Justice David Masuhara’s courtroom had likely seen a fair share of procedural missteps before, but few as quietly consequential as the incident buried in Zhang v. Chen. What began as a standard family law matter quickly veered into a cautionary tale for the digital legal age. In this 2024 ruling, the BC Supreme Court became the unlikely site of Canada’s first major judicial stand against the improper use of AI-generated evidence.
The problem wasn’t the use of artificial intelligence itself, but rather the failure to verify its output. A lawyer, pressed for time and seeking efficiency, turned to ChatGPT to generate legal arguments and citations. Among them were several fictitious precedents—plausible-sounding decisions that, upon scrutiny, simply didn’t exist. AI hallucinations, as developers call them. The court called them something else: abuse of process.
Key Details from the BC Supreme Court Ruling (Zhang v. Chen, 2024 BCSC 285)
| Key Issue | Details |
|---|---|
| Case Name | Zhang v. Chen (2024 BCSC 285) |
| Jurisdiction | British Columbia Supreme Court |
| Incident | Submission of AI-generated fictitious legal cases in a family law case |
| Responsible Party | Lawyer used ChatGPT for legal brief, failed to verify citations |
| Court Finding | No intent to deceive, but failure to verify constituted abuse of process |
| Consequence | Special costs ordered against the lawyer personally |
| Broader Implication | Precedent set for AI disclosure and lawyer accountability |
| Source Link |
Justice Masuhara, notably measured in tone, acknowledged that the lawyer had not intentionally misled the court. But intent was not the only issue. The fabricated case law had already consumed court time and created the risk of cascading procedural errors. The fact that it came from an AI tool made little difference in the eyes of responsibility. Lawyers, he ruled, are still the stewards of accuracy, no matter their digital aides.
That ruling set a precedent with rippling implications—not only for legal practitioners in British Columbia but for courtrooms across jurisdictions wrestling with the role of generative AI in legal practice. At the heart of the matter was a deceptively simple question: Who checks the checker?
The answer, in this case, was painfully clear. No one had. And that failure earned the lawyer a special costs penalty—one that had to be paid personally.
For legal professionals already dabbling with AI for research or drafting, this outcome may feel like a turning point. Until now, tools like ChatGPT have operated in a grey zone—convenient, fast, and frequently correct, but still prone to confabulations delivered with uncanny confidence. Lawyers, trained in the fine details of argumentation and citation, may find it strikingly tempting to trust a tool that mimics their cadence so well.
But as this case shows, the risk is not theoretical. The fictitious case law passed through filings, past opposing counsel, and into the judge’s hands before the error was flagged. That detail alone should spark considerable concern. It nearly worked.
I found that part particularly unsettling—the idea that even a seasoned courtroom could be momentarily misled by synthetic case law dressed up in legalese.
The ruling didn’t merely stop at punishment. Justice Masuhara also offered guidance. Lawyers using AI should disclose it. They should verify every AI-sourced authority as rigorously as if they’d researched it themselves. And they should never assume the machine is right just because it sounds authoritative. That clarity was, in itself, a form of protection—not only for the courts, but for those hoping to harness AI responsibly.
Outside the courtroom, the Law Society of British Columbia quickly launched a professional conduct investigation into the lawyer involved. That move, while procedural, signaled a larger cultural shift. AI is no longer an emerging novelty in legal spaces—it’s a force that must now be governed.
In response to the case, some law firms have already begun drafting internal policies for AI usage, mandating disclosures or restricting tools like ChatGPT to non-substantive tasks. Others are quietly testing large language models fine-tuned on Canadian legal corpora—hoping to retain the benefits without the risks.
Still, the warning from Zhang v. Chen is hard to ignore: legal hallucinations carry real-world costs. And unlike in science fiction, no one is immune from consequences just because a machine wrote the error.
There’s also the matter of public trust. Courts rely on a shared understanding that every submission has been vetted, scrutinized, and sourced with integrity. The introduction of synthetic, unverifiable content—even by accident—threatens that trust. And while the case was resolved without catastrophic damage, the next one might not be so forgiving.
A senior litigator I spoke to off the record likened it to a “fire alarm pulled before the fire started.” The metaphor felt apt. British Columbia’s judiciary caught the breach early. But the infrastructure—the ethics, the tech literacy, the regulatory response—is still catching up.
And so, this case becomes more than a footnote. It’s a hinge.
On one side, an era of unfettered AI enthusiasm, where tools like ChatGPT are used to speed up everything from memos to legal drafts. On the other, a reassertion of accountability. Not against the machine—but against the professional who chooses to trust it.
For now, Zhang v. Chen stands as Canada’s most definitive legal stance on AI hallucinations. But it likely won’t be the last. Judges, regulators, and even clients will begin asking sharper questions about how legal work is produced. Whether that scrutiny results in a better-integrated AI future—or a backlash that drives it underground—may depend on how quickly the profession adapts.
