Whitepaper
Balancing Efficiency & Citizen Privacy in Urban Governance
ndian cities are embracing technology at an unprecedented pace. City
managers are establishing digital governance systems and deploying
smart technologies to improve the quality of urban governance
and service delivery. These systems are generating transactional,
operational and sensor data, resulting in cities rapidly becoming datarich.
With this unlimited growth in digital data availability, city managers are
exploring the use of this data to improve decision-making, notifying
governance reforms and catalyzing innovation. A vital example is India’s draft strategy by the NITI Aayog for the use of Artificial Intelligence (AI). At the same time, there is a growing legal recognition of the right to privacy and the need to protect citizen privacy and data internationally.
Data Protection has been a sensitive topic in India ever since the
Supreme Court judgment in August 2017 holding privacy to be a
fundamental constitutional right of every Indian, and the subsequent
work by the Srikrishna committee in producing the Personal Data
Protection Bill in August 2018.
Our research shows that equilibria between governance efficiency and information privacy are not a zero-sum game, as shown in the figure above. By calibrating their existing practices around data collection, data use and data disclosure using the GEI and IPI constructs, city managers can achieve a high level of efficiency while ensuring the privacy of citizens’ information is not compromised in a harmful manner. E.g., city managers can implement simple rules preventing citizens’ financial information and their properties from being accessed by non-revenue functionaries. These entities may not have a direct need for the information to perform their function without reducing the overall quality of service delivery to citizens.
Moreover, by reengineering processes and policies, it might be possible for the city manager to shift the set of possible equilibria towards further improving both governance efficiency as well as information privacy simultaneously. The GEI and IPI constructs are designed to scale from an individual form or service, to city departments and the city at large, thus enabling more targeted policies. We believe the GEI and IPI constructs could act as significant tools in helping city managers make decisions on the collection, usage, and disclosure of data within their jurisdictions in a structured manner. We hope the GEI and IPI constructs will act as crucial building blocks for cities to effectively unlock data economies without compromising citizen privacy by identifying which data and data aggregates can be released safely to spur data-driven innovation.
About Authors
Gautham Ravichander leads eGov’s policy initiatives with the Government of India and partner states. He started his career at Janaagraha where he led the Ward Infrastructure Index Program and was a founding team member of The Education Alliance. Gautham has a MIB degree from Fletcher where his studies focused on social enterprises and leveraging business models to reach underserved populations. At Fletcher, Gautham organized and co-chaired the first
Tufts Innovation Symposium on Scaling Innovation in Emerging Markets.
Dr. Chintan Vaishnav is a socio-technologist, an engineer trained to understand and build large-scale systems with both human as well as technological complexities. He is motivated to build socio-technical solutions that overcome constraints fundamental to improving human conditions in resource-poor environments, and is pursuing this objective at the intersection of Information Technology and Systems, Development, and Public Policy. His current work focus on building the Information Architecture for addressing challenges in agriculture, water, and urban governance.
