Aadhaar, NPR & Developmental Benefits

Concurrent Necessity: Arguments For and Against

The question of whether Aadhaar and NPR need to run concurrently is complex. Proponents argue that both schemes serve distinct purposes. Aadhaar focuses on establishing identity for service delivery and financial inclusion, while the NPR aims to collect demographic data for planning and policy formulation. The NPR, they contend, can leverage the Aadhaar infrastructure for verification, enhancing its accuracy and efficiency. However, this argument overlooks the inherent risks of data convergence and potential for misuse.

Conversely, critics highlight the redundancy and potential for conflict. Both schemes collect similar demographic data, raising concerns about data security and privacy. The compulsory nature of NPR, coupled with the potential for exclusion based on documentation requirements, contradicts the inclusive spirit of Aadhaar. The Supreme Court in K.S. Puttaswamy v. Union of India (2018) affirmed the right to privacy as a fundamental right, raising concerns about the extensive data collection involved in both schemes. Furthermore, the linkage of NPR with the CAA has fueled anxieties about its potential to disenfranchise vulnerable populations, particularly those lacking adequate documentation.

Potential for Developmental Benefits and Equitable Growth

Both Aadhaar and NPR possess the potential to contribute to developmental benefits and equitable growth, but their realization depends on effective implementation and safeguards against misuse.

• Aadhaar: Has facilitated direct benefit transfer (DBT) schemes like PM-Jan Dhan Yojana, reducing leakages and ensuring that benefits reach intended beneficiaries. According to the UIDAI, as of December 2023, over 1.38 billion Aadhaar numbers have been issued. It has also enabled access to financial services for marginalized communities.
• NPR: The data collected can be invaluable for targeted interventions in areas like healthcare, education, and social welfare. Accurate demographic data can help identify vulnerable groups and tailor policies to address their specific needs. For example, identifying areas with high infant mortality rates can lead to focused healthcare initiatives.

However, several challenges hinder the realization of these benefits:

• Exclusion Errors: Both schemes are prone to exclusion errors, particularly affecting marginalized communities lacking documentation. This can exacerbate existing inequalities.
• Data Security Concerns: The centralized storage of sensitive data raises concerns about data breaches and misuse.
• Digital Divide: Limited digital literacy and access to technology can hinder participation in both schemes, further marginalizing vulnerable populations.
• Potential for Discrimination: The NPR, if linked to the CAA, could lead to discriminatory practices and the exclusion of certain communities from accessing essential services.

To maximize developmental benefits and ensure equitable growth, the following measures are crucial:

• Strengthening data privacy and security measures.
• Ensuring inclusive documentation processes and providing assistance to vulnerable populations.
• Promoting digital literacy and access to technology.
• Decoupling the NPR from the CAA to allay fears of discrimination.

A more pragmatic approach would be to focus on strengthening the Aadhaar infrastructure and leveraging its existing data for targeted interventions, rather than pursuing a parallel, potentially problematic NPR exercise.