The legal profession is changing—and not slowly. With generative AI models like ChatGPT-4 becoming increasingly capable, it’s no longer a matter of if they’ll assist legal professionals, but how. So I decided to put ChatGPT-4 through its paces with one of the more demanding legal documents in my field: the Data Transfer Agreement (DTA) for health research.
DTAs are not your everyday consumer contracts. They deal with sensitive personal data, cross-border data flows, and legal compliance in an increasingly regulated landscape. They are intricate, specialist documents, and they’re rarely found in the public domain—meaning they likely weren’t heavily represented in the data ChatGPT-4 was trained on. In short, if generative AI can draft a decent DTA, that would be something worth paying attention to.
So I ran an experiment. First, I used ChatGPT-4 to generate an outline of a typical DTA. Then, I fed it each clause heading and asked for a detailed version of each clause. The result? A 6,800-word draft DTA—coherent, reasonably structured, and almost impressive.
But not perfect.
In my article just published in Humanities and Social Sciences Communications, I dig into where ChatGPT-4 excels and where it still falls short. Yes, it can generate most of the expected clauses. But its grasp of legal precision, clarity, and especially data protection compliance still leaves room for improvement. There are issues with redundancy, inconsistent use of terms, and ambiguous concepts like “derivative works.” And although it mentions security and compliance, it doesn’t always go deep enough to meet best-practice standards.
The takeaway? ChatGPT-4 is not ready to replace lawyers. But it is already a powerful tool in the legal drafting toolbox—especially when used strategically. My two-stage approach (first outlining, then refining clause-by-clause) is a method I believe many legal professionals can adopt to streamline their work while maintaining full control and accountability.
Most importantly, this experiment raised a set of broader questions—ethical ones. Should clients be told when AI was involved in drafting? Who is ultimately responsible for errors? And how do we ensure fairness in a world where algorithmic bias can quietly shape outcomes?
The answers aren’t simple. But one thing is clear: the future of legal drafting will be a collaboration between human lawyers and artificial intelligence. This study is a small, practical step in figuring out what that collaboration should look like.
If you’re curious to see what ChatGPT-4 produced—or if you’re a legal professional wondering how to make the most of AI without compromising on quality—you’ll find the full article here:
Donrich Thaldar 