One can only wonder when opening a science journal. Feats that would have been conspicuous in science fiction are now commonplace. For example, a letter to Nature describes the identification of specific kinds of cow's milk in potsherds from a Neolithic tomb. Another reports the finding of multi-organism 'cities', apparently unchanged from fossil examples of the same assemblages laid down over a billion years ago. The one tells us when and where animals were domesticated, the other allows us to reconstruct something of the climate at the dawn of life. A further recent article shows that exactly the same biological structure causes the pathology associated with common black spot in roses, and with bubonic plague, which devastated Asian and European populations in the C13th.
The forest of knowledge grows denser and richer, and complex interactions emerge from it. Ideas that describe the behaviour of insects and ecologies offer insight and opportunity in engineering and economics. Fundamental concepts in particle physics, such as symmetry breaking, crop up when we try to understand cognition. Mathematical toys created in aftermath of World War II appear to describe the fundamental interactions of which the universe is made. Statistical concepts assembled by a British vicar drive internet search engines centuries later, whilst statistical ideas that described steam engines crop up in fields as distinct as risk management, the study of black holes and the putative theory of everything, super-symmetry.
Science is the high culture of the new millennium, of huge aesthetic appeal to those who are involved, and an incomprehensible challenge to those who have not made the effort. Our lasting cathedrals are patterns of knowledge and data, and our constructs are things of the mind, open only to those with a sufficient grasp. This said, science allows us to see what could not be seen, to envisage what was previously incomprehensible and to capture what appeared incomprehensible.
It is necessary to treat what follows with one element of caution. We may have seen too many white coats in detergent advertisements for our own good. It is all too easy to equate 'knowledge' with 'science', plus 'making use of what science has won'. There is, however, much more to knowledge than the extrapolation of highly structured, rigorous understanding. Virtually all decisions which are taken about general affairs are indeed informed choices, but are seldom founded on rigorous structures of understanding - on science.
This is because the issues which are addressed are too complex for rigor, because time frames are too tight or because those taking the choices are disinclined to cede choice to abstract assessments. Most commonly, however, we make choices in general ignorance on the basis of hints, analogy and experience. We fuse opinion and vast amounts of weakly interconnected information so as to guide our steps
We may become much better at doing this, using techniques founded both in information technology and in better forms of organisation: around knowledge management. Building the bridge between rigorous explanations - science - and the general use of these in a fluid environment is a critical feature in any culture and economy. The effectiveness with which we do this will mark success and failure in the knowledge economy.
We discuss three topics. The sheer scope of the knowledge that is being stockpiled - and something of where this may lead - are considered in the first section. Next, we consider the economic worth of knowledge, and the processes by which knowledge gets turned into wealth. Third, we consider the policy implications of this as applied to public spending on research.
This section is focused on the scope and scale of scientific endeavour. The section which follows revisits the profoundly important issue which we have already met: that science is one form of knowledge, but it is not the sole or even dominant form that guides our world. Harnessing the undoubted beauty and potential of science remains a major challenge. Harnessing the complex, muddled processes by which we seek options and renew our affairs is, however, and even more important issue.
Figure 1 shows the growth in scientific publication since 1700. The recent explosion parallels other human activities, but the pace is now far swifter than almost any other endeavour. The base of knowledge is alleged to double every eighteen months, and the databases of biology double every six-to-nine months. The more general growth rate implies that the knowledge base of 2020 will be over ten thousand times greater than it is today: much more than is shown in the relatively modest figure. We would be creating about 300 million times as much science in 2020 as we did in 1700.
Figure 1: Scientific output shows a familiar exponential pattern.
Individual satellites and particle detectors are capable of producing immense data streams which must be sorted and refined. Very large amounts of information do not necessarily create very large advances. Nevertheless, the volume of useful data will grow sharply, with sources in everything from genetics to astrophysics, cognitive research to seismology. One striking outcome of this flood of data is that we are able to synthesise it in order to create perspectives that no human could have seen before.
We can visual individual atoms and, indeed, watch mass waves propagate along coherent streams of matter-behaving-as-waves, in Bose-Einstein condensates. We can see the smoothness of the universe and the ripples in this caused by gravitational fields in it. We can watch molecules shuttle in cells and see the delicate structures that this creates shift and dance. We can look at our planet from a myriad of points of view. Figure 2 shows light pollution in Europe, reflecting patterns of economic activity, oil extraction and the like.
Figure 2: Europe, showing night-time light pollution.
These images and ways of fusing data let us see patterns of relatedness and processes that work over time. Population movements have, for example, left their imprint on our genes. The likely migrations into Europe which these record can be matched with other records from archaeology, linguistics, climatic change and the spread of crop plants and their pests. These multiple perspectives are likely to develop and intertwine as our capacity to collect and fuse data develop. It is from these fused linkages that our certainties about the world in which we live are shaped.
Science has had the habit of finding the previously invisible and making it tractable. Our lives have been changed by the detection and understanding of electromagnetic waves and currents, for example, or the micro-organisms that maintain our habitat, transform our food and cause many of our diseases. This process of seeing the invisible has, if anything, accelerated. Three decades ago, we did not know the primary dynamics by which the continents are formed and the land masses shaped. We had little or no idea how our climatic system worked, what happened at the bottom of the oceans or at the heart of the cells in our bodies. The standard model of nuclear physics was just being formed.
In the last five years, we have seen all manner of strange things. In the realm of the very small living organisms, for example, it has become apparent that an entire bacterial population exists deep in the Earth's crust, comprising perhaps a half to a third of all the biomass on Earth. An entire new kingdom of micro-organisms, the Archaea, were identified in the same period. (A "kingdom" is the grandest division into which life is classified. Animals are a kingdom, as are plants, fungi, bacteria and the Archaea. Finding a new one is thus rather a surprising thing to have achieved.) A completely new form of photosynthesis was uncovered which is responsible for perhaps a third of all of the energy captured in the deep oceans. What all this means in practical terms is not yet known, but early steam engines were seen as curiosities and as mine pumps, not the engines that would disperse populations, create cities, build empires and radicalise economies.
What are the 'new invisibles' that may emerge in the course of the next 20 years? Clearly, we cannot discuss what we do not know, but there are, nonetheless, some major problems to which solutions may be forthcoming. Here are a few of them
We do not know, however, what constitutes 96% of the universe. Whatever it is, it carries immense energy density, and at least some of it streams continuously through our bodies and artefacts. The search for the "Higgs boson" in the world's major particle accelerators seeks an observable consequence of the so-called 'false vacuum'. Observable matter is thought to have precipiated out from this false vacuum, a dense state of extraordinary energy. In its pre-precipitated form, the false vacuum has the weird property of reversing net gravity, such that the universe expanded very rapidly before generating all of the mass and energy that we now see. It has the additional weird property that it can increase its scale indefinately, essentially 'paying' for the mass created by the (negative) gravitational energy that is generated. Thus we all come from nothing, we are suspended in a vastly energetic medium which we do not understand, and all that there is exploded out from a infinitessimal speck of temporarily-perturbed probability embedded in not time and no space. Such a situation seems a likely source of profound surprises.
Figure 3: Prediction and actual arm movement in three dimensions.
However, what happens to create awareness or the fusion of these primitive forms remains a mystery. A central element appears to be related to the concept of emergence. This states that simple things, when connected together, create systems with complex properties. Such properties require more complicated models to capture what they do than is needed to 'explain' the component parts. Markets, for example, emerge from the interaction of a myriad of vendors and purchasers, in reality and in simulation. Ecologies emerge from the properties of individual organisms. Particle physics uses a version of emergence - symmetry breaking - to explain much of how the universe acquires structure. Phase changes - such as the ice-water-steam continuum - are examples of macroscopic symmetry breaking. There is no Platonic template for emergence: be it evolution, thermodynamics or, perhaps, cognition, it "just happens".
Such concepts may give us machines that seem to think, and companies that do think. The may also give us self-designing systems, with the capacity to develop very rapidly. Recent examples are primitive structures set to work surmounting particular hurdles, where the most successful pass on their characteristics to the next generation. Engine and bearing design, the creation of enzymes of ruse in food processing are examples of practical uses of this. The Eurofighter aircraft is being designed to learn to fly modified versions of itself should it suffer combat damage, using just such technologies. The more expensive cars are beginning to 'learn' their driver's habits.
Figure 4: IL2 recognition and signal transduction at the gene level.
This pathway is involved in critical regulator processes in the cell, which impact on embryonic development, immune system responses and cancer development. Understanding this maze will, without doubt, give us the tools to design better systems and the means to interact with exquisite selectivity with those which have gone wrong.
Where can we expect the greatest changes? People tend to look to the mysterious areas, as we have done above. However, all science 'stands on the shoulders of giants' and it is the contributory flows that seem to have the greatest impact, rather than the exploration of completely new terrain. Biology is, however, fit for revolution. The tools have developed, the data is streaming in and the commercial imperatives to fund research are in place. Events will move much faster than they did in the unfolding IT revolution, but they will do so amidst vastly much more complex and inaccessible structures, in a regulatory and political environment that will also oppose swift change. The biology, in short, may outstrip the capacity to deliver socially useful products
IT will continue to expand what it can do, although the emphasis on representing data in meaningful contexts will increase very greatly. (Issues of IT connectivity are discussed elsewhere.) The great strides made with internet search engines are very crude precursors of what may develop. Context-sensitive indexing, physical representation of content relatedness, dynamic searching are all tools which will be commonplace on corporate intranets in a few years. As spell checks today alter or flag what you type, so existing knowledge may be indexed against developing texts, and perhaps even discussions. It would be nice to believe that it would be possible to have a meaningful conversation with whatever passes for a work station in 2020. The capacity to do this (or to provide the elderly with companionship, or the businessman with a mobile earphone that reminds him of his colleagues wife's name and birthday) all depend on the issues of cognition to which we referred earlier being solved. If such issues do reach solution, then change may be very rapid as self-designing systems succeed themselves. The social impact of this will be large and the consequences imponderable.
One area of IT that may be of great consequence is quantum computing, where - effectively - every path of an algorithm can be evaluated simultaneously, using the parallel and indeterminate nature of the quantum wave function. If this were to prove possible, the promise of free computing and infinite band width would be near to realisation. However, there are major technical issues to resolve.
An area which attracts much attention is that of making very small, complicated things. When biology does this, we arrive at low energy systems with high resilience and strength. Machines which have self-repair capabilities, or which construct intricate devices, are promised. The use of free-standing examples of these is not always clear, as they will need very clean environments in which to operate. However, technologies which separate mixed materials, atoms by atom, may have major roles to play. Structural materials - such as nanofibres, diamond matrixes and the like - may be flexible, strong and made from renewable materials. So-called optical crystals, which are actually regular patterns embedded in matter - have remarkable effects on light, which may be used in computing as a result. It may be possible to record data in very dense forms, such that a hand held device can contain immensities of information.
The science of the very complex may also become more tractable. The social sciences operate in multidimensional environments about which it is hard to say precise things. Understanding how complexity assembles itself, and measuring far wider contributory factors may, however, trigger a revolution in understanding in these areas. The policy, defence and market-related issues that flow from this are striking. So, too, are issues of human affairs: the next Reich could well last a thousand years because we are managed to want it to do so. Whether that would be a good thing or a bad thing depends on the criteria that one chooses
These somewhat exotic concerns are raised because technology has moved from the fringe to the heart of industry. It has had major impact in how we live, chiefly, however, in things which are external to ourselves as 'spiritual beings'. It is, however, set to invade the space marked out by those quotation marks. This will be an invasion that many will resist. It may be right for them to do so, and in some instance, it will certainly be right to proceed with the greatest caution. This said, the boundaries of these areas will be drawn by activism, and those nations, industries and disciplines which get off on the wrong foot will be left behind in the commercialisation, regulation and general adoption of the better aspects of the field. German pre-eminence in pharmaceuticals has been all but eroded by the blanket limits applied to biotechnological work as a result of allegedly green pressures. The same could happen to almost any of the fields of endeavour which have been touched upon in this text. And in most which have not.
We hope that the previous section has convinced the reader that scientific progress is poised for the greatest leap in human history. At issue is whether this matters to the economy, to the policy community and, ultimately, to the lay public.
The answer is, of course, a very affirmative 'yes'. Studies on the ultimate value of scientific investigation suggest internal rates of return that vary wildly, but are seldom less than venture capital rates. The table shows a summary of an OECD study of the literature on the subject.
Private rates of return to research and development
Rate of return to
Rate of return to
Business units (924 samples)
General firms (307 examples)
Japanese firms (555 samples)
Innovations (43 samples)
Private rates of return are usually less that the social rates, which is to say that the initiator of the research does well, but that the overall benefit of the innovation and knowledge is felt more widely and used by many more people than the initiator. This is a benefit or a problem, depending on perspective. The 'problem' camp see this as an example of the free rider problem, which is that a firm which trains or performs R&D - which increases the sum of knowledge - may do this for beneficiaries other than its shareholders. A Presidential study was conducted into the value of US fundamental research. Focusing on IT-related investment that was conducted in the 1970s, it showed that this had created a knowledge base that was, of course, exploited commercially in the US, but also in Japan. In the US, the knowledge earned about 25% real. In Japan, it earned nearly twice as much, and served to undercut the US consumer electronic industry
The scale of public and private investment in knowledge is explored elsewhere. At issue is the effectiveness with which latent potential is grasped. This issue has been discussed elsewhere. In brief, however, most organisations tend to have a set of processes which set direction and allocate resources which are insulated from considerations of potential. That is, those who define what is wanted seldom have complete insight into what is possible. Connecting these two groups up is what one flavour of knowledge management seeks to achieve. As those who are involved are distinct by age, interest, seniority and job role, this can be a difficult thing to achieve.
Once there is a clear view of the general types of potential which exist, and which of these the organisation would care to reap, then those who stumble across options - or who have laboriously to generate them from scratch - will know what is wanted. Those who assess proposals have a context within which to perceive, evaluate and develop these. The organisation becomes more adaptive, confident, agile; it knows what it wants and can seek this in its daily interactions with the outside world.
Such processes tend to develop spontaneously within senior management 'clubs' that arise in milieux between organisations, rather than within individual companies. Where knowledge management tools have not been deployed, therefore, nations may have to rely heavily upon these spontaneous processes. Anyone involved in the creative industries will know how 'doing lunch', engaging in industry gossip, attending award ceremonies and the like are the trawl in which new ideas are caught. This is highly inefficient, and usually does not work well in more staid industries. These rely on individual champions, on routine processes of new product development, of benchmarking products against consumer needs, against item-by-item measures of industry best practice and against production or process improvements. This piecemeal approach seldom produces great leaps in capability or market position, but rather low-risk incremental improvement which makes full use of installed capacity.
This patterns tends to be replicated in the structure of knowledge-intensive industries. Smaller organisations trawl for new ideas or develop the thoughts of their founders. They may be small enough for social processes to enable innovation internally, and they network heavily with the operating milieu. Larger organisations engage in gradual improvement, outsource much of what they do to specialists and filter-feed on the knowledge-rich plankton which the small companies represent. IBM, for example, is said to have acquired tens of thousands of smaller organisations during the 1965-85 period. One which they missed was Microsoft.
Elsewhere, we have discussed the determinants of growth in the industrial world. Knowledge is a factor of production. More of it creates more activity. Knowledge is, however, unusual in one respect, which is that the style of its use is of critical importance. In the absence of good processes and prepared minds, knowledge is as useless as cars without fuels or computers without electricity. The issues of knowledge utilisation are ill-understood - although, as above, some progress is being made in understanding what is entailed - but we do not know how to score ourselves for our adequacy, let alone set up explicit programs for improvement. This domain, loosely descried as 'knowledge management' - encompasses a vast array of tools and issues that operate in all time frames and at all levels of scale. As we have observed in other sections, when there is someone to undertake almost any module of work tat you can specify, knowing what to do becomes the critical, scarce factor. Option creation and execution will become central to economies, and - it has to be hoped - to the preoccupations of markets and thus management teams.
Governments should have a basic attitude to science and technology, which is that they want to see more of it, and to see it better used in the pursuit of wealth and a general improvement in the quality of life.
Translating this prescription into action is, of course, complex. It translates into three very broad areas
The management of public expenditure on research is a topic which has been much examined. Virtually all nations co-ordinate what is being done so as to be effective in meeting three kinds of target.
First, production needs to be efficient in generating output, including trained people.
Second, assets are allocated to meet public sector needs - such as environmental assessment, defence needs or analytical capabilities - and to be focused on areas where the nation has particular strengths.
Third, the nation needs to have a wide enough portfolio of interests so as to be able to engage with global civilisation and so as not to be outflanked or astonished.
All of this has to be done in an environment in which those managed know more than their managers, are articulate and are unwilling to be directed. The time frames within which changes can be made are gradual, and every aspect of what is done impacts on many interests. Sweeping changes are not, therefore, easy to achieve. Most of the industrial nations have undertaken some attempt to achieve a consensus around foresight on what could be done. To be effective, these need to be tightly focused. Many have been diffused by trying to solve many problems at once, or solving the wrong problem. Indeed, one important outcome of such enquiries may be to point up the real problems - management education, for example - and to unsaddle commonplace hobbyhorses, such as the alleged 'short-termism' if venture capitalists.
Ultimately, most of the industrial nations spend much the same proportion of their economy on public support for science, and most spend it in much the same ways. Spending in the developing nations is explored elsewhere.
By contrast, nations have rather disparate levels of commercial spending research and development. These levels also vary between sector very greatly, and knowledge-intensive economies such as Sweden or Finland tend to have higher levels of R&D than their peers precisely because their economies are weighted for these sectors. However, the tax treatment of such re-investment varies considerably between nations, and so what is reported as "R&D" depends on what it is commercially appropriate to categorise in this way. Sectors in which there is a high element of regulatory permission to what they do tend to report their compliance activities as R&D. Industries such as finance are less inclined to publish what they do. Knowledge so generated is often ephemeral, and yesterday's stock analysis serves to wrap fast food. Statistics are not, therefore, entirely meaningful.
This said, the scope for policy interaction in this area is very great. The nature of human resource development, the use of quality assurance standards for the presses of R&D, the accounting standards for intangibles, the tax treatment of innovation and the career structure of public sector scientists all offer profound levers that have been shown to work.
Science output - as measured by papers published, or published papers later cited by people other than their authors - tend to follow scale, in the sense of correlating strongly with the absolute size of economic sectors and their knowledge intensiveness. This changes with circumstances: the US service sector spent 4.1% of the national R&D in 1970, but has risen to around a fifth of thetotal by 2000. Large economies - such as the US, and knowledge intensive sectors within them, such as pharmaceuticals - therefore dominate publication output. The service sector, however, dominates the output of skilled people.
This has one profound implication, which is that the commercial returns to knowledge do not scale in a linear manner. If one spends ten times as much, one gets ten times the output; and all other things being equal, one gets ten times as great a chance of developing a top product from this. However, consumers tend to buy the best, meaning that the top two or three products capture virtually the entire market. Scale thus generates disproportionate return, offset only by luck and niche marketing. Further, success breeds spin-off industries, innovative milieux, confidence and capable people. It creates surplus capital in search of projects. Additionally, where options emerge from chance interactions, the number of options which the overall system explores scales factorially with the number of agents and their size. Large agents tend to be highly connected into networks and to span many otherwise closed networks, such as academic institutions and interests.
The consequence of this is, once again, the need to recognise the importance of geography and clustering, of social processes and of scale. Knowledge milieux become effective when they reach a critical size and maturity, and they need to be fed with fundamental understanding - science - and capable people who can operate in multiple domains as well as specialisms. It is not possible to know into what such milieux will evolve, but it is easy to prevent their evolution. State-funded projects (software, aerospace, marine engineering, new broadcasting, de facto consultancy) have created the nuclei from which milieux have developed. Others - in vehicle manufacture, design, clothing, retailing, finance, advertising, telecommunications, entertainment, life sciences, offshore engineering, logistics - have evolved on their own. The former were often of dubious economic merit, whilst the later have proven self-justifying. Virtually all such clusters have required active engagement with urban planners, with local education and training, security and transport. All such industries rely upon a coherent state approach to regulation, as discussed elsewhere.
We listed three grand goals for the state at the beginning of this section. The last of these was the assurance of public confidence in what was being done. Regulation protects the public from harm. It insures firms against unlimited risk, by laying down the compliance boundaries. Third, it assures the public that their interests are being reflected, and that their sensibilities as well as their objective interests will be protected. This last is becoming a major issue, not least as technologies create possibilities which were hitherto unthinkable. The need to engage politically with a public that may lack the grounds to debate the issues is explored in much more depth elsewhere. However, failure in this regard may inhibit the development of whole industries. This is particularly true of those most disturbing of activities, life science and cognition research.
Public perception of risk is that there should not be any, and that the role of the state is to wish away uncertainty. The public capacity to assess risk is not good, however, as the scattergram for the US population shows. Microwave ovens, fluoridation or GMOs have never been shown to hurt anyone, whilst handguns and vehicles, alcohol and tobacco account for the deaths of a significant fraction of the US population.
Figure 5a: Public perceptions of risk.
Below, some of the same issues are set in an actuarial context. Figure 5b shows the 'real' risk which is involved. The scale is logarithmic, such that the lowest score amounts to one change in one hundred thousand million of dying in the course of a year as a result of exposure to the risk.
Figure 5b: Objective assessment of risk.
The risks which concern the public - such as nuclear power - fade into insignificance when compared to what is accepted in daily life, or indeed, sought out. Attitudes to risk are tempered by the fear of the catastrophic, by the sense of being out of control of the sources of the risk and by poor understanding of the forces which are involved. When an unexpected event occurs, however, blame is allocated and the public regulator is a natural target for this. Compensation is often expected, frequently for issues where the impact could not have been foreseen and where there is no question of blame. Articulate bodies who stand to gain from this often arise in the aftermath of highly publicised incidents. Alleged syndromes - post traumatic stress disorder - are discovered or invented and become a mantra in what follows
Evidence-based policy offers a weak bulwark to these events. Elsewhere, we discuss the need for the political process - in its broadest sense of mass discourse - to bring about a wider public understanding of evidence-based approaches and of the factors that are at work in the modern world. We all need to work harder in order to understand and manage the awesome potential with which we are faced.
|to the top|
The Challenge Network supports the Trek Peru charity.