Big-data could be the game changer in future. Data and big-data are conceptually similar but the later differs technically due to the enormity in volume and the corresponding difficulty in storage. Big-data would imply information that is collected in microseconds from any or all activities that can be captured through recent and path breaking technologies. And of course its use is wide ranging, spreading across a spectrum from simple identification of technical snags (traffic jams, flight delays or power failures) to possible prediction of life expectancies of an individual from signal collected over a period from his eating, search behaviour online and so on. Until this point it is fine; but the big question is how do we comprehend big-data? What do we expect in future? I am not going to go into the tricky affair of the morality of collecting such data from individuals. A better way to put it is how many of us know and are exposed to the data collection business that goes around us. This point in time of human history is only the beginning of the graph where there is an overabundance of big-data. Agencies and institutions that have the logistics have already started collecting and storing it. Imagine data accumulation at the level of being able to successfully predict what each and every individual, institution or nation would be doing say ten minutes from now. That’s like being God. Is it? Need not be. An analogy with natural resources would help us to predict that market mechanism would erase monopoly ownership of big-data in the long-run.
Is big-data a natural resource?
Why a natural resource? Because just like the natural resources it is natural that each of our act whether intended or unintended produce data as an outcome. It is difficult to classify it as renewable because what has been produced cannot be reproduced under the same conditions. So data that I generated through an act yesterday may be reproducible today but not under the same conditions as yesterday.
The fate of natural resources has been this: For a long period of time these resources were subject to constant exploitation, and mankind benefited much out of this. Demand for these resources steadily increased. The good thing was that supply also increased and at times outpaced demand due to technological progress as well as innovative methods of exploitation. The long-term prices has been continuously declining as a consequence. This is also due to the fact that technology helped to produce alternatives for some of these resources.
Now consider big-data, it is a (non) renewable resource. Just like natural resources at its earliest stage in development, whatever has been produced till now is up there for exploitation. People who had the skill in identifying the benefits of natural resources, who had the logistics to extract it benefitted at this early stage in natural resource exploitation. Trade allowed them to prosper. This is just similar to people who have the logistics is getting into the data accumulation process. Just like those laws and regulations which were revised time and again to determine who should own the natural resources, there are laws (at a nascent stage) being formulated to control the generation and accumulation of big-data. Google’s ‘forget-me’ is the outcome of such attempts to legally negotiate possible outcomes of such accumulation.
Big-data in the long-term
In the long-term the following might result. Demand for big-data would be increasing considering the various potential businesses that could be done with it. For instance, predicting victors in elections would become much easier and much more accurate (questioning the democratic process itself), health would be a major area benefitting, and many avenues for business which can be developed after understanding the choices and preferences of people would increase. All this might just reengineer the world that we live in now with new forms of institutions and mechanism developing in response to these possibilities. Supply of big-data would also increase. And just like the exploitation of natural resource, newer technology and innovation would make it cheaper to extract more data. The costly logistics could be avoided. Thus supply would outpace demand and lead to a long-term decline in prices. The possibility of substitutes is difficult to imagine at this point; but in case big-data finds its substitutes, prices would decline further.
So demand and supply is likely to bring down big-data to affordable levels considering the possibility that it is like a natural resource. However, what is going to be crucial is the period ‘in between’; that is between now and the time when such data becomes affordable to everyone. For natural resources, such a period was mostly misutilized in fighting for ownership rights. The state finally won this fight and ended up assuming the role of protectors of natural resources. But for big-data, the period should be better used to develop a policy framework that could ensure privacy. We can also use this time frame to understand the various possible misuse of information and tighten the legal apparatus to ensure such things are minimal. Another possibility that could be thought about is on the individual’s opportunity to trade his data. The richness of it and the demand would ensure that each individual could sell the data to whoever demands it. We might just end up on a positive note in future if these considerations are duly discussed.
Rahul V Kumar
Centre for Public Policy Research