Authored By: Utkarsh Sharma
Symbiosis Law School Noida
Introduction
Imagine walking into a courtroom where the judge isn’t wearing a robe, where the accused is anxiously standing beside his lawyer. and the victim’s family waits for justice and a voice emerges from a lean and thin screen, “Verdict generated, Probability of guilt: 97% Sentence: “Rs.10 lakhs of compensation”. No questions asked, no witnesses examined, no hesitation in the judgement and the question arises “Can we convert justice into a mathematical question or does it require judicial discretion through human interaction?”. This question gains critical importance in context of Section 138 of the Negotiable Instrument Act, 1881 concerned with dishonoured cheques. This statute was introduced to safeguard the integrity of cheques to ensure credible commercial transactions between parties by imposing criminal liability on people whose cheques were dishonoured due to insufficient funds or analogous reasons. But as time has gone by, the provision which was meant to assist in enhancing the judicial process has ultimately resulted in accumulation of cases.
It is mainly because these cases are very structured and document driven and many believe that an AI can resolve and adjudicate them with commendable efficiency. Such a system can go through large statutory provisions, dispose of unnecessary data and examine a pile of judicial precedents in a jiffy as compared to a human judge. This certainly raises a question that whether an algorithm can function more precisely as compared to an individual.
Yet outer looks don’t always reflect reality, disputes that at first glance may look straightforward on paper can often be a mix of complexities like financial distress, business expectations or even allegations of fraud or deceits. And such matters may require critical judicial assessment of fairness, credibility, intention and broader understanding of the situation. These matters cannot always be easily interpreted and answered through data analysis by machine algorithms.
The discussion is not merely limited to whether AI will replace judges in the coming years, rather it’s also about if our society is ready and prepared to vest the decision-making authority in the hands of a machine which is devoid of important human aspects like morality, sympathy and weight of responsibility of the future of a human being.
Limits of AI in Judicial Proceedings
There is no doubt that Artificial Intelligence is changing the legal system. It can quickly organize documents, summarize case files, identify legal precedents, and help judges with legal research.
However, assisting judges is a very different aspect from replacing them. A cheque bounce case under Section 138 of the Negotiable Instruments Act, 1881 may seem simple, but every case has its own facts and circumstances. A judge has to look at the intentions of the parties, the credibility of witnesses, settlement efforts, and procedural fairness. These matters require human judgment, reasoning, and discretion, which an artificial intelligence generally lacks.
Secondly, justice isn’t just about applying the law; it’s also about understanding people. Sometimes a cheque bounces due to fraud, financial trouble, banking errors, or genuine misunderstandings. A human judge can consider these factors with empathy and fairness. AI only relies on data and algorithms—it does not grasp emotions, morality, or social realities. Another major concern is bias and accountability.
AI systems are trained on historical data. If that data includes errors or biases, AI may make unfair decisions. Moreover, if an AI makes a wrong judgment, who is responsible? The software developer? The government? The court? This lack of accountability raises serious legal and ethical issues.
Additionally, as according to the legal maxim “Audi Alteram Partem”, the Constitution of India guarantees the right to fair hearing and also the principles of natural justice. Citizens expect their cases to be heard by an independent and impartial human judge who can listen, ask questions, and explain the reasons behind a decision. Public trust in the judiciary depends on human responsibility, not outcomes generated by machines.
AI as Means of Ensuring Efficiency and Consistency
Even though it’s true that cheque bounce cases involve a lot of legal complexities and discrepancies like the intention of the parties, enforceability of the cheque and some disputed facts which may be overlooked by an AI algorithm, but we cannot ignore its ability to go through and rectify the mistakes in large volume of cases with precise efficiency and consistency.
In India, there is currently a huge backlog of cheque bounce cases pending in courts. And while some of these cases may involve such legal complexities, it would be unrealistic to assume that each and every one of them have such requirements. There are many straightforward cases which can be easily handled by AI and can reduce delays, as compared to a human judge. It can assist the judges and allow them to focus more on complex cases while it deals with routine ones.
AI is available 24×7, and unlike humans, it can work continuously and efficiently without dropping a sweat. From organizing case files and answering legal queries to analysing concepts and conducting legal research without dropping a sweat with remarkable speed and preciseness. This again can help judges in delivering faster and accurate justice to people.
It can significantly reduce fraud and scam cases as it can easily detect forged signatures, inconsistency in documents, alteration in transactions in cheque bounce cases. With the help of its advanced software and data analysis algorithms, it can help eradicate this class of cases in the early stages and help in maintaining the credibility and integrity of judicial proceedings and commercial transactions.
AI is also cost efficient, and can highly reduce the costs of legal services, making it more affordable and accessible for people. It can automate routine tasks that are time taking and expensive such as drafting, documentation and case summaries.
India’s Approach Towards AI: Analysis of Judicial Precedents
India has gradually started embracing the use of AI in legal field. As we saw in the case of State of Maharashtra v. Dr. Praful B. Desai (2003), the court established that the recording of evidence through video conferencing is valid, this clearly shows that AI algorithms and legal principles can coexist.
Another case that promoted the use of technology in legal system was, Swapnil Tripathi v. Supreme Court of India (2018). In this case, the Supreme Court permitted live streaming of judicial proceedings in public, this shows the willingness of our constitution to emphasize transparency, access to justice and awareness with the help of technology.
But in the case of, Maneka Gandhi vs Union of India (1978), the Supreme Court established that Article 21 guarantees a “just, fair and reasonable procedure”, this supports the need for human intervention and fairness in decision-making. This reflects the never-ending need of judges in our constitution.
In the case, Loomis vs Wisconsin (2016), the court allowed the use of COMPAS AI risk-assessment tool for sentencing. And also held that AI can only assist judges and not replace them. This is an international case but it also demonstrates that how AI can be productively integrated in the system.
Conclusion
Artificial Intelligence will likely be a prominent feature in the Indian judicial system in the next two decades, especially in cheque bounce cases under Section 138 of the Negotiable Instruments Act, 1881. However, its future role should be understood as one of judicial assistance, rather than complete judicial replacement. AI is likely to be able to review large numbers of documents, identify relevant precedents, check for inconsistencies, ensure procedural requirements are met, help with settlement and reduce delays in routine cases. Those capabilities can greatly improve the efficiency, consistency, accessibility and speed of justice.
Furthermore, from a legal and ethical standpoint, the issues of algorithmic bias, transparency, privacy, accountability and the right to a fair hearing make the complete replacement of human judges difficult. If an AI system makes an incorrect or unfair decision, it is unclear who is responsible. Judicial power is constitutionally authorized and vested in public trust. It simply cannot be exercised by an opaque system without meaningful human oversight.
Moreover, it can be counterproductive to assert that AI Judges will always differ from Human judges in some respect. As we noted above, many technology futurists suggest it is likely that AI will not necessarily replace humans. Instead, technological advances are more likely to augment human intelligence. This suggests that judges could still be human, but “augmented,” that is, their intelligence and analytical functions enhanced by AI. These enhancement approaches raise issues about judicial appointment, workload and retention and broader questions about how judges contribute to society, as well as the importance of responsive judging and a need to better understand and explore the impact that people experience when a human judge deals with their concerns.
Therefore, the most realistic future is not “AI versus human judges,” but “AI-assisted human judges.” AI can be a very efficient judicial tool that reduces the burden of repetitive, document-heavy work, while human judges still have the final say in interpreting the law, evaluating evidences, exercising discretion and ensuring fairness.
As a result, even in twenty years’ time, AI may help courts to administer justice more quickly, consistently and efficiently, but human judges will still be needed to ensure justice, as it is not only computed, but also listened to, understood, reasoned and administered fairly.
References (OSCOLA)
Cases
- A K Kraipak v Union of India (1969) 2 SCC 262.
- Maneka Gandhi v Union of India (1978) 1 SCC 248.
- State of Maharashtra v Dr Praful B Desai (2003) 4 SCC 601.
- State v Loomis 881 NW 2d 749 (Wis 2016).
- Swapnil Tripathi v Supreme Court of India (2018) 10 SCC 639.
Legislations
- Constitution of India, art 21.
- Negotiable Instruments Act 1881, s 138.
Secondary Sources
Journal Articles
- Coglianese C and Lehr D, ‘Regulating by Robot: Administrative Decision Making in the Machine Learning Era’ (2017) 105 Georgetown Law Journal
- Edwards L and Veale M, ‘Slave to the Algorithm? Why a Right to an Explanation is Probably not the Remedy You are Looking For’ (2017) 16 Duke Law & Technology Review
Books
- Abbott R, The Reasonable Robot: Artificial Intelligence and the Law (Cambridge University Press 2020).
