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Introduction
Human civilisation has always created tools to extend its abilities. The wheel increased mobility, machines transformed production, and computers accelerated the processing of information. Today, artificial intelligence has taken this relationship to a new level. Machines can analyse medical reports, recommend financial decisions, drive vehicles under certain conditions, generate content and assist governments in delivering public services.
However, this progress raises a fundamental ethical question: when a machine makes a mistake or causes harm while acting on behalf of a human being, who should be held responsible?
A machine may execute an instruction, identify a pattern or make a prediction, but it does not possess human moral responsibility in the same sense as a person or institution. Therefore, technology may perform the action, but accountability must remain with those who design, deploy, control or authorise it.
The Difference Between Action and Responsibility
Machines are increasingly capable of performing tasks that once required human intervention. Yet the ability to perform an action is different from the ability to understand its moral consequences.
A machine may identify a patient as low-risk based on available medical data. If that assessment is wrong, the consequences may be serious. Similarly, an automated system may reject a person’s application for a public benefit without properly recognising exceptional circumstances.
In both cases, the machine has produced an outcome, but the responsibility for the system’s design, limitations and use belongs to people and institutions.
Responsibility involves more than producing a result. It requires the ability to explain decisions, recognise harm, correct mistakes and provide remedies to those affected.
Delegating a task does not mean delegating the duty to answer for its consequences.
Artificial Intelligence and Ethical Decision-Making
Artificial intelligence offers significant benefits in healthcare, education, agriculture, transport and public administration. It can process large volumes of data, identify patterns and support faster decision-making.
However, AI systems depend on the data, objectives and assumptions used to develop them. If training data contains historical discrimination, an AI system may reproduce that discrimination. If its objectives reward speed without adequately considering fairness, it may produce efficient but unjust outcomes.
For example, an automated recruitment system trained on biased historical hiring data may disadvantage qualified candidates from underrepresented groups. The resulting discrimination cannot simply be excused by saying that the algorithm made the decision.
Human beings and organisations chose the data, established the criteria and decided to use the system. They must therefore remain accountable for its consequences.
Autonomous Weapons and the Value of Human Judgment
The issue becomes even more serious when machines operate in situations involving life and death.
Autonomous weapons systems raise difficult questions about whether machines should be allowed to select and engage targets without meaningful human control. Military decisions require assessments of context, proportionality and the distinction between combatants and civilians.
An algorithm may process information quickly, but speed alone cannot establish the moral legitimacy of using lethal force.
The use of such systems must be governed by applicable international humanitarian law and effective human oversight. Responsibility cannot disappear into a chain of software developers, military operators and automated decisions.
The more serious the potential harm, the stronger the need for clear accountability.
Governance: When Algorithms Decide Citizens’ Futures
Governments are increasingly using digital systems to process applications, detect fraud, allocate resources and improve public services.
These tools can reduce delays and improve consistency. However, public administration is not merely a technical exercise. It also involves constitutional rights, fairness and individual circumstances.
Imagine a welfare beneficiary whose assistance is incorrectly stopped because of a data mismatch. An automated system may classify the person as ineligible, but the person may still depend on that assistance for food and essential needs.
If officials refuse to review the case because the computer has already made the decision, technology becomes a barrier between the citizen and justice.
Therefore, automated public decisions must include transparency, human review and accessible grievance-redressal mechanisms.
A citizen must never be left without a remedy simply because a decision was made by a machine.
The Indian Context
India’s digital transformation has created opportunities to improve service delivery, financial inclusion and administrative efficiency. Digital public infrastructure can reduce intermediaries and help public services reach millions of people.
At the same time, digital governance must protect privacy, equality and dignity. The Digital Personal Data Protection Act, 2023, reflects India’s evolving legal framework for personal-data protection, although its scope and implementation must be considered according to the applicable provisions and rules.
As AI becomes more widely used, India needs clear institutional responsibility, appropriate risk assessments, independent scrutiny where necessary and meaningful opportunities for affected citizens to challenge consequential decisions.
The objective should not be to reject technological progress, but to ensure that technology strengthens constitutional governance rather than weakening accountability.
Who Is Responsible When a Machine Causes Harm?
Responsibility may be distributed among several actors, depending on the circumstances. Developers may be responsible for negligent design; organisations may be responsible for unsafe deployment; operators may be responsible for misuse; and institutions may be responsible for failing to provide proper supervision.
However, responsibility should not become so widely distributed that nobody can be held accountable.
A sound system must establish clear duties before harm occurs. It should also provide mechanisms to investigate failures, correct decisions and compensate affected people where appropriate.
This requires three essential principles:
First, transparency: people should be able to understand the basis of consequential automated decisions.
Second, human oversight: important decisions affecting rights, safety and dignity should receive appropriate human review.
Third, accountability: every high-risk system should have clearly identified individuals or institutions responsible for its deployment and consequences.
The Way Forward: Human-Centred Automation
The future does not require a choice between human intelligence and machine intelligence. It requires a partnership in which machines improve human capabilities while humans retain responsibility for the decisions they authorise.
AI systems should undergo appropriate testing, monitoring and audits. High-risk applications should have stronger safeguards. Institutions must train employees to recognise technological limitations rather than follow automated recommendations blindly.
Education must also develop ethical reasoning alongside technical skills. Future professionals should learn not only how to build powerful systems, but also how to anticipate harm and take responsibility for their creations.
Ultimately, the objective should be responsible automation, not automated irresponsibility.
Conclusion
Machines can calculate faster than humans, process more information and perform increasingly complex tasks. Yet technological capability does not remove the need for moral judgment.
When a machine acts on our behalf, its action remains connected to human choices about design, purpose, supervision and use. Allowing responsibility to disappear behind technology would create a dangerous world in which decisions have consequences but nobody answers for them.
True progress requires institutions that use technology confidently while remaining accountable to the people they serve.
Machines may inherit our tasks, but they must never become an excuse for abandoning our responsibilities.
