Key Highlights

  • The Office of the Registrar General & Census Commissioner, India (ORGI) has formally notified a 40-question schedule for the second phase — Population Enumeration — of Census 2027, compared with 29 questions in the 2011 Census.
  • New fields introduced include: Aadhaar, Voter ID, mobile number, nationality, parents' details and bank accounts.
  • Census 2027 will be India's first fully digital and self-enumerated demographic exercise.
  • Concerns have emerged over the necessity of collecting extensive personal information and its implications for privacy, data integrity and citizenship profiling.

Background: Census as a Statistical Exercise

  • The United Nations defines a census as the process of collecting, processing and analysing demographic, economic and social data at the smallest geographical level.
  • The UN Fundamental Principles of Official Statistics emphasise:
  • Maintaining confidentiality of individual information.
  • Using data strictly for statistical purposes.
  • In India, the Census Act, 1948 provides statutory confidentiality safeguards for census data.

Major Concerns Regarding Population Enumeration of Census 2027

1. Shift from Statistical Exercise to Citizenship Profiling

  • Several new questions — parents' birth details, declared nationality, Aadhaar, Voter ID, passport, driving licence and mobile number — closely resemble information sought for the National Population Register (NPR).
  • Critics fear that collecting parental details and nationality could shift the Census from a statistical exercise towards population and citizenship profiling, potentially facilitating a National Register of Citizens (NRC).
  • Despite safeguards under the Census Act, 1948, concerns remain over possible sharing of Census data with the NPR or other administrative systems, undermining the principle of purpose limitation.

2. Methodological Flaws in Caste Enumeration

  • SC and ST categories will be selected from a predefined list.
  • Other castes, including OBCs, will be recorded through an open-text field based on the respondent's declaration.
  • Risks: different spellings, regional names and sub-caste identities could produce duplicate or unclassified entries.
  • Precedent: The 2011 Socio-Economic and Caste Census (SECC) reportedly produced around 46 lakh caste names, making standardisation and meaningful analysis extremely difficult.
  • Without a robust standardisation and validation mechanism, the exercise may generate extensive data but limit its usability for policymaking.

3. Privacy Risks in a Digital Census

  • Details such as Aadhaar, Voter ID, passport numbers and Covid-19 vaccination location have little relevance for generating aggregate statistics needed for socio-economic planning.
  • Centralising multiple personal identifiers into linkable digital profiles elevates risks of:
  • Data breaches
  • Unauthorised access
  • De-anonymisation
  • Critics warn this shift from statistical data gathering to individual-level tracking compromises privacy, violates purpose limitation, and could facilitate state surveillance.

4. Respondent Fatigue and Practical Challenges

  • The 40-question questionnaire may increase respondent burden; the primary respondent may not have immediate details of every household member, leading to incomplete or inaccurate responses.
  • The challenge is greater in institutional households (hostels, old-age homes), where administrators may not possess detailed parental or identity information of all residents.

5. Methodological Challenge: De Facto Enumeration

  • The de facto enumeration approach (counting people where they are found on census night) may lead to undercounting of migrant workers, who may be away from their usual place of residence during the Census.

Measures Needed to Ensure Census Integrity

  • Standardise Caste Data: Replace the open-ended caste field with a standardised, consultative caste list (drop-down menu) to avoid fragmented and unusable data.
  • Limit Non-Statistical Data: Remove granular administrative identifiers like Aadhaar, passport and bank account numbers; a simple "Yes/No" on bank account ownership suffices for financial inclusion data.
  • Strengthen Data Verification: Conduct a robust Post Enumeration Survey (PES) to identify undercounting and inaccurate responses.
  • Separate Census from NPR/NRC: Establish clear legal and administrative firewalls to prevent Census data from being repurposed for citizenship profiling or administrative tracking.
  • Robust Data Protection Architecture: Implement stringent cybersecurity protocols aligned with the Digital Personal Data Protection (DPDP) Act, 2023 to prevent unauthorised access or cross-linking of census databases with other government servers.
  • Strengthen Cybersecurity: Ensure end-to-end encryption, independent security audits and strong access controls for the digital Census ecosystem.

Related Legal and Institutional Framework

  • Census Act, 1948: Statutory basis for census conduct; provides confidentiality safeguards.
  • Digital Personal Data Protection (DPDP) Act, 2023: Governs digital personal data processing; relevant for the fully digital Census 2027.
  • ORGI: Apex agency responsible for conducting the Census and maintaining the NPR.
  • UN Fundamental Principles of Official Statistics: International benchmarks for confidentiality and statistical purpose limitation.

Significance for India

  • Census data underpins delimitation, reservation policies, welfare targeting, fiscal devolution and planning.
  • The caste enumeration in Census 2027 is politically and socially significant, being the first comprehensive caste count since 1931; its methodological design will determine data usability.
  • Public trust and voluntary cooperation are essential for accurate enumeration; perceived surveillance could depress response quality.
  • The outcome will shape India's evidence-based policymaking capacity for the next decade.

Conclusion

The integrity of the census is fundamentally anchored in public trust. Ensuring that the exercise remains a purely demographic tool — shielded from political polarisation, stripped of extraneous administrative variables, and fortified by rigorous statistical protocols — is non-negotiable for evidence-based policymaking in India.