The past couple of decades have witnessed a “data deluge” in various fields - from astronomy to genetics to healthcare.
While most other sciences are based on causation, big data analytics is based on correlation.
There is a possibility that big data predictions can be used to punish people on intentions alone, even before they have acted.
The past couple of decades have witnessed a “data deluge” in various fields - from astronomy to genetics to healthcare. Taming this deluge and finding useful patterns is the objective of the new field of big data analytics.
Viktor Mayer-Schonberger and Kenneth Cukier’s Big Data: A Revolution That Will Transform How We Live, Work and Think (2013) focuses on various aspects of big data: its current status, its future growth, its implications to society, its risks and so on.The analysis of big data springs surprises that are not immediately evident. An analogy would help understand this-
The principle behind nanotechnology is that when you get to the molecular level, the physical properties can change.... At the nanoscale ... more flexible metals and stretchable ceramics are possible. Conversely, when we increase the scale of the data that we work with, we can do new things that weren’t possible when we just worked with smaller amounts.
Consider another analogy-
For humans, the single most important law is gravity: it reigns over all that we do. But for tiny insects, gravity is mostly immaterial. For some, like water striders, the operative law of the physical universe is surface tension, which allows them to walk across a pond without falling in.
In a similar manner, while most other sciences are based on causation, big data analytics is based on correlation. In other words, the main question one asks is: what is the connection? Not, why does it connect so? This may even bring down the importance of hypothesis generation in research.The authors dwell a lot on the benefits of big data analytics and how Google and Amazon are profiting from this. I will not go into all that. Best to read the book. I want to focus on the risks of the “dictatorship of data” as privacy is slowly eroded, or as the authors put it, redefined.
The authors write-
With big data promising valuable insights to those who analyze it, all signs seem to point to a further surge in others’ gathering, storing, and reusing our personal data. The size and scale of data collections will increase by leaps and bounds as storage costs continue to plummet and analytic tools become ever more powerful. If the internet age threatened privacy, does big data endanger it even more? Is that the dark side of big data?
Big data may make prediction of future propensities possible. There is a possibility that big-data predictions can be used to punish people on intentions alone, even before they have acted. If you remember the movie Minority Report (2002), this is exactly what happened. Future proclivities of individuals were foreseen by clairvoyant women and the would-be criminals were apprehended before they committed the crime. This can now become fact - only this time prediction would be not by clairvoyant women but by big data - and the prediction can be acted upon by government agencies.
The authors state:
[W]hile they are not dragging us away in the middle of the night, firms [like Amazon, Facebook and Twitter] amass mountains of personal information concerning all aspects of our lives, share it with others without our knowledge, and use it in ways we could hardly imagine.
In The Road Ahead (1995), Bill Gates compared the invention of the Internet to the invention of the printing press by Gutenberg. Gates went into how the Internet would revolutionize the world much as the printing press had. That was in 1995.
A lot has happened in the succeeding 20 years. The authors of this book hark on the same analogy and state that we are in the incipient stages of a revolution that is bound to transform the world.The authors propose some basic regulatory measures to control the onslaught of big data.
At present, private data is being made public subject to the private individual’s consent. But in the era of big data, the individual may not be able to foresee all the future uses of the data by secondary organizations. Hence, this concept of consent loses relevance. The authors say that the burden of responsibility should be shifted from the public to the users of data and these users should be held accountable. The authors propose that the “data barons” should be governed by antitrust-like laws though I do not know how effective that would be. It remains to be seen whether big data will take on the mantle of an Orwellian Big Brother.