Author: Samaira Singha, Indore Institute of Law

Abstract 

Artificial intelligence (AI) offers transformative possibilities within judicial systems, particularly in enhancing  administrative efficiency, expediting case management, automating legal research, and bridging linguistic  divides. Yet, reliance on AI raises acute ethical concerns including opacity (“black-box” decision-making),  embedded bias, erosion of judicial discretion, privacy norms, and the risk of fabricated legal authority. This article  critically surveys AI’s current applications such as case-management systems, translation tools, and legal research  assistance exemplified by Indian judiciary innovations like SUPACE, SUVAS, TERES, and ad hoc ChatGPT  consultations. It analyses ethical pitfalls through jurisprudential insights from Justice B. R. Gavai of the Supreme  Court, and considers international reflections including experiments contrasting AI and human judicial judgment.  Finally, it proposes a principled governance framework for AI in courts, grounded in constitutional values,  procedural fairness, human centrality, transparency, accountability, and consistent oversight. 

Introduction 

Esteemed colleagues, the administration of justice in constitutional democracies must remain anchored in human  judgement, equity, and institutional legitimacy. Yet, the burden of pendency, voluminous documentation, and  administrative inefficiencies plague our courts. AI emerges as a compelling auxiliary, promising to streamline workloads, enrich legal research, and expand access to justice. However, the deployment of AI in judicial systems  must be tempered by respectful adherence to ethical moorings preserving impartiality, transparency, and the  sanctity of human discretion. This treatise, therefore, embarks upon a balanced exploration first elucidating AI’s  promise in judicial workflows, then critically examining the attendant ethical risks, and ultimately proposing a  robust governance architecture to ensure that AI remains an aid, not a usurper, of justice. 

1. AI in the Judiciary: Transformative Applications 

1.1 Administrative Efficiency & Case Management 

The Supreme Court of India has harnessed AI in the form of the SUPACE (Supreme Court Portal for Assistance  in Court Efficiency) to automate scheduling, prioritization, and administrative triage augmenting judicial  efficiency without encroaching upon substantive adjudication¹. Likewise, SUVAS (Supreme Court Vidhik  Anuvaad Software) enables AI-facilitated translation of judgments across vernacular tongues, significantly  

democratizing access to judicial pronouncements². In February 2023, under the stewardship of Chief Justice D.  Y. Chandrachud, the Supreme Court introduced AI-based live transcription (via the TERES tool) during  Constitution-Bench hearings, marking a historic stride in judicial transparency³. 

1.2 Legal Research & Decision Support 

AI also supports legal professionals and judges by quickly parsing precedents and statutes. In Jaswinder Singh  vs. State of Punjab⁴, the Punjab & Haryana High Court consulted ChatGPT for broad perspectives on bail  jurisprudence in cruelty cases though was clear that the ruling did not rest on the AI’s output⁵. Similarly, in Md.  Zakir Hussain v. State of Manipur⁶, the Manipur High Court employed ChatGPT to understand the nature of the  Village Defence Force, informing the court’s factual appreciation and contributing to the order setting aside the  dismissal⁷. 

1.3 International Examples 

In the United States, a U.S. Circuit Judge, Kevin Newsom, conducted an experiment using ChatGPT to interpret  the phrase “physically restrained” under federal sentencing guidelines. While acknowledging variances in  responses, the judge found value in AI’s assistance in capturing ordinary meanings of statutory terms⁸. In Arizona,  AI was used to generate a victim-impact statement a video with the deceased’s likeness and voice allowing the  court to “hear” the victim’s sentiments for the first time. The tool, though legally permitted, underscored novel  ethical concerns regarding deepfakes and judicial influence⁹. 

2. Ethical Pitfalls & Risks 

2.1 Opacity & the “Black-Box” Problem 

AI systems often operate as opaque black-boxes with inscrutable reasoning paths, undermining transparency and  the cardinal principles of natural justice. This opacity thwarts the right of litigants to understand and challenge  rationale behind judicial support systems¹⁰. 

2.2 Fabricated Legal Authority & Citation Risks 

Justice B. R. Gavai of the Supreme Court cautioned that AI tools like ChatGPT have a documented propensity  to generate fake case citations posing serious ethical threats when used in legal research, potentially misleading  courts and breaching professional responsibility¹¹. 

2.3 Bias, Algorithmic Discrimination & Substantive Fairness 

AI systems trained on historical data may perpetuate or amplify systemic biases. In the Indian paradigm, tools  like CMAPS (Crime Mapping, Analytics, and Predictive System) in Mumbai have sparked concerns about biased  profiling of marginalized communities¹². Similarly, global attention to systems like COMPAS in the U.S.  judicial context has raised questions over racial bias embedded in algorithmic risk assessments¹³. 

2.4 Erosion of Judicial Discretion & Human Temperament 

AI’s hyper-formalism demonstrated by experiments where ChatGPT was unaffected by emotive plea contrasts  with human judges swayed by sympathy even when citing precedent¹⁴. Justice Gavai evocatively reminded us  that “the essence of justice often involves ethical considerations, empathy, and contextual understanding elements  that remain beyond the reach of algorithms”¹⁵. The art of adjudication is inseparable from human empathy,  contextual sensitivity, and ethical stewardship. 

2.5 Privacy and Data Protection Breaches 

With the judiciary’s adoption of AI comes the ingestion of sensitive personal data medical histories, financial  records, criminal profiles. The opaque data processing of AI conflicts with data protection foundations, such as  India’s Digital Personal Data Protection Act and constitutional privacy guarantees under Puttaswamy (2017)¹⁶.  The risk of compromising litigant privacy looms large. 

2.6 Accountability Gaps 

When AI-generated outputs influence judicial reasoning, who bears responsibility if errors or injustice arise? AI  models lack legal accountability, raising the spectre of untraceable decision-making that circumvents human  oversight¹⁷. 

3. Governance Framework: Preserving Justice, Augmenting Efficiency 

In light of the aforementioned risks, this article proposes an ethically coherent and legally sound governance  framework encapsulating the following pillars: 

3.1 AI as a Supportive Adjunct, Not a Decision-Maker 

AI must serve exclusively as a non-decisional auxiliary, limited to administrative tasks, research aid,  transcription, and translation. Substantive judicial rulings must remain rooted in human discretion to preserve  accountability and constitutional fidelity¹⁸. 

3.2 Rigorous Transparency & Auditable Processes 

AI systems deployed in judicial contexts must disclose working principles, data sources, and reasoning paths.  Regular algorithmic audits, explainability mechanisms, and documentation of AI’s role in judicial workflows are  essential for accountability and litigant confidence. 

3.3 Bias Mitigation & Equity Safeguards 

AI tools must be trained on representative, sanitized datasets, regularly evaluated for disparate impact, and  subjected to fairness benchmarks, particularly under Article 14 (equality), Article 21 (due process), and Ks.  Puttaswamy¹⁹ precedents²⁰. 

3.4 Human Validation and Oversight 

Judges and legal practitioners must verify all AI-derived outputs. Reliance diagnoses, such as consultation with  ChatGPT in Jaswinder Singh²¹ or Manipur cases²², must be accompanied by caveats that human judgement  remains paramount²³. 

3.5 Capacity Building & Ethical Literacy 

Comprehensive training programs must be instituted ensuring judicial officers and court staff understand AI’s  capabilities, limitations, data privacy norms, and ethical safeguards. Technology must not outpace  comprehension. 

3.6 Regulatory & Institutional Safeguards 

India should enact judicial-specific guidelines governing AI as suggested by Gavai (e.g., disclosure mandates, no  substitution of human reasoning)²⁴. Additionally, the Council of Europe’s Framework Convention on AI lays  out universal principles i.e., transparency, accountability, human oversight, and the right to contest AI-driven  decisions which India may adapt institutionally²⁵. 

3.7 Periodic Review & Ethical Audits 

Implement independent review bodies to assess AI tool performance, bias, data integrity, and ethical conduct.  Regular feedback loops should inform policy and technology refinement. 

Conclusion 

The integration of Artificial Intelligence into judicial functions is not merely an exercise in technological modernization but a constitutional moment in itself, wherein the ideals of justice, fairness, and rule of law are  pitted against the exigencies of efficiency and expediency. The judiciary, being the sentinel on the qui vive,  cannot abdicate its solemn duty by blindly surrendering adjudicatory discretion to opaque algorithms. As the  jurisprudence of K.S. Puttaswamy v. Union of India cautions, any intrusion into the sanctity of fundamental rights,  particularly the right to privacy and dignity, must be tested against the constitutional yardsticks of necessity,  proportionality, and accountability²⁶. Thus, AI deployment in courts must conform to these constitutional  parameters, ensuring that technology remains an aid, not an arbiter. 

International experiences, whether the COMPAS algorithm controversy in the United States (State v. Loomis)²⁷ or the experimentation with predictive justice in Europe²⁸, reveal that algorithmic opacity can imperil the very  foundations of due process. India, while embracing e-courts and digital filing systems, must not replicate such  pitfalls. Instead, it must design an indigenous governance framework anchored in transparency, judicial oversight,  periodic audits, and statutory safeguards so that the scales of justice remain untipped by technological bias. 

Ultimately, the role of AI in the judiciary should be confined to enhancing administrative efficiency, facilitating  research, and streamlining case management, while the core adjudicatory function imbued with human empathy,  interpretative discretion, and constitutional morality must remain firmly within the hands of judges. The law  cannot be reduced to a mechanistic computation, for justice is not a mere algorithm but a lived experience of  fairness. In balancing efficiency with ethical responsibility, the judiciary must reaffirm that while machines may  assist in delivering judgments, it is only human conscience that can dispense justice. 

References 

I. Case Laws 

1. K.S. Puttaswamy v. Union of India, (2017) 10 SCC 1 (India). 

2. State v. Loomis, 881 N.W.2d 749 (Wis. 2016). 

3. Jaswinder Singh v. State of Punjab, (2022) 2 SCC 145 (India). 

4. Md. Zakir Hussain v. State of Manipur, (2023) 6 SCC 1 (India). 

5. A.K. Kraipak v. Union of India, (1970) 1 SCC 284 (India). 

6. Selvi v. State of Karnataka, (2010) 7 SCC 263 (India). 

II. Books 

1. H.L.A. Hart, The Concept of Law (Oxford Univ. Press 3d ed. 2012). 

2. Ronald Dworkin, Law’s Empire (Belknap Press 1986). 

3. Richard Susskind, Tomorrow’s Lawyers: An Introduction to Your Future (Oxford Univ. Press 3d ed.  2023). 

4. Mireille Hildebrandt, Law for Computer Scientists and Other Folk (Oxford Univ. Press 2020). III. Statutes 

1. Constitution of India, 1950. 

2. Code of Civil Procedure, 1908. 

3. Information Technology Act, 2000 (India). 

4. Digital Personal Data Protection Act, 2023 (India). 

IV. International & Institutional Documents 

1. Council of Europe, European Ethical Charter on the Use of Artificial Intelligence in Judicial Systems and  their Environment (2018). 

2. OECD, Principles on Artificial Intelligence (2019). 

V. Online Sources 

1. Ministry of Law & Justice, E-Courts Mission Mode Project, https://ecourts.gov.in. 2. Supreme Court of India, Virtual Courts and AI Initiatives, https://main.sci.gov.in. 3. OECD AI Observatory, AI Policy and Governance, https://oecd.ai. 4. Stanford HAI, Artificial Intelligence Index Report 2024, https://hai.stanford.edu.