How Can HR Policies Ensure Payroll Oversight and Preserve Worker Dignity in the Face of Digital Identity Errors?

On August 19, 2025, the Haryana Human Rights Commission took suo motu cognizance of the case of Vijay Kumar, a diligent health department employee in Rohtak who was mistakenly marked as "deceased" in Aadhaar records. This error led to repeated denial of his salary. The HHRC condemned this mistake as a severe violation of his right to livelihood and dignity under Article 21 of the Constitution and Article 7 of the UN ICESCR. Authorities were ordered to correct the record, release his salary immediately, and prevent such incidents in the future.

Imagine reporting to work but being denied pay because your digital identity declares you're dead. Such a glitch can cause panic, shame, and fear, crushing one's dignity. Vijay's experience highlights a growing tension: digital bureaucracy failing the very humans it's meant to serve. For HR leaders, the message is clear: digital-first systems must retain human oversight. A payroll stoppage shouldn't turn into existential trauma, and oversight committees must watch for these failures before platforms cause harm.

This case intersects digital governance, payroll reliability, and human rights. Compensation disruptions violate Payment of Wages norms, and Aadhaar errors reflect data governance failures. HR must institute identity reconciliation audits, "living status" checks, and a rapid escalation pathway for salary disruptions. Compliance isn't just about process—it's about protecting dignity. Systems must pair digital with empathy, balancing automation with human correction. Boards need assurance that payroll systems can't "kill" an employee.

What payroll oversight guardrails (e.g., identity flags, manual audits) should HR put in place to catch technical life/death errors? How can HR policy honor digital compliance while preserving worker dignity with redundant human checks?

To prevent such incidents in the future, HR departments should consider implementing the following measures:

1. Regular Identity Reconciliation Audits: These audits should cross-verify employee data across multiple databases, ensuring that there are no discrepancies in the status of the employee.

2. Living Status Checks: Regular checks should be conducted to confirm the 'living status' of employees. This could be as simple as a monthly or quarterly confirmation from the employee.

3. Rapid Escalation Pathway: A process should be in place for employees to report and quickly resolve issues related to their identity or payroll. This pathway should be clear, easily accessible, and should guarantee a swift response.

4. Redundant Human Checks: Despite the move towards digitalization, it's crucial to have human oversight to catch errors that automated systems might miss. This could involve manual checks of payroll and employee status at regular intervals.

5. Employee Awareness: Employees should be made aware of these checks and processes. They should know who to contact and what to do if they face a similar situation.

6. Regular Training: HR staff should be regularly trained to handle such situations and to stay updated on the latest in digital compliance and data governance.

Remember, the goal is not just to comply with the law but to ensure the dignity and rights of employees are not compromised by digital errors. Balancing automation with human oversight is key to achieving this.

CiteHr Think-tank,
The report is not only shocking but disgusting nature.
We can't say what kind of Pay roll system adopted by the Haryana Govt matters a lot.
The department of Birth and death should be taken to task for such records of declaring live person as dead. Secondly, aadhar has no role in pay roll rocess.
This could be in an end process of bank transfer the aadhar intercept in identity.
This can be said in the case of Vijay Kumar, the birth and death registaan depart made some erroneous entry of X person as dead wrongly one or two digit change declared Vijay Kumar as dead against X.
Therefore, limited use of digital data. Because this can happen with anyone because Aadhar update is not done by the single unit rather thousands centres doing on back-hand.