Thursday, December 3, 2009

Meaning of Heuristics and why it is important today

Heuristics is the big word, yet a lovely word that you and I should care about. It is synonymous to a "rule of thumb". It can be as simple as Pareto Principle or as complicated as adaptive algorithms. We, the humans love our rules of thumb.

We make decisions using rules of thumb. Everyday as you and I use the web, heuristics get built and decisions you make get captured as data. This is certainly one of the premises for PAKRA's existence.

As Frank Schirrmacher discusses in his HuffingtonPost post The Age of the Informavore
: "This is a very good beginning."

Game theorists, economists, psychologists are promoting the value of Bounded Rationality
principles to model decision-making. The main questions they ask are (a) how do you and I make decisions using heuristics? (b) are these decisions optimal, i.e. the best?

From models to computational algorithms to daily web searches to pattern-recognizing analytics that feed our consciousness from places such as Amazon.com (e.g. "Those who have bought PAKRA Games, also bought ... " --> all these are making us learn and make decisions faster.


Frank Schirrmacher writes, "Gerd Gigerenzer, to whom I talked and who I find a fascinating thinker, put it in such a way that thinking itself somehow leaves the brain and uses a platform outside of the human body. And that's the Internet and it's the cloud. And very soon we will have the brain in the cloud. And this raises the question of the importance of thoughts. For centuries, what was important for me was decided in my brain. But now, apparently, it will be decided somewhere else."

The rule of thumb algorithms that were developed on your and my data, in turn learn/retrain our brain. Moreover, as a society, as we all participate, in this reality/digital existence, we redistribute this wealth of learning.

This makes us (PAKRA), believe that "Real Human Learning" is the ultimate monetization of digital bits.

All that is left for you and I to do is answer the following:
(a) how much do we value "Learning" and
(b) how much are we willing to invest/pay in it?

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