Algorithmic Justice v. Constitutional Morality: Can AI Ever Satisfy Article 21?

This Blog is Written by Yashika Datta Wadke, 1st Year, BA LLB, Hindi Vidya Prachar Samiti's College of Law, Mumbai.

Introduction

The proliferation of Artificial Intelligence (AI) in administration and legal decision-making has fundamentally modified the justice delivery framework. From algorithmic policing to automated decision-making, automated methods ensure effectiveness, consistency, and fairness. However, these assertions must be scrutinized within the framework of the Indian Constitution, especially Article 21, which guarantees the right to life and autonomy. Judicial interpretation has notably broadened the scope of Article 21 to encompass not only procedural due process but also fundamental rights such as dignity, independence, and privacy. This development illustrates the core principle of constitutional ethos, which requires that all state action must comply with fundamental values of justice and dignity of the individual. Given these circumstances, a key question emerges: can automated decision-making, data-centric and free from human intervention, fulfil the regulatory requirements of Article 21?

Algorithmic Justice: Promise and Paradox

Algorithmic justice denotes the integration of AI systems into policy-formulation processes typically performed by human administrators. These mechanisms depend on data analysis, algorithmic modelling and big data collection to produce results or outcomes. In theory, they assure objectivity and efficiency by eradicating personal bias. However, this guarantee is fundamentally paradoxical. Automated processes are reliant on data-driven decision-making; they are formed by the data on which they are trained and the presumption embedded in their design. Where archival data represents systemic discrimination, computational results risk perpetuating and validating that discrimination. The international experience strengthens this concern. In the United States, computational risk evaluation tools such as COMPAS have been condemned for racial bias in sentencing forecasts. This illustrates that algorithmic decision-making can root inequality under the disguise of impartiality. Additionally, many AI mechanisms operate as “black boxes”, yielding results without clear reasoning. This weakens the core principle of justice as a rational and challengeable process.

Article 21: From Procedure to Substantive Justice

The development of Article 21 signifies a transition from legal formality to transformative constitutionalism. In A.K. Gopalan v. State of Madras, the Supreme Court embraced a restrictive interpretation concentrated on procedural formalism. This perspective was fundamentally modified in Maneka Gandhi v. Union of India, where the Court ruled that such procedure must be “just, fair, and reasonable”. This verdict introduced substantive due process into Indian constitutional law. Following judicial decisions has broadened this structure. In Francis Coralie Mullin v. Administrator, Union Territory of Delhi, the Court acknowledged the right to live with dignity. In Justice K.S. Puttaswamy v. Union of India, the Court upheld privacy as fundamental to life and autonomy. Thus, Article 21 now incorporates an integrated standard including dignity, impartiality, autonomy, and a shield from arbitrariness, benchmarks that any algorithmic system must meet.

Constitutional Morality vs Algorithmic Rationality

Constitutional morality functions as a value framework, demanding that the actions of the state align with primary constitutional principles. It is intrinsically interpretive, context-aware, and centred on human dignity. Automated systems, on the other hand, function on instrumental rationality. They maximize results based on pre-determined variables and data correlations, without engaging in moral judgement. This discrepancy results in a systemic tension. Constitutional review requires balancing competing rights, contextual interpretation, and acknowledging individual dignity; irreducible functions to algorithmic logic. Philosophically, this exhibits the difference between systematic decision-making and principle-based adjudication. While algorithms can enforce regulations efficiently, they cannot operationalize moral reasoning that judicial interpretation demands.

Opacity and the Crisis of Procedural Fairness

Procedural fairness under Article 21 entails transparency, justified decisions, and the opportunity to question state action. However, algorithmic mechanisms often lack interpretability. This obscurity generates a serious deficiency in constitutional safeguards. If individuals fail to comprehend how a ruling influencing their rights was made, their capability to question it becomes superficial. This explicitly weakens the principle enshrined in Maneka Gandhi, that procedure must be fair and rational. Similarly, issues about computational obscurity have also been raised in authorities governed under the European Union’s regulatory structure. The proposed EU Artificial Intelligence Act highlights transparency and liability in high-risk AI mechanisms, acknowledging that opaque decision-making is contrary to rights-based governance. In the absence of identical mandatory regulations in India, the application of obscure AI mechanisms risks breaching due process of law.

Bias, Discrimination and Arbitrariness

Automated bias emerges when AI systems reproduce patterns of discrimination present in archival data. This is especially problematic in societies defined by systemic inequalities. The Indian constitutional structure addresses arbitrariness as contradictory to equal protection. In E.P. Royappa v. State of Tamil Nadu, the Supreme Court ruled that arbitrariness is the absolute negation of equality. When computational systems generate biased or inaccurate results, they fail to comply with both:

• The equality assured under Article 14.
• The principle of fairness under Article 21.

The COMPAS dispute in the United States further demonstrates how automated systems can unduly impact vulnerable communities. Such results emphasize the danger of integrating systemic inequality within supposedly unbiased technologies.

Privacy, Surveillance and Information Technology

AI-driven governance frequently depends on mass data collection, giving rise to privacy issues. Systems such as facial recognition and biometric identification expand the monitoring capabilities of the state. In Justice K.S. Puttaswamy v. Union of India, the Supreme Court acknowledged privacy as a fundamental right and instituted the criteria of legality, necessity and fairness. AI-powered monitoring mechanisms often function without adequate regulatory safeguards, giving rise to issues about:

• Mass surveillance
• Profiling and tracking
• Undermining of informational autonomy

These methods compromise the constitutional assurance of dignity and personal liberty under Article 21.

Regulatory Vacuum and Accountability Deficit

India presently is devoid of a thorough legal framework that specifically regulates AI. While policy programs such as NITI Aayog’s AI strategy grant fundamental principles, they remain unenforceable. Current legal frameworks, comprising the Information Technology structure and data privacy laws, insufficiently engage with challenges such as:

• Computational accountability
• Liability for algorithmic decisions
• Obligatory transparency standards

This legislative vacuum creates unpredictability regarding duty for rights infringements. Lacking accountability, individuals influenced by computational decisions are denied adequate remedies. Legal scholarship has highlighted that accountability is fundamental to the rule of law. In its absence, the implementation of AI in governance risks weakening constitutional safeguards.

Human Dignity and the Limits of Automation

Human dignity constitutes the foundation of Article 21. It entails acknowledgement of individuals as independent actors capable of choice and worthy of respect. Computational mechanisms, however, map humans to data points and prediction-based categories. They are incapable of considering personal accounts, circumstantial factors or moral dimensions. As acknowledged in Francis Coralie Mullin, the right to life comprises the right to live with dignity. This is unsatisfied by automated decision-making processes that deal with individuals as quantitative abstractions. Thus, the transfer of decisions affecting fundamental rights to AI risks undermining the human-centric principle of constitutional law.

Can AI be Constitutionally Aligned?

Notwithstanding these obstacles, partial alignment between AI and constitutional principles is achievable through stringent controls. Key measures include:

• Interpretable AI to ensure transparency.
• Human intervention in all decisions influencing fundamental rights.
• Automated audits to identify and address bias.
• Compliance with data protection laws consistent with standards laid down in Puttaswamy.
• Comprehensive AI regulatory framework mitigating accountability and liability.

These systems can decrease risks and enhance validity. However, they are unable to fully replace the interpretative and ethical functions carried out by human authorities.

Conclusion

The relationship between computational justice and constitutional morality is marked by both potential and tension. While AI proposes efficiency and consistency, it questions the core values rooted in Article 21. Indian constitutional doctrine has developed to give precedence to dignity, impartiality, and autonomy as principles that cannot be entirely maintained by automated systems. The lack of transparency, accountability, and normative reasoning restricts the capacity of AI to independently maintain these values. Therefore, AI fails to, in its current state, satisfy the standards of Article 21 by itself. It may perform as a complementary tool within a constitutionally sound framework, but the final decision-making must remain grounded in human judgement informed by constitutional morality. In a democracy under constitutional governance, justice is not simply about results but about the impartiality, dignity, and reasoning that strengthen them. These remain fundamentally human commitments that mechanisms cannot substitute for.