Do We Need a Right Against Automated Justice? Making the Case for Human Oversight in the Age of Legal AI

The current intersection of judicial practice and emerging legal technologies presents a moment that calls for both openness to innovation and caution in implementation. The potential of AI to enhance judicial efficiency, reduce pendency, and expand access to legal resources is undeniable. It can relieve overburdened judges of repetitive tasks, empower litigants through legal help tools, and make the system more inclusive at least in theory.

Yet, amid this technological optimism lies a growing unease. The very attributes that make AI powerful its speed, consistency, and data-driven predictions also raise fundamental questions about fairness, transparency, and human discretion. When algorithms begin to influence, or worse, determine legal outcomes, we must pause and ask: Are we prepared for what we are delegating?

And more critically: Should we begin to articulate a constitutional safeguard, a right against fully automated justice?

Let me be clear, this is not a call to reject AI. In fact, AI when responsibly integrated, can play a transformative role in enhancing legal access, streamlining routine tasks, and assisting with drafting and data analysis. The key word, however, is assisting. When we begin to talk about replacing human reasoning with machine-generated outcomes in core judicial functions, the line between augmentation and abdication becomes dangerously blurred.

What Is “Automated Justice”?

Automated justice, in this context, refers to the use of artificial intelligence systems that produce or significantly influence legal outcomes with minimal or no human involvement. These systems may be designed to recommend decisions, predict likely outcomes, or even generate draft or final orders based on patterns in historical legal data. For example, an AI tool might predict the likelihood of bail being granted based on previous case characteristics, or calculate compensation in injury cases using predefined formulas tied to disability percentages and fixed multipliers without leaving space for judicial discretion or context-sensitive adjustments.

While such tools are often promoted as efficient and consistent, they raise serious concerns about fairness and accountability. When a system operates as a black box offering no meaningful explanation that a litigant can understand, question, or challenge, it risks subverting the fundamental principle of due process. Efficiency alone cannot justify decisions that lack transparency, reasoning, or the possibility of human oversight.

Law Is Not Math: The Need for Context, Nuance, and Discretion

Legal provisions do not operate in a vacuum; their application often depends on a range of contextual factors. A quantified impairment such as 45% permanent disability may result in very different compensation outcomes depending on the individual's occupation, earning capacity, age, and socio-economic background. Likewise, procedural elements such as a delay in filing an FIR may be interpreted as reasonable in one case and detrimental in another, based on the surrounding circumstances. These are not uniform data points. They reflect lived realities that require interpretive judgment, moral reasoning, and an understanding of human complexity. While AI systems may effectively identify recurring patterns or ensure consistency in certain procedural aspects, they are not equipped to capture the subtle, situational, and often emotionally charged dimensions of justice. They can provide structural assistance, but they cannot emulate the deliberative, human-centered reasoning that legal adjudication demands.

The Constitutional Foundations: Articles 14 and 21

The Indian Constitution provides a robust framework to safeguard individual rights, particularly through Article 14, which guarantees equality before the law and protection against arbitrary treatment, and Article 21, which encompasses the right to life and personal liberty. Judicial interpretations have expanded Article 21 to include the right to a fair, just, and reasonable procedure, forming a cornerstone of Indian due process jurisprudence.

Landmark decisions such as Maneka Gandhi v. Union of India 1978 SCC (1) 748 and Selvi v. State of Karnataka 2010 SCC (7) 263 have reinforced that state actions especially those affecting liberty or access to justice must adhere not just to procedural formality but to substantive fairness and transparency. These decisions emphasize that justice must be reasoned, explainable, and accessible to those affected.

In this context, the introduction of AI tools into adjudicatory processes raises significant constitutional questions. If decisions concerning liberty, property, or personal rights are produced through automated systems lacking transparency or avenues for meaningful challenge, the foundational principles of Articles 14 and 21 may be compromised. Justice that is generated by a machine, without the possibility of human explanation or discretion, risks becoming opaque and inaccessible.

Judicial reasoning is not merely a conclusion. It is a process that must be open to scrutiny, capable of being understood, and grounded in context. An AI model cannot be cross-examined. An algorithm cannot weigh moral nuance. These functions are essential to uphold the legitimacy of legal outcomes in a constitutional democracy.

The Illusion of Objectivity in AI

One of the most compelling yet potentially misleading promises of artificial intelligence is the claim of “objectivity.” AI systems are often portrayed as neutral tools that remove human bias from decision-making. However, in practice, these systems are only as reliable as the data on which they are trained. If the underlying datasets reflect historical or systemic biases based on caste, gender, class, or community, those same patterns may be reproduced, and even reinforced, by the algorithm under the appearance of impartiality.

Moreover, AI systems are not static. They require continuous updating, monitoring, and revalidation to remain contextually relevant and socially fair. Without regular audits and recalibration, there is a significant risk that outdated or skewed data will continue to shape legal outcomes long after the underlying social realities have changed.

International experience affirmed these concerns. In the United States, tools like COMPAS used for predicting recidivism and informing bail decisions have been shown to disproportionately flag individuals from marginalized communities, thereby exacerbating existing inequalities. In a country like India, where structural inequities are deeply embedded, the uncritical adoption of such systems could have even more severe consequences.

What AI Can Do: The Case for Assisted Justice

The integration of AI into legal systems need not be viewed as inherently problematic. Rather, it calls for the establishment of ethical, constitutional, and procedural guardrails to guide its development and deployment. AI should not be seen as a replacement for judicial discretion, but as a tool with the potential to responsibly augment judicial functioning.

In practice, AI systems such as large language models can offer meaningful assistance in structuring factual matrices, generating draft templates for legal documents, or outlining possible lines of legal reasoning. When designed with transparency, accountability, and human oversight in mind, such tools could help reduce delays, enhance consistency, and expand access to justice.

However, a clear distinction must be maintained: these technologies should function as assistive mechanisms, not as substitutes for human decision-making. The responsibility for interpreting the law, weighing evidence, and applying discretion must remain with the human adjudicator. Preserving this boundary is essential to maintaining the integrity and legitimacy of judicial outcomes.

Where We Must Draw the Line

While the benefits of AI in supporting legal workflows are evident, there remain certain domains within the justice system where automation must be approached with utmost caution or avoided altogether. When legal determinations impact fundamental rights such as personal liberty, bodily autonomy, family welfare, or the dignity of the individual, the legal process transcends procedural formalism and enters deeply human territory.

Cases involving anticipatory bail, parole, compensation for wrongful death or disability, child custody disputes, or findings of criminal guilt often involve trauma, vulnerability, and moral complexity. These are not merely technical exercises; they require sensitivity, contextual understanding, and the capacity to respond to human suffering in ways that no algorithm, however advanced, can replicate.

In such matters, a fully automated process risks reducing lived experiences to abstract inputs and legal questions to computational logic. AI may be capable of identifying correlations, but it cannot comprehend hesitation in a witness's voice, the emotional toll of a delay, or the unspoken significance of a silence. It cannot assess the credibility of pain or the layered realities behind a legal claim.

For these reasons, systems affecting core aspects of human dignity must be designed as human-in-the-loop where AI serves as a supportive input but never as the final arbiter. Retaining human oversight in these contexts is not just advisable; it is indispensable for upholding the constitutional promise of justice that is reasoned, empathetic, and fair.

The Case for a Right Against Automated Justice

In light of the growing use of AI in judicial contexts, there is a compelling need to consider the formulation of a constitutional safeguard, what may be termed a right against automated justice. Such a right would not seek to prohibit the integration of AI into judicial processes, but rather to establish non-negotiable parameters that uphold the integrity, fairness, and transparency of adjudication.

At its core, this safeguard would ensure that no legal decision particularly those affecting fundamental rights is made entirely by an automated system. Wherever AI tools are employed, whether to assist in drafting, analyze factual patterns, or offer preliminary assessments, all parties involved should be explicitly informed of such use. In addition, any AI-generated content must be subject to meaningful human review, capable of being scrutinized, explained, and overridden where necessary. Final responsibility for the outcome must always reside with the human decision-maker.

This is not merely a procedural requirement, it is a substantive protection of the principle that justice must be reasoned, contextual, and accountable. Far from hindering technological innovation, such a right would serve to align emerging tools with foundational constitutional values. It would prevent the gradual erosion of human oversight and ensure that the adoption of AI remains transparent, ethical, and constitutionally compliant.

International regulatory developments point in this direction. The European Union's AI Act, adopted in 2024, classifies AI applications in judicial contexts as “high-risk” (Annex III, Section 5c). The legislation requires that AI systems used to assist legal decision-making be subject to rigorous safeguards most notably, human oversight and final control. Article 14 of the Act mandates that a human must always retain responsibility for legal outcomes, thereby prohibiting fully automated judicial decisions.

As legal systems around the world confront similar challenges, there is a timely opportunity for jurisdictions with a strong constitutional foundation such as India to take the lead in articulating rights-based frameworks that preserve both technological advancement and democratic accountability.

A Human Future with Machines

The trajectory of legal technology points toward increasing integration of AI into judicial systems. This evolution brings with it significant opportunities for efficiency, consistency, and expanded access to legal resources. Intelligent drafting assistants, automated triage tools for undertrial cases, and AI-based legal help desks are just a few examples of how technology can support the justice delivery process.

However, as AI tools become more sophisticated, it is essential that their design and deployment are guided by a clear ethical and constitutional framework. Technological progress must not come at the cost of core judicial values such as transparency, accountability, empathy, and procedural fairness. Legal adjudication is not a transactional function. It is a deliberative process that must reflect both the letter of the law and the spirit of justice.

We must ensure that AI serves justice, not replaces it.

Let us remember: justice is not a product. It is a process. And that process must remain accountable, transparent, and ultimately human.

Justice cannot be downloaded. And liberty cannot be outsourced.

Maybe it's time we recognized a new constitutional safeguard: A right against automated justice.

The author is a judicial officer and a doctoral researcher in artificial intelligence and machine learning. Views are personal.