Lately, I have had a lot of free time to myself. Not that there's been no work - no - but basically, I've been goofing up for some time - primarily because of this bloody disease called "common cold". Anyway, with a light head (literally empty) and some time at my disposal I expected myself to come up with something ridiculous for my blog - so here it is.
How does one measure what people want from technology? In other words, how does a technologist determine which problem should he/she solve? Well, (s)he looks at the current scenario of things and says hey, this could be done better - or maybe, see something which is not being done and start doing it. And then, (s)he comes up with a new technology/method/algorithm/notion/... which attempts to solve the problems. So what's wrong with this? Evolution, that's what!!
Let's take the example of computers. In their early days, people[1] knew nothing about computers. Then, IBM, Apple etc. popularized computers to the extent that several individuals got involved and then started using computers. As a result, the very things that were required of computers - changed (or more correctly, evolved). TTBOMK, computers are being used almost everywhere. And you can find people in every nook and corner who know tons about computers. So what is really needed from computers now?
My point here is that people are evolving to learn a lot of technology. We can draw a parallel with Heisenberg's uncertainity principle here. Crudely, the principle said that if you use light to measure the position and momentum of a particle, you can't do both accurately, because the light's energy would move the particle or change it's momentum.
Similarly, if you try to evaluate the success of a technology, you will notice that people would have evolved to that technology and the latter would hardly be measuring up to it.
I can take a small example - something which I have noticed. There's this notion of data mining, which is supposed to help the non-IT sector companies with business intelligence. With increasing awareness to data mining techniques, thanks to extensive customer-training programs, these non-IT companies have started expecting more from the software. It is like you were constructing a complex solution to somebody's IT problems, and somebody "educates" that person about the things involved in constructing such a solution - your efforts will mostly be wasted. So how does one estimate what a customer expects? I mean, go figure.
[1] Normal people - not nerds/geeks/engineers/idiots
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