Homo futuris: AI, data privacy and uncertainty

Artificial intelligence (AI), machine learning and deep learning are growing trends being developed across various magnitudes encompassing tremendous amounts of data. This collation of data has made impossible things possible, improbable things positive, and many things available to individuals with a few clicks. With this data growth, we are progressing towards a world that rests on mathematical probabilities.

Take the probability that a rat might die if it doesn’t escape the cat vis-à-vis the possibility that the cat might catch him before he escapes. In order to assist itself, the rat requires a lot of data to analyze the probability of survival, how to effectively extract the data to understand its opponent, and all of this through de-codifying the algorithms created by its community.

The energy propelling all these probabilities is “big data”, often referred to as high-volume, high-velocity and high-variety information, and its effective analysis. These applications with machine learning tools are recording every bit of information fed into their systems with or without knowledge from the users, as there is so much information, with limited ability to utilize it to our advantage.

We have relied on these applications, but isn’t all of this at the expense of data privacy? The online form we fill in for bank insurance, the statistical data recorded from our FitBit, even the posts we upload on social media – it is evident that this use of big data in all volumes, sizes, shapes and patterns has major implications for privacy, data protection, creativity, territoriality and related rights of individuals and of big data users, all of which need to be unlocked.

Pravin Anand is managing partner at Anand and Anand, and Mrinali Menon is an associate at the firm