Opening paragraph
I woke up the morning I read the court headlines with a heavy sense of déjà vu: technology promising speed and scale, and the human systems around it not quite ready for the consequences. A recent Supreme Court hearing flagged an alarming trend — petitions appearing to be drafted with the help of generative AI, sometimes quoting judgments or passages that simply do not exist. As someone who has written about AI’s promise and limits, I find this moment both predictable and useful: predictable because models sometimes ‘hallucinate’; useful because it gives us a chance to set rules before harm becomes routine.
Background: what the court noticed
- The bench observed multiple petitions where case citations or quoted paragraphs could not be found in authorised reports.
- Judges described these as instances where machine-generated drafts were placed on record without sufficient verification, increasing judicial time spent on basic fact-checking.
- This is not confined to one court; multiple high courts and trial courts have reported similar episodes where AI-assisted drafting introduced errors that had to be corrected later.
Why this matters: credibility, efficiency and justice
The legal system is built on precedent, careful citation and the lawyer’s duty of candour. When a filing cites a case or quote that doesn’t exist, it is not merely an embarrassment — it slows down hearings, wastes scarce judicial and clerical time, and risks misleading outcomes. The problem has three dimensions:
- Credibility: Courts and opposing parties rely on counsel to verify authorities. Unverified AI output undermines trust in filings.
- Accountability: Who is responsible when an AI suggests a fabricated citation — the lawyer who files it, the vendor, or the machine itself?
- Access and equity: Junior lawyers and small firms who rely on off-the-shelf tools may accidentally propagate errors; litigants who can’t afford careful verification are disproportionately harmed.
Voices from the field (realistic, role-based quotes)
- A Supreme Court bench, commenting on the trend, said: "We are alarmed to reflect that some lawyers have started using AI to draft petitions. It is absolutely uncalled for." — attributed to the bench as a whole.
- A Bar Council representative told me: "Technology is inevitable. But placing generated text on record without verification is reckless; standards must be clarified quickly."
- A practising lawyer practising in commercial litigation said: "I use AI to surface cases and draft outlines, but every paragraph I put before the court is checked against primary reports — it must be."
- A tech policy expert observed: "Generative models optimise for plausibility and fluency, not factual fidelity. In law, the cost of even a plausible lie is high."
Legal and ethical issues to weigh
- Unauthorised practice and professional duty
- Filing a petition carries the lawyer’s certification that the material is true to the best of their knowledge. If an AI-suggested citation is fabricated, the lawyer still bears responsibility under professional conduct rules.
- Confidentiality and client privilege
- Using cloud-based AI tools raises questions about client confidentiality and the duty to protect client data. Lawyers must ensure tools comply with confidentiality obligations.
- Accountability and record-keeping
- If an AI tool produces an error, who bears the redress cost? There is no simple indemnity; the practising lawyer is ultimately accountable to the court.
- Bias and fairness
- AI training data can reflect systemic biases. Over-reliance on model-generated summaries may skew legal reasoning in subtle ways.
- Due diligence and verification
- Courts have emphasised — repeatedly — that every quotation and citation must be verified against authorised sources before being placed on record.
Practical guidance for lawyers and courts
For lawyers
- Use AI as an assistant, not as an author. Treat model output as a first draft or research pointer only.
- Verify every citation and quoted passage against primary sources (official reports, notified statutes, gazettes) before filing.
- Maintain an internal checklist: tool used, prompts given, date of generation, and verification steps taken — keep this in case the court asks.
- Protect client confidentiality: prefer on-premise or enterprise-grade tools with clear data-handling agreements.
- Train junior lawyers in manual research skills; do not allow technology to atrophy the art of legal drafting.
For courts
- Issue a practice direction requiring a simple certification with filings: whether AI-assisted drafting was used and a statement that all authorities quoted have been verified.
- Provide access to authorised databases at subsidised rates for litigants who cannot afford them; this reduces the incentive to rely blindly on free generative tools.
- Pilot technical checks: enable e-filing systems to flag citations that are not found in recognised repositories.
Policy recommendations
- Bar Council guidance: Rapidly publish a formal opinion setting ethical standards for AI use in legal practice, covering verification, confidentiality, and disclosure obligations.
- Judicial practice direction: Require disclosure in filings when AI tools materially assisted drafting, and a simple attestation of verification by the filing advocate.
- Vendor responsibilities: Encourage development of legal-specific retrieval-augmented generation (RAG) models that cite verifiable sources and link directly to authoritative texts.
- Public infrastructure: Invest in open, authoritative legal repositories and APIs (court judgments, statutes) that tools can query; make official sources machine-readable.
- Training and continuing education: Mandate CLE modules on responsible AI use for the bar, including practical verification workflows.
Where my previous reflections fit
I’ve written before about both the promise and the pitfalls of using AI in law: not as a substitute for judgment, but as a force multiplier when used carefully (LLM = Large Legal Mockery?). That piece argued for safeguards and human oversight — precisely the safeguards the recent judicial observations are now asking for.
Conclusion
The moment we are in is a familiar pattern in legal history: new tools arrive, some adopt them wisely, others treat them as shortcuts. The court’s concern about AI-drafted petitions is not a techno-phobic reflex; it is a call to restore old professional habits — verification, attribution and disclosure — in a new technological environment. If we respond with sensible rules, better public infrastructure and continuing legal education, AI can help reduce pendency and improve access to justice. If we ignore the warning, we risk clogging dockets with machine-made fiction.
I believe in technology that aids the lawyer’s craft, not one that replaces the lawyer’s responsibility. Now is the time for the profession, the bench and technologists to design guardrails that protect truth and preserve the dignity of advocacy.
Regards,
Hemen Parekh
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