“Technology is a useful servant but a dangerous master.” – Christian Lous Lange
Digital technology provides vast data infrastructure for modern governance, yet its reliability as an input for objective, rational decision-making remains highly controversial.
Digital Technology as a Reliable Source of Input for Rational Decision-Making
Real-Time Policy Inputs: Eg: CoWIN platform enabled real-time vaccine inventory planning across all Indian districts.
Citizen Participation in Policy- Eg- MyGov collected over 10 crore citizen suggestions that shaped the National Education Policy 2020.
Digitizing demographic and macro-surveys significantly eliminates human enumeration mistakes and calculation errors.
Satellite tracking and geospatial maps provide precise objective inputs for infrastructure projects. Eg: PM GatiShakti National Master Plan GIS data.
Leakage Elimination-
Interlinked digital architectures unify isolated departmental databases into a singular, holistic policy-making dashboard. Helps eliminate duplication.
Predictive Weather Planning: Eg: The IMD’s advanced Doppler radar systems supplying precise cyclone trajectory inputs to save coastal communities.
Counter-Argument: The Flaws and Risks of Digital Inputs
Poor data collection practices hampers objective policy making and implementation. Eg- Ghost Beneficiaries under Ayushman Bharat.
The “Black Box” Problem- AI logic is often opaque.
Institutionalizing Historical Bias- If data is biased , the AI will “learn” and automate that bias. Eg- US COMPAS tool biased against African-Americans.
Difficulty in ensuring accountability for mistakes.
Correlation vs Causation Fallacies: Analytical engines can link two completely unrelated data trends together, generating irrational choices.
Exclusion of the Digitally Illiterate from policy making & online grievance portals
Way Forward
Human-in-the-Loop (HITL)- The final “sign-off,” especially in cases affecting human rights, must be by a human officer.
Mandating regular 3rd-party audits of government algorithms to detect and “unlearn” biases.
The EU AI Act Approach- “Risk-Based Framework” where high-risk AI (policing or judiciary) face the highest level of ethical regulation.
Digital Ethics Commissions including ethicists, jurists, and technologists to oversee AI deployment in public service.
Ethical Coding Standards- Teaching “Ethics by Design” to programmers working on public infrastructure.
While digital technology streamlines administrative efficiency, it cannot replace human empathy, requiring a balanced model where data informs but conscience rules.