Rethinking the Knowledge Economy

During the few ‘off hours’ I have, I love thinking about innovation and technological change in the grand scheme of things. In fact, a couple of weeks ago I did a weekend trip to New York on my own budget to attend the Singularity Summit 2009 – a conference of futurists. In my recent thinking I’ve stumbled upon a nagging little problem: The concept of the Knowledge Economy is very ambiguous and ill defined.

When I look up the definition of Knowledge Economy on Wikipedia, there is already a big alarm bell going off in my head when I read: “In a knowledge economy, knowledge is a product, in knowledge-based economy, knowledge is a tool.”. The words product and tool treat knowledge on par with physical goods, which in my mind is the reflection of a fundamental disconnect.


In the academic world there is no real consensus on the difference between information and knowledge, a definition that’s not at all trivial. Asking the question will most likely yield different answers depending on which ‘field of expertise’ you consult (management, philosophy, computer science), but there is a common way of explaining the concepts of data, information and knowledge on a continuum:

  • Data is raw facts
  • Information is data that is organized, analyzed or placed into a certain context
  • Knowledge is internalized information: skills, experience, cognition, etc.

“Knowledge is the whole body of cognition and skills which individuals use
to solve problems. It includes both theories and practical, everyday rules
and instructions for action. Knowledge is based on data and information, but

unlike these, it is always bound to persons. It is constructed
by individuals, and represents their beliefs about causal relationships”

(Probst, Raub & Romhardt, 2000)

There is also a very popular view (by Nonaka & Takeuchi) in which knowledge is divided up into explicit knowledge and tacit knowledge. But this widely accepted view has now come into dispute because many claim the concept of explicit knowledge is no different than information.

No matter what stance you take, it’s clear that knowledge always has a certain context associated with it. On one end of the spectrum this could simply mean that certain chunks of knowledge are useless without other chunks of knowledge (still explicit). In other cases it might be that the knowledge is completely useless without a lifetime of experience or skills (tacit).

However, I do think it’s important to realize that while tacit knowledge is a lot less ‘portable’ than explicit knowledge, this could change very quickly with the advent of technology. With the existence of zero-cost communication, learning-enhancement software and artificial intelligence, tacit knowledge is also becoming more ‘portable’.

Many thanks go out to Jozua Loots who helped me with the question “What’s the difference between knowledge and information?”. All done through an awesome new (synaptic) Q&A service called Aardvark.

Informational v.s. Physical

To understand the fundamentals of the problem, we have to take a look at the difference between information and physical objects. Physical objects abide by different laws than information. A physical object can only exist in one place in one time and it deteriorates when used or touched. Information on the other hand, can exist in many places at any time and multiplies when touched.

Picture 26

Thanks to zero-cost communication, the replicating nature of information has showed itself over the last decade. There are now vast amounts of knowledge (and obsoledge) being generated every day, making many derivatives of information (content, knowledge) a commodity. Kevin Kelley explains this well in his essay ‘Better than Free’, where he compares the internet to a giant copy machine where the copies drop in value. Interestingly, when those copies become abundant, the value starts shifting to what’s scarce: the attention of people. This is where the concept of the Attention Economy starts.

A Non-Economy?

If information is so fundamentally different than material goods, you can start asking the question: Does the term ‘economy’ apply to knowledge at all? Let’s take a look at the wikipedia definition of the word ‘economy’:

“An economy is the ways in which people use their environment to meet their material needs. It is the realized economic system of a country or other area. It includes the production, exchange, distribution, and consumption of goods and services of that area.”

And here is the definition of an ‘economic system’:

“An economic system is the system of production, distribution and consumption of goods and services of an economy. Alternatively, it is the set of principles and techniques by which problems of economics are addressed, such as the economic problem of scarcity through allocation of finite productive resources.”

Both definitions are inherently bound to ‘goods’ and the fundamentals of finite production. The problem is that with information, there is infinite free replication. This explains why it is so hard to use traditional methods of economics to measure and understand value created by information. But fortunately there is hope in the definition of ‘economics’ itself (by Lionel Robbins in 1932):

“The science which studies human behaviour as a relationship between ends and scarce means which have alternative uses.”

Because even though the characteristics of information/knowledge are so different , the economic fundamentals of abundance and scarcity still apply.

Informational Drivers of Economic Growth

The influence of information on wealth creation is quite complicated. The biggest mistake people make is treating information (or it’s derivatives) as a physical good that can be traded. So if you can’t sell it, it has no value? Yet information plays a profound role in driving economic growth.

Hans Rosling, a Swedish econometrist has given several TED talks in which he showed how developing countries have been caching up with great speeds. Every booming developing country had it’s own drivers of growth, but one can imagine that a common driver would be the availability of ‘know how’. This ‘know how’ took the Europeans centuries to develop and apply, but for developing countries this was readily available and could be applied fairly quickly. This application of explicit knowledge set off the main driver of growth: change. And when you apply new knowledge to a country that needs to build things from scratch, you get a rapid rate of non-incremental change.

On the scale of an entire economy, it’s really the non-incremental change that matters. An example of normal incremental change could be aesthetics, the improvement of physical products.  Another example would be a well-oiled service industry that services existing markets. All of these dwindle in comparison to the amount of value created by fundamental change. Real innovation will create and destroy new markets (e.g. telephony, online advertising, social networking, etc) whereas incremental change merely optimizes existing market dynamics.

The rapid shift from physical systems to more informational systems – informationization – goes hand in hand with non-incremental change. When a system becomes more informational and has less physical obstacles, changes can happen more quickly. And these changes are non-incremental, meaning that informational systems will have more paradigm shifts, are less predictable and have more volatility. Nassim Nicholas Taleb (NNT) explains this in a different way in his famous book The Black Swan, whereby he defines an Extremistan (informational-law world) and a Mediocrestan (physical-law world).

To summarize:

  • It’s not the explicit knowledge that creates value, but it’s rather the flow and application of it.
  • Non-incremental change is the main driver of economic growth
  • The more informational a system becomes, the more non-incremental changes will happen

Note: A nice example of informationization can be found in the biography of Nikola Tesla, one of history’s greatest inventors. Tesla had a special brain condition where he could visualize and iterate his inventions in his mind using his photographic memory. This allowed him to innovate at a very rapid pace, because he did far less physical experiments in the innovation process.

Stimulating Non-Incremental Change

Some governments, like my own (the Netherlands), come up with special ten year action plans that try to create a vibrant ‘Knowledge Economy’. What should these action plans entail and how relevant is the knowledge aspect of things?

The first thing that needs to happen is the stimulation of informationization. This requires removing physical constraints in for example bureaucracy. Many governmental organizations still require you to handle paperwork with real paper or require you to unnecessarily interface with a person. Also, there needs to be a general reduction of the amount of bureaucracy. This could be done for example by reducing the amount of certifications required to start a certain (informational) business.

Education needs to stimulate independent thinking. They need to stimulate their students to do new things (sponsor adventurous travels?), but more importantly: they need to shift focus from ‘knowing’ to applying knowledge and using creativity.

Corporations need to be formed ever quickly, but more importantly, they need to be dissolved quickly too. Companies – that are getting smaller and leaner – must be able to fail early and often in order for real innovation to happen. This also means that you need a culture that can deal well with failure and makes sure that the people involved don’t have to deal with ‘face loss’. On the flip side people need to be rewarded when they are successful, this might mean having a more loose taxation system for the wealthy. One idea here could be to allow tax-free re-investments of earned capital to stimulate successful entrepreneurs to become angel investors.

Which brings me to entrepreneurship: you need a very vibrant investment climate that has VC’s and angel investors that invest in bold ideas. Many countries outside of the US cope with a sickening amount of risk averseness. When you present a prototype to a European investor, they don’t ask you when you will generate revenue, no, they will ask you: “when will you break even?”.


The economics of a world that is becoming ever more complex are not as simple as they have been. The concept of a “Knowledge Economy” is outdated and is not factoring the new dynamics of informationization. The real driver behind economic growth is non-incremental change, something that is catalyzed by informationization. In order to gain economically, governing bodies, companies and people need to stop resisting informationization and go with the flow.