Artificial Intelligence (AI) is increasingly being used in governance and administration for tasks such as predictive policing, welfare delivery, tax compliance, and healthcare monitoring. However, whether AI can be considered a dependable source of input for administrative rational decision-making raises serious ethical concerns.

Ethical Merits of AI in Administrative Decision-Making

• Objectivity and Rationality: AI can help in objective and rational decision-making by minimizing human biases, emotions, and arbitrary discretion.

  • Example: Use of AI in e-Courts Project in India for objective crime management.

• Efficiency and Speed: Automated processing of data allows timely administrative decisions, enhancing responsiveness to citizens' needs.

  • Example AI-powered chatbots on government portals like UMANG reducing wait time and enhancing accessibility.

• Consistency: AI ensures uniformity in decision-making, which aligns with the ethical principle of equality before law.

  • Example: Uttar Pradesh has deployed an AI-enabled video analytics platform called "Jarvis" in 70 prisons to monitor inmates and flag potential threats in real-time.

• Accuracy & Precision: AI minimizes manual errors, enhancing accuracy in areas such as beneficiary identification, Targeted service delivery.

• Cost-Effectiveness: Automating routine and repetitive tasks reduces administrative costs in the long term.

  • Example: Chatbots handling citizen queries, reducing need for human customer support.

• Predictive Capabilities: AI can forecast trends and detect risks early, enabling proactive measures.

  • Example: Mission Mausam of IMD to incorporate AI-powered model in weather forecasting for effective disaster management.

Ethical Concerns with AI Dependence

• Lack of Accountability: Accountability is central to public administration. AI decisions can often be opaque (the "black-box" problem), making it difficult to assign responsibility when decisions lead to adverse consequences.

  • Ethical Dilemma: If an AI system wrongly denies welfare benefits, who should be held accountable—the programmer, the administrator, or the system itself?

• Embedded Biases: AI systems may reflect systemic biases present in their training data. This may lead to discrimination against marginalized groups, violating the principles of justice and fairness.

  • Example: the COMPAS recidivism algorithm in the US disproportionately targeted black defendent.

• Absence of Human Sensitivity: Administrative decisions often require empathy, compassion, and moral reasoning — traits AI cannot emulate.

  • Example: AI's reliance on proof for targeted PDS may exclude intended beneficiaries lacking adequate documents.

• Infringement on Autonomy: Citizens may be subjected to opaque decisions by AI without consent or appeal, undermining democratic and ethical legitimacy.

• Human Dignity & Autonomy: Over-reliance on AI may lead to dehumanization of administrative processes, where citizens are reduced to data points, undermining their dignity and autonomy.

• Privacy Concerns: AI relies on extensive data collection, raising concerns regarding privacy and potential misuse of personal information, conflicting with ethical principles of confidentiality and trust.

Need for a Balanced Ethical Approach

AI should be treated as an aid, not a substitute for human judgment. A hybrid model where AI provides rational inputs and civil servants apply ethical reasoning ensures both efficiency and moral responsibility. The ethical value of prudence demands cautious integration of technology in public service.

AI in governance is not inherently unethical, but its use must be guided by ethical safeguards, transparency norms, and human oversight. In a democracy, rationality must walk hand-in-hand with empathy.