16 February, 2007

Economic Growith - India and China

As per the latest report Indian GDP has grown at the rate of 9% in 2005-06 and expected to grow at 9.2% for 2006-07. All the analyst keep wondering if this is a one of case of high growth or have India entered a high growth phase. They break up the growth sector wise, look at various economic parameter like investment, money supply, inflation and even government deficit. However, I have not seen any analyst link this growth rate to export performance and I find this very surprising!

For the last few years the export growth and growth of IT & ITES has been steadily around 30%. The combined contribution of these to the overall GDP has been increasing from just above 10% few years back to nearly 20% now. If you breakup the economy into export and non-export, then you will see a surprising result. The growth rate of the rest of the economy has remained at around 5%. Because of the significantly faster growth in export, the relative share of export is increasing. As a result, the overall GDP growth has been accelerating without any change in the growth rate of export or rest of economy!

My calculation shows that GDP growth for 2006-07 is likely to be around 9.5%! Also, by 2009 we would have reached a double digit growth. I suspect that India will overtake China in GDP growth rate in 2009 for the following reasons.

  1. China's growth is also fueled by export, but its share of export to total GDP is close to 50%
  2. China will find it difficult to sustain the export growth rate
  3. The Olympics to be held in China in 2008 will a contributing factor to the growth
  4. So, in 2009 that factor will not be there
  5. On the other hand India is hosting commonwealth games in 2010
  6. The investment in infrastructure would have reached its peak in 2009

08 February, 2007

Wisdom of the Crowd vs. Collective Intelligence

When I search the Internet for material on CI, I frequently come across the term "Wisdom of the Crowd" (WoC). Can these terms be interchangeably used? I think there is a significant difference between the two term. In my earlier post I had elaborated on Collective Intelligence as "the characteristics of a complex system to organize itself and appears to be more intelligent than its constituent parts". It is been a property of any complex system, both man made as well as in the nature.

The principle behind WoC is that a conclusion reached in collaboration with and from competition among multiple individuals will be more intelligent than any conclusion reached by an individual, no matter how smart. The focuses on aggregating isolated inputs. For this to work, an algorithm for summarizing the individual input into one collective verdict is needed. I can not think of an example of this in the nature. It is devised by us human being.

The whole Open Source movement is an example of CI, where as the Google search is an example of WoC. I leave it to you to decide what the following phenomenon are?

  • Wikipedia
  • Free market economy
  • Holding election in democracy
  • SecondLife
  • Stock market
  • Scientific research

That leads us to the next question. Which of these are more effective. The answer obviously "it depends". Normally they applicable in different circumstances. But I am curious to compare the two. Can we think of a situation where both are applicable?

Would you consider del.icio.us an example of CI or WoC? I think it is an example of CI. At least it is much closer to CI than Google search. I have the following experiment in mind. I will take a term say "Web 2.0" and search in Google and del.icio.us. I will compare the relevance of the result rating the top 10 hits in a scale of 1-5. It will be subjective, that is it will be my opinion. I will also repeat this experiment after some time to examine the stability of the result. Let me do the experiment ...

The Google hits are:

  1. O'Reilly -- What Is Web 2.0 (5)
  2. Web 2.0 - Wikipedia, the free encyclopedia (5)
  3. Web 2.0 Conference - November 7-9, 2006 - San Francisco, CA (3)
  4. Web 2.0 (5)
  5. Web 2.0 Workgroup - A network of Web 2.0 resources (4)
  6. Digital Web Magazine - Web 2.0 for Designers (3)
  7. Go2Web20.net - The complete Web 2.0 directory (4)
  8. Web 2.0 Validator : We're the dot in Web 2.0 (2)
  9. SEOmoz's Web 2.0 Awards (3)
  10. WEB 2.0 JOURNAL (3)

Average = 3.7

The del.icio.us hits are:

  1. script.aculo.us - web 2.0 javascript (3)
  2. The Best Web 2.0 Software of 2005 (web2.wsj2.com) (3)
  3. O'Reilly -- What Is Web 2.0 (5)
  4. Web 2.0 Directory : 900+ Web 2.0 Sites in 50+ categories : eConsultant (4)
  5. Go2Web20.net - The complete Web 2.0 directory (4)
  6. Web 2.0 Workgroup - A network of Web 2.0 resources (4)
  7. Sacred Cow Dung: All Things Web 2.0 - "THE LIST"(4)
  8. SEOmoz's Web 2.0 Awards (3)
  9. Web 2.0 how-to design style guide (3)
  10. Software Development in the Real World: Best of the Best Web 2.0 Web Sites (4)

Average = 3.7

They are same!!! Believe me, I did not manipulate the result.

What is interesting is del.icio.us has thrown up more sites which will appeal to techies. Google sites are more of general interest.

I will repeat this experiment after a few days.

01 February, 2007

Can we engineer Collective Intelligence?

I have been following the developments in web 2.0 for some time now with keen interest and observing the unfolding of Collective Intelligence (CI). This phenomenon of CI, as you know, is the characteristics of a complex system to organize itself and appears to be more intelligent than its constituent parts. This has been in evidence in nature from the beginning of evolution.

The most interesting part of CI is its ability to come up with a totally unexpected and surprising outcome. Imagine, five years back, somebody predicting that we will shortly have an encyclopedia on the web freely accessible and richer in content than Britannica; where anybody in the world can contribute with no editorial control. I am sure it would have been considered as a laughable idea. Yet, today, we have Wikipedia.

Similarly, the success of Open Source is nothing but astonishing. Whoever would have believed, 10 years back, that the biggest threat for Microsoft Windows will come not from IBM, Apple, Sun or not from any new startup but from a large community of people who write code for an Operating System for no monetary gain. In fact, before the success of Linux, it would not have been thought possible for a very large community of people to write an operating system collaboratively without any central control.

However, if we look at nature, we should not be very surprised. Have you ever noticed the highly coordinated movements of flocks of birds or schools of fish. It is one of the most fascinating phenomena to be found in nature. The group seems to turn and maneuver as a single unit, changing direction almost instantaneously. There is no leader, no overall control; instead the flock's movements are determined by the moment-by-moment decisions of individual birds, following simple rules in response to interactions with their neighbors in the flock. There has been a fair amount of research into this area and many simulation models have been produced.

In the film Batman Returns a horde of large black bats swarmed through flooded tunnels into downtown Gotham. The bats were computer generated. Each bat was instructed to move about on its own on the screen following only a few simple rules: don't bump into another bat, keep up with your neighbors, and don't stray too far away. When the algorithmic bats were run, they flocked like real bats.

Ant colonies display similar intelligent behavior. Though an individual ant is a relatively simple organism, the colony has a highly structured social organization. As a result of this organization, ant colonies can accomplish complex tasks that in some cases far exceed the individual capabilities of a single ant. Their ability to locate food is nothing short of astonishing.

These phenomena have led to a new and novel researcher discipline called Swarm intelligence. Algorithms like the ant colony optimization algorithm are inspired by the behavior of ants in finding paths from the colony to food. Such algorithms are used to solve complex optimization problem like traveling salesman problem.

One common characteristic of the examples I have mentioned above is the surprise element each one of them posses. If you breakup each of the system into its constituent parts and analyze them, you will find it difficult to believe that combining them can produce such startlingly intelligent behavior.

Currently, we do not have a theoretical understanding of Collective Intelligence or Emerging Behavior of a complex system. The normal method we follow in understanding any large system is to break the system down to smaller, more manageable units and understand each of them separately. In case of CI, this approach will not work because in most cases, intelligent behavior will not emerge till a critical mass is reached. So, the individual elements will not tell us much about what the behavior of will be.

Of course there is always a possibility of a scientific breakthrough happening in our understanding of complex system. But till then we will not be able to either manage or engineer systems based on CI with any certainty. Any success will be pure chance. However, that should not stop us from taking advantage of any known or emerging CI behavior. That will be a subject of my future discussion.