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.
Knowledge
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.
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?”.
Summary
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.
The Rise of JS and the New Server-side
I started writing this article in my excitement of Server-side Javascript (SSJS) and how I’ve become increasingly interested in Javascript (JS) over the past years. But at the end of the day, Javascript is just another programming language, its importance is defined by the frameworks and applications that are built on top of it. But while I was writing this, I noticed that together with the rise of Javascript, something much bigger is happening in the way services are and need to be structured.
Javascript in the Browser
A little more than a year ago, I wrote about the grim future of Adobe Flash. I think by now, there are even more signs that Flash is dying in it’s current form. Flash got a big stab in the back recently by Youtube when they started supporting the HTML5 video embed and also Apple is once again not supporting Flash on the Apple iPad.
Javascript is getting faster and stronger in the browser. A good example is the powerful, open-source V8 Engine developed for Google Chrome. Also, mobile devices are increasingly centered around Javascript, all Palm Pre apps are written in Javascript; the iPhone Google App is pretty much a JS interface in Safari; And there are cool new frameworks out there that allow you to write native iPhone/Android/Desktop apps completely in JS.
An oldschool client-server scenario with a web application running on the LAMP stack.
Javascript Beyond the Browser
At the end of the day JS is just a programming language, it’s success is determined by the amount of adoption and the problems it can solve. So far most of the problems solved by JS have been in the browser. But this is about to change.
Server-side Javascript is nothing new, but it’s not common yet. There are many open-source frameworks sprouting up now and I think the rise of cloud-services like the Joyent Smart Platform will definitely help SSJS taking off. Also, there are some serious economic benefits to having JS be the only programming language used in a web application. Do you know any programmers that don’t know how to write HTML? How about Javascript? JS and it’s relatives – ActionScript and Java – are very widely known by developers. This means that finding and training JS developers is easier.
These SSJS frameworks need to accommodate very different use-cases than their client-side counterparts (jQuery, Prototype, …). A SSJS framework shouldn’t care about the DOM, but it should care about things like IO / file access, network and database connectivity, template rendering, communication with existing dynamic libraries, etc. The server-side use-cases are completely different!
The Migration to Client-side
For the past years, I have been involved in scaling a huge service called Smart.fm. Over the course of 2009 we’ve made some big adjustments in our technology strategy. We’ve been offloading more and more controller logic into the browser using jQuery/Javascript. This also means that we’ve had to beef up our API and make sure all data can be accessed smoothly using JSON feeds. This has given us huge benefits in performance, modularity, manageability and user experience. But when looking at top-sites out there like Facebook and Google, this seems to be common practice nowadays. More and more logic is now running in the browser.
A typical client-server scenario with a web application using the Rails stack.
So all of this has got me thinking: what does the server-side still mean for a web application?
The controlling of the UI flow and interactions is now done by Javascript in the client. This means that access control is purely done by the API, the client will not get the data it doesn’t have access too. This means that all access control and data routing will be controlled by the API.
What about server-side rendering of templates? Surely we need this for the search engine bots, but do we really need to treat them the same as users? Search engine bots like the Google Bot need to be able to scrape server-side rendered HTML information and will not execute any client-side logic. But as simple keyword search is becoming less relevant, we need to start building different interfaces for machines. Why not render some simple HTML for those dumb Google Bots and not worry about it in our UI? Oh and while we do that, render something more semantic for those smarter bots!
Architecturally, we can define these components in a modern web application:
So when all rendering and UI flow logic moves to the client, what responsibilities remain for the server? It is very important to ask this question when you build a new server-side framework. What problems does it need to solve? Most server-side web frameworks are built around the increasingly irrelevant Model-View-Controller (MVC) pattern.
A Next-generation Architecture
Now that the responsibilities of both the client and the server have changed, we need to build new frameworks accordingly.
The browser, technically known as a ‘user agent’, needs a framework that takes care of all the UI flow. This means that we need the MVC pattern running on the client. This ‘user agent framework’ needs controllers that can render views and it needs a comprehensive routing system based on anchors.
As a business, now that more of your code (a.k.a. intellectual property) is running openly in your browser, where does your strategic advantage come from? Well, it comes from making your backend very intelligent.
The server, who I like to call ‘machine agent’, needs a very solid Application Programmer Interface. The sole purpose of this API is interfacing with different user interfaces (web, iphone, ipad, …). However, it should have a separate facility to deal with other ‘machine agents’ like Google Bots. Other servers that interface with your system have very different needs than third-party user interface applications. An example of this would be API calls that perform bulk operations (like Twitter’s mass-following call).
In order to deliver smart services that can compete, machine agents need to be able to analyze the state of their internal universe (business models) and act on them. This could be a simple iPhone push notification that gets sent after a certain event happens, or it could be after the completion of a statistical analysis. Web backends need to become more event-driven (like Javascript) because a simple cronjob will no longer suffice.
Machine-agents need to be able to integrate with other services. Sometimes this means that they need to be able to fetch many feeds from a single service. I consider this to be one of the hardest technical challenges of most projects I work on. For example, if I want to do something semi-intelligent with someone’s Twitter activity, I will need to first fetch all his data, import it and then analyze it. This is very expensive and I haven’t found any economically viable solutions yet. Of course no one wants to passively fetch feeds and then analyze them, it would be much better to do something like server-to-server long polling (e.g. listening for Tweets with a certain keyword), but sometimes you have no choice: you have to aggregate.
Conclusion
The use of Javascript on websites has been unstoppable and now it has spread to other platforms like the Palm Pre and iPhone. Javascript is a programming language that’s here to stay.
It is now common practice for web application developers to off-load a lot of work to the browser. This migration to the browser together with the changing technology landscape requires us to re-think web application architectures and frameworks.