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June 29, 2026e-Paper
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June 29, 2026e-Paper
Updated – June 29, 2026 10:54 am IST
It is important for law schools to initiate conversations on how pedagogical practices can be improved with or without ethical AI, without displacing the time-tested approaches of reading, writing, analysing, and debating. | Photo: Special Arrangement
The decision of the High Court of Andhra Pradesh to set aside a May 2025 order by an Additional District Judge in Vijayawada set off a chain of events that could alter the course of the legal profession and education in India. The trial court’s reliance on fabricated, AI-generated citations and the resulting ire of a livid Supreme Court triggered a broader dialogue regarding artificial intelligence (AI) in the judiciary. This controversy culminated in the publication of the draft Regulations for Use of AI in Courts, 2026, earlier this month.
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The draft makes explicit what was implicitly expected by the legal community – that the substance of judicial decision-making must never be delegated to machines, and that the ‘rule of law’ shall remain the key to the administration of justice. Specifically, the rules institute a ban on algorithmic judicial decision-making (such as outcome prediction) and a blanket prohibition on using AI to predict bail eligibility. Furthermore, citing AI hallucinations is now strictly classified as professional misconduct and carries the risk of debarment. A disclosure requirement is mandated, forcing advocates to declare any use of AI.
At the same time, the regulations are decidedly not anti-AI but provide the necessary set of principles and pathways for the adoption of AI wherever permitted, a spirit captured by a presumption in favour of responsible AI adoption. In this adoption, the central pillar is human primacy – AI must assist judges and court officers. The onus of pre-empting discrimination, bias, and errors arising from AI rests solely with judges, just as that of ensuring factual accuracy rests with the advocates.
As these safeguards have implications for the readiness of graduates from our law schools, a pertinent question arising in the wake of these regulations would be: What does this mean for legal education in India?
Education is a field most directly and extensively impacted by the emergence of AI. Research has consistently revealed that AI offers an easy way out for students in the face of academic demands, a temptation that few can resist. This not only raises difficult questions about academic integrity, ethics, and fairness, but also about risks of ‘cognitive offloading’, dependence, and long-term impacts on skill development and employability. Conversation surrounding displacement at the entry-level positions now dominates the discourse.
These are genuine concerns. But addressing them may require a counterintuitive approach rather than the conventional approach. In India, several educational institutions have applied the plagiarism rules created by UGC under the UGC (Promotion of Academic Integrity and Prevention of Plagiarism in Higher Educational Institutions) Regulations, 2018 in a blanket fashion to AI generated content, without assessing whether use of AI is ethically identical to plagiarising from others’ work (around which the 2018 Regulations were drafted), or even if AI detection tools, whose results will determine the penalty, constitute reliable evidence of use of AI. This undermines principles of academic justice and creates a vicious cycle of mistrust in the academic ecosystem, where instructors view every work with suspicion and students go out of their way to avoid suspicion, even when that forces them to write in ways that are sub-par. Addressing these concerns does not require avoiding AI but engaging with it, albeit with a keen, critical sense of its use.
The legal industry is fast adopting AI. Add to this the ‘whitelist’ of AI uses espoused by the draft regulations, which include, among other things, research, analytics, and document generation, and it becomes clear that the mandate for law education is now to inculcate competence in AI use among students. Add further to this Rule 43 of the draft regulations, which provides that AI use by the parties must not only be disclosed but, if AI-generated material turns out to be fabricated or false, the party submitting it bears full responsibility for it.
This clearly means that the competence to be imparted must be twofold, including both the ability to use it effectively and the ability to avoid erroneous and unethical outputs (such as hallucinations, biased output, etc.) when using it. Inculcating these competencies will not be an easy ask. It may be necessary, but no longer sufficient, to add an ‘AI and law’ course to the curriculum.
Law students tread interesting ground, needing to understand the technology without delving into the technicalities. This is not merely because it can make them better technology lawyers, but also because it can help them work more effectively with technology and form the basis of both the above-mentioned competencies. This is the first order of business for law schools, and must be approached using the principle of ‘functional history’ of technology, rather than its technicality.
The nature of today’s AI is largely shaped by historical factors. It was the repeated failure of rule-based AI systems that prompted continued work on neural networks, but this also tells us that neural networks are ‘not’ rule-based, but probabilistic. And that neural networks were inspired by biological neurons, designed to imitate them but not explain themselves, gives us a glimpse into why they suffer from inherent opacity. Such functional history connects directly to the technology’s legally salient features and supports the complex legal analysis that accompanies it.
This foundational knowledge should then be supplemented by a second layer of skill-based education. This may be best integrated throughout the curriculum (if selectively) rather than as a stand-alone course. This layer enables the ethical and skilful use of AI for legal tasks permitted under Supreme Court regulations. More specifically, however, it calls for a paradigm shift in legal education, in which working with AI and its output is brought to the fore of the learning experience. First, students can learn how to get better outputs.
Second, this stops avoidable deception about the use of AI. If the institution actively develops a framework for working with AI, there is no need to hide its use, which is a significant problem in education globally. Lastly, it allows for ironing out the creases – determining what is ethical, what is not – what works, what does not – iteratively within this paradigm.
While many students may learn to use AI on their own, there are reasons why law schools are best advised to institutionalise its use. First, it creates greater parity among students, who may not all be equally equipped to learn technology on their own. Second, it reduces the scope for unethical use of AI. Third, it can sensitise students to the real pitfalls of using this technology, from errors to unhealthy dependence, and help them identify and deal with them more effectively.
A third layer can be AI as teaching, learning, or assessment tools. Some examples include: extracting metadata, summarising complex legal documents, and identifying defects in petitions before they are submitted. Given that many modern AI and Online Dispute Resolution (ODR) tools support audio and text transcription in various vernacular languages, legal aid clinics could leverage this functionality to optimise their operations and make their services accessible to the local community. AI can also serve as a powerful assistant in case law mapping, which has been a logistically complex and administratively laborious exercise.
But before we deploy these multiple layers of AI in legal education, we must address the elephant in the room, the bug in this code. There is a palpable realisation that traditional law classroom teaching in India has become pedagogically obsolete. AI has further exposed the complete failure of doctrinal recall – instead of a professional attribute which is built over time, memorisation and rote learning become core pedagogical devices and learning techniques in law schools. Instead, pedagogy must evolve with the technology.
To be fair, we cannot blame law schools entirely. It would be onerous for the forgotten majority of regional colleges and resource-constrained law schools to focus on pedagogical excellence and elevate benchmarks for high-quality learning when the unending struggle is with infrastructure and faculty shortages. Further, since most law schools are not housed in universities with strong engineering, technology, and computer science departments, they cannot develop AI tools tailored to their specific needs.
A glimmer of hope is the thriving AI startup ecosystem, where new AI tools are being specifically designed for teaching and learning law (the recent AI Impact Summit showcased some of the finest applications developed by indigenous AI companies). Law schools must look beyond basic plagiarism-detection software or general purpose large language models and seek out these new AI tools partnering with the emerging AI startups.
Judges of the higher judiciary are endorsing the ethical use of AI in legal proceedings. Major regulations covering AI in courtrooms are being discussed at the highest levels and by the public. Courts in other countries have imposed costs on litigants for submitting fabricated AI cases. Tribunals in India are recalling orders based on entirely hallucinated cases. Every other week, a law firm announces a partnership with an AI company. The need for clarity demanded by clients is pushing law firms to overhaul the ‘billable hour model’. All of this is happening right now, at a pace far faster than most lawyers and law students realise. It is important for law schools to initiate conversations on how pedagogical practices can be improved with or without ethical AI, without displacing the time-tested approaches of reading, writing, analysing, and debating.
(Ashish Bharadwaj is Pro Vice Chancellor, WPU Goa and Krishna Deo Chauhan is Associate Professor, JGLS. Views are personal.)
Published – June 29, 2026 08:00 am IST
education / court / Artificial Intelligence / law
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