The role of digitisation in realising India’s vision of becoming a $5 trillion economy cannot be overstated. As per a NASSCOM report, data and artificial intelligence (AI) can add approximately $450-500 billion to India’s GDP by 2025. Rapid digitisation of government operations, however, is accompanied by increasing volumes of citizen data. Such data is typically of two kinds — Personal Data i.e., data containing identifiers through which an individual can be mapped; and Non-Personal Data (NPD) i.e., data excluding personal data.
NPD constitutes the primary kind of citizen data obtained by the government, which possesses the potential of serving as a ‘public good’. To create synergies and devise scalable solutions, integration of NPD in the dispensation of public services is generally being advocated for. Application of high value advanced analytics and AI to NPD across key sectors of the economy can help predict socially and economically sound outcomes. Junctures where such data-driven insights can better inform governance and public functions are meteorological and disaster forecasts, infrastructure capacity and citizen use-patterns, mobility and housing patterns, and employment trends, to name a few.
Unfortunately, unlike Personal Data, there is a stark absence of regulation for NPD. As of date, efforts have been made at the executive level to construct governance policies for the same. The expert committee chaired by Kris Gopalakrishnan in its reports dealt with this at length. Noteworthy issues such as the risk of de-anonymisation of NPD, the institutionalisation of a central authority for NPD, and ownership and data sharing mechanisms were raised therein. Subsequently, the Ministry of Electronics and Information Technology (MeiTY) released the National Data Governance Framework Policy (NPD Framework) which was touted as the first building block of the digital architecture being conceived to maximise data-driven governance. Notwithstanding, neither of the above mentioned provides for an enforceable regime for NPD in India. For this reason, vast reservoirs of NPD stand unregulated and are supported only by limited guidance in dissemination, use, or exchange thereof. Such a de-siloed accumulation results in sub-optimal legal and policy decisions, and engenders sub-par strategies at sectoral and national levels.
Data exchanges are scalable ecosystems which galvanise multiple stakeholders. This makes them a fertile ground for deploying advanced analytics for outcome-oriented decision making and helps achieve economies of scale.
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The unprotected inter-flow of NPD across government departments, third-parties, and citizens can make sensitive aspects of NPD vulnerable due to privacy breaches. This can unfairly benefit capacity-carrying actors like Big Tech. The imperfect analysis of crucial public trends can result in faulty decision-making. Such exchange of data is also inefficient as it fails to unlock the power of interdisciplinary legislative and policy-making.
The NPD Framework, being a pioneering step, also exhibits several gaps. It formulates abstract high-level principles and objectives for NPD governance but lacks tangible, actionable guidance to achieve them. While legislation is expected, practical operationalisation is overlooked, leaving questions unanswered regarding stakeholder rights and obligations across sectors. Additionally, mechanisms for pricing of data and appropriate legal structures for data exchange are not addressed. The absence of standardised governance tools compounds these challenges.
A critical evaluation of the NPD Framework to address the existing gaps will be beneficial. This will supplement MeiTY’s effort to regulate NPD and will help forge data exchanges as suitable media to make NPD interoperable across sectors. By creating a regulatory design for data exchanges in India, public-welfare functions can be digitised and automated to a large extent. This reduces administrative burden, facilitates inter-sectoral integration, builds the safeguards to using/sharing NPD, and makes digitisation of civic functions more participatory in nature.
In Australia, data exchange frameworks and data exchange protocols have been adopted. Data exchanges have been incorporated for sectors such as housing, employment, aged care, agriculture, etc. Similarly, the U.K. and Estonia have also constructed data exchanges specifically to tackle the issue of unemployment.
Formulating a blueprint
In India, the State of Telangana has designed an agriculture data exchange, while India Urban Data Exchange has been established by the Ministry of Housing & Urban Affairs in collaboration with the Indian Institute of Science. Similarly, the Department of Science & Technology has announced its intention to set up data exchanges to implement aspects of the National Geospatial Policy.
Given the budding interest in data exchange structures, it is crucial to formulate a blueprint for governing them in India. Such examination will be at pace with the global discourse on the regulation of data exchanges and supplement the efforts of MeiTY, the expert committee, and other bodies vis-à-vis governance of NPD in India. It will also help operationalise the high-level principles of NPD in India by providing an actionable pathway and laying a forward-thinking framework for the governance of NPD in respect of data exchanges.
Jyotsana Singh is a research fellow at the Vidhi Centre for Legal Policy under its Applied law and technology and Fintech verticals
