Ethics of technology in governance

The first principle

Technology makes the State faster and more consistent, but it does not make it wiser or fairer by itself. A machine applies whatever values and errors are built into its data and design, at a scale no single officer could reach. The ethical question is therefore not whether to use technology in governance, but who remains answerable when it goes wrong, and how the person at the far end of the system can still be heard.

The core

• Efficiency is a real good. Direct benefit transfers, online services and digital records cut delay, leakage and the discretion that breeds petty corruption.
• Algorithms carry bias. A system trained on past decisions learns past prejudice, and because its output looks objective, people question it less. This is called automation bias.
• Explainability is a duty. A citizen denied a benefit or flagged as a risk is owed reasons, and a decision that no one can explain cannot be fairly appealed.
• Accountability cannot be outsourced. Whatever tool is used, a named officer must own the decision, because a machine cannot be held to account in a court or before a legislature.

Dimensions

• Rights: surveillance, data collection and profiling touch privacy, free speech and equality, and each needs a legal basis.
• Equity: the digital divide means those with the least connectivity, literacy and documents are the most likely to be left out by an online first system.
• Institutional: systems bought from private vendors may be closed to scrutiny, so public authority can end up resting on code the public cannot inspect.

In practice

• K. S. Puttaswamy v Union of India (2017): a nine judge bench held that privacy is a fundamental right under Article 21. Any limit on it must pass legality, a legitimate aim and proportionality, as explained in the note on schools of normative ethics.
• Puttaswamy (Aadhaar) (2018): the Supreme Court upheld Aadhaar for welfare benefits but struck down its mandatory use by private companies.
• Anuradha Bhasin v Union of India (2020): restrictions on the internet must be lawful, proportionate and open to review, and orders imposing them must be published.
• Digital Personal Data Protection Act, 2023: it requires consent or a lawful ground for processing personal data, places duties on data fiduciaries, and sets up a Data Protection Board of India. The Rules were notified in November 2025 with phased compliance over 18 months, and penalties can reach ₹250 crore. Section 17 allows the Central Government to exempt its agencies on grounds such as sovereignty, security and public order; the government sees this as necessary, while critics see it as too wide.

• Online methods and vulnerable groups: online meetings, approvals, classes and telemedicine save time and reach remote areas, but they can leave out the elderly, the disabled and those without a device or signal, and they weaken privacy when sensitive talks happen on shared phones. Keeping an offline route open is the ethical minimum.

Issues and way forward

• Opaque systems, because vendors claim trade secrets and departments lack technical staff. Publish the purpose and logic of public algorithms, and require independent audits before high stakes use.
• Exclusion by design, because systems are built for the typical user. Build in an exception route so that no one loses an entitlement because a machine failed, and track denials by group.
• Data collected without limits, because storage is cheap and data seems useful later. Collect only what is needed, keep it only as long as needed, and tell people what was taken.
• Officers on social media, where the line between personal views and official position blurs. Service conduct rules on political neutrality and on speaking about government policy apply online as much as offline.

Common confusions

• Privacy and secrecy. Privacy protects the citizen's personal sphere from the State and others. Secrecy hides the State's actions from the citizen. A good system increases the first and reduces the second.
• Automation and AI. Automation follows fixed rules written by people. AI learns patterns from data, which is why its reasoning can be harder to explain and its bias harder to see.
• Digital literacy and digital access. Access is having a device and a connection. Literacy is the ability to use them safely, and many have the first without the second.

For the exam

• Keyword bank: artificial intelligence, algorithmic bias, automation bias, explainability, human in the loop, privacy, proportionality, data minimisation, consent, data fiduciary, biometric exclusion, digital divide, misinformation, offline alternative.
• Previous year questions: Practise the previous year questions on this topic →
• Introduction lines:
  • The Digital Personal Data Protection Rules, notified in November 2025, give organisations eighteen months to comply, which shows how new India's data protection regime still is.
  • In K. S. Puttaswamy v Union of India (2017), nine judges of the Supreme Court held that privacy is a fundamental right, so every use of data by the State must be lawful, necessary and proportionate.
• Conclusion lines:
  • Technology should widen the State's reach without narrowing its conscience: the machine may assist, but a person must answer.
  • A digital system is judged by the citizen it fails, not by the average citizen it serves.