Over the last decade, data has become all-pervasive, rewriting conventional business and governance models, and redefining personal lives. The global technology industry has been driving this transformation, which stands at a crucial inflection point. For people, data has made daily tasks simpler and easier. For businesses, data has emerged as the key to competitive advantage.
Today, every 48 hours, human beings create the equivalent of all the data generated through human history up to 2003. However, only 20 % of this data is currently searchable as 80%, or the "dark data", is unstructured. While structured analytics provides the what, where and when of a business challenge, unstructured content analytics using artificial intelligence (AI) provides the why and how. India is poised not just to lead this 'data revolution', but also transform its data for the benefit of the economy given the enormous amount of data being generated by over 1 billion people. This will be driven by the intersection of big data and machine learning, or AI, which is transforming the way individuals, governments and companies interact and do business.
While the data economy infused with new-age technologies presents significant opportunities in India, it also has the potential to be the greatest concern - from mass data breaches to intentional manipulation of online platforms. The quintessential question is, how do we benefit from this new world while limiting the risks? It is all about responsible use of data. In a rush to harness the potential of data, organisations are losing sight of basic expectations that individuals, enterprises and communities have regarding security, privacy, trust of data shared and more. There is an obligation to handle data responsibly throughout the data lifecycle.
It is also crucial to usher in AI with responsible data stewardship. Clients' and individuals' data are their own, and government data policies should be fair, equitable and prioritise openness. Unique insights derived from clients' data are their competitive advantage, and companies should not share them without the consent of their clients.
In the digital world, the flow of data is akin to 'digital trade agreements'. Like with any other form of trade, protectionism is often reciprocal, which means in a steady state, restrictions apply both ways. Let's consider some obvious unintended implications of preventing cross-border flow of data.
Data of Indian patients pertaining to cancer, genomics, clinical trials, etc., not being available for global experts for drug discovery or personalised medicine, or reciprocally, data of a global enterprise's customers not being made accessible to data science and AI experts in India.
However, this can't be taken as supporting evidence for a blanket policy, because it is driven by a narrower lens on select data scenarios. Similarly, data on, say, desktop software product usage is OK to keep within a user base. These are indeed extremely narrow data sets, which are not representative of the huge opportunity that data presents across industries.
Based on our experience as custodians of data for the world's largest organisations, we understand the full potential of data flow and innovation and, at the same time, own the responsibility of protecting the privacy and competitive advantages encapsulated in that data.
In any of these situations, it is important for organisations to oppose any effort to weaken or limit the effectiveness of commercial encryption technologies, while the government should promote the usage of internationally-accepted encryption standards and algorithms, rather than country-specific mandates to protect clients'/individuals' data and transactions.
Those responsible for driving technological progress have an obligation to ensure that new innovations solve social problems within the social framework. A unique partnership between policymakers, business leaders and citizens, led by government, will be able to build the future of work and life in the age of data. It is with this view that we encourage carefully-designed "digital trade agreements" on data, as opposed to simplistic policies that have a detrimental impact on innovation.
The article was originally published here