience only technological advancement, or ‘cleverness’ are meaningless from social policy and democratic perspectives. It is important therefore to ask what might the adverse effects of knowledge in the absence of wisdom be and how might innovation be a disservice to the community? It is inadvisable to assume that all innovation and knowledge are necessarily good. It is instructive that the American business, Enron, was an innovation focussed and knowledge intensive business that went horribly wrong. It was a very clever company with access to a fantastic array of knowledgeable people but had no wisdom. Enron was a catastrophic failure of knowledge and innovation because its management not only lacked ethics, but failed to reflexively critique the ideas that underlay its business model. The same can be said of the sub-prime mortgage and Bear Stearns collapses. In each of these cases, increasingly abstract concepts were bundled into ‘products’, the foundations of which were akin to the South Sea Bubble or 17^th century Dutch tulip prices. In other words, a mania for clever innovations that seem almost intoxicatingly good, as well as any other ungrounded claims of the virtues of knowledge and innovation, must be treated cautiously. Doing this requires a sophisticated vocabulary and conceptual foundation. This means not just a robust business community, whose capacity for ‘product’ innovation is strong and inherent, but also a robust intellectual community who can critique existing or proposed positions and point to new or different possibilities. There are many benefits in knowledge and innovation but also many potential pitfalls if we do not proceed wisely.

My Home Page

Knowledge Generation in Knowledge Economies

Knowledge has always been a difficult thing to define. It is, nevertheless, necessary to say what is meant by it and what assumptions we make about it when constructing and evaluating knowledge policy such as science and innovation policy. Not to do so would render policy conceptually weak, lacking in substance, likely to miss-specify the generative mechanism of knowledge, and evaluations of policy initiatives unreliable. Such a situation would be less than citizens have the right to demand. Knowledge is a constellation of phenomena comprised of ideas, assumptions, beliefs, intuitions, memories, cognitions, etc., that are taken to have socially justifiable truth values, and that are emergent properties of relations. In this sense knowledge is taken to have truth values that are (re)constructed in social relations and through communication. Knowledge policy and its evaluation, therefore, should include the stewardship, steering and facilitating of these relationally-generated phenomena in pursuit of the community’s goals.

What this means in practical policymaking terms can be seen at three levels. First, knowledge has to be seen as a broad concept that is more than fact, data and information. Knowledge has to also be seen as ideas, insight, wisdom, creativity and so on. Furthermore, sociologists frequently point out that knowledge is essentially a cultural artefact, particularly given its profound links to values, shared meanings, language and the expressive nature of humans. On top of this, it must be recognised that the links between effective knowledge creation, diffusion and use, and social capital and social networks is now well known. An important aspect of knowledge-related policy should, therefore, be that it deals with the way components of knowledge systems are interconnected; it is about relationships. These aspects of knowledge dynamics cannot be over emphasised in the context of an increasingly networked economy. We suggest that a serious misunderstanding of these dimensions of how knowledge works will in all likelihood lead not to the development of a knowledge-based economy but merely to a technocratic economy with limited meaningful returns to tax payers.

Second, translated into science and innovation policy terms, theory says that public investment in science and innovation requires an enabling investment in the social, cultural and communicative foundations of science and innovation work. More broadly, for science and innovation to be working best, it must be built on a large social and cultural foundation. Another side of it is that while culture and society actually generate knowledge, science and innovation should nourish those foundations by responding appropriately to their needs. This is a matter of democratic and open science. Responses to cultural issues, social objectives and community values are critical elements of all knowledge work. In this light, technology for the sake of technology or simply for the sake of commercial imperatives is likely to be short-sighted, socially unproductive, and unhelpful to taxpayers. In other words, the products of public investment in science and technology must be shown not only to respond to social and cultural imperatives, it must also contribute to the social and cultural foundations of its society.

Third, theory suggests strongly that policymakers should take a stewardship or steering role and that much of that effort should be focussed on connections or relationships between components of knowledge systems. These relationships can be between individuals and groups, between people and knowledge (ideas, data, insights, information, etc.), between different kinds of knowledges, and even between people and the physical environment (both natural and built environments) that include and are shaped by the products of science and innovation systems. Part of that stewardship role is to be informed by data collected in light of a valid and reliable evaluative framework. While evaluating the quality of relations and the effectiveness of stewardship activities is challenging, we cannot claim to effectively be developing knowledge about the effectiveness of knowledge-related policy and policymakers unless we find ways. Modern social scientific and economic research methods make doing these kinds of assessments more possible now than in the past.

We are reminded at this point to ask what the purpose of public policy is in a representative democracy. While a complete answer to this question is outside the scope of this document, it is pertinent to say that public policy in a democracy must serve a broad range of interests and needs, and that a goal of policymaking should be to strike a balance across competing interests and needs. This is no easy task. With this challenge in mind, recent research suggests that any policy, including science and innovation policy, should account not simply for knowledge but for wisdom.


My Home Page

Innovative Intellectual Property Rights for a Knowledge Economy: Openness and Flexibility not Strength

IP systems need to be more flexible for communities, business and research, rather than stronger. Holding on to an out-dated industrial model of IP rather than to a knowledge-based model is inadvisable because communication underpins knowledge-based economies; we must assess the IP system in terms of its effects on communication in knowledge creation and diffusion processes. Traditionally, IP rights design aims to distort communication processes that underpin knowledge economies and therefore may have negative effects on knowledge and innovation. In a knowledge economy one must protect the communicability of important ideas and traditional IP takes ideas out of communication channels. Knowledge economies are animated by communication. In this respect, it is accurate to say that knowledge-based economies are communication economies. All knowledge-related policy, including IP policy, should be cognisant of this fundamental point. A central innovation and IP policy question should therefore be about what effects the IP system has on knowledge communication.

In light of the communication view of knowledge systems it is worth noting that contemporary approaches to knowledge production and discovery routinely depend on cross-disciplinary and interdisciplinary practices and collaboration. These practices are effective because they address the basic communication dynamics of knowledge systems. Many of the communication structures and processes that have evolved in traditional universities and more recently in business are core to innovation, knowledge discovery, and knowledge diffusion. This is not to say that all recent changes in knowledge system workings are welcome. In particular, the intellectual closure of university and other research through aggressive assertion of stronger IP rights is often problematic, and precipitates failure at the level of communication.

Looking beyond university research to industrial Research and Development (R&D) generally, it is important to note that IP necessarily also stifles commercial knowledge communication in significant ways. Publication, though, in extinguishing IP rights, encourages wider use of scientific knowledge in the economy. Intellectual property rights therefore occupy an awkward and sometimes unhelpful position in the dynamics of knowledge-based economies. Inflexible traditional IP rights regimes can obstruct effective interdisciplinary and collaborative R&D processes increasingly used in industry. From a knowledge and communication point of view, stronger IP introduces frictions, inefficiencies, and distortions into knowledge and innovation systems. Countries need to calculate the relative macro and micro economic costs and benefits of open versus closed innovation and more or less open (and flexible) versus closed (and stronger) IP rights regimes.

By adopting a knowledge policy theory perspective to guide IP reform, there is an opportunity to be an IP policy leader by bringing important innovations to the IP system. IP reform can make a knowledge economy more flexible, resilient and competitive. 


My Home Page

How Do Knowledge Economies Work: A Short Answer

If you had to develop public policies for knowledge economies you would want to understand how they work. It is safe to say that knowledge, innovation, and creativity stand on a foundation of social, cultural, and economic factors. Because of this knowledge-related policy should provide social, cultural, and economic benefits. In particular, it is communication that forms the fabric and superstructure of innovation and knowledge-based economies and societies.

Flows creation and diffusion of knowledge are, quite simply, the flows of ideas through communication. In this respect it is accurate to say that knowledge economies and societies are communication economies and societies. It is therefore helpful to understand the communication view of knowledge economies by thinking of knowledge as simply sets of meaningful and actionable ideas. If one asks what happens to ideas in social and economic life thoughts will quickly turn to communication. Communication is the exchange of ideas, and ideas have little worth if they are not active in social exchange. It is through communication processes that (1) ideas are diffused, absorbed, and refined to have socially and economically valuable meanings; (2) that particular problems or questions are agreed to exist and to be in need of attention; (3) that particular groups decide how best to resolve questions and problems; and (4) that otherwise disparate ideas can be re-organised into socially and economically meaningful and creative sets of ideas to solve new problems.

People in social and economic contexts are the platforms on which knowledge economies are built. Therefore knowledge is, at base-level, linked to language, social structure and process, and culture. All knowledge-related policy, including innovation policy, should be cognisant of these fundamental issues, and should respond decisively and intelligently to them. A central innovation policy question should therefore be about what basic social and cultural (including communication) conditions are required for national innovation systems to be both economically competitive and socially enriching. Innovation and knowledge systems are misrepresented when portrayed as being simply science-, engineering-, or technology-based. Science, engineering, and technology are best seen as some of the expressions of innovation systems rather than their drivers.

Knowledge-related public policy must begin with consideration of the social architecture and cultural frameworks that are needed for knowledge to flourish without alienating the less fortunate, without creating autocratic intellectual elites, and by making life (not just economies) richer and more sustainable, and citizens more engaged and wiser.

My Home Page