Overview
In our previous post, we examined several questions that AI may raise in life sciences patent disputes. This post considers a complementary question: what may remain constant. Even as research tools evolve, many of the elements that have long shaped these cases are likely to remain central, though they may appear in new forms. Contemporaneous records are one example. Whether they take the form of a bound notebook, an electronic lab notebook, or a model log, records created during the research process may continue to aid in reconstructing how and when an invention came about. Witness credibility is another. Inventors and fact witnesses who can clearly describe their own contributions, including how they used AI tools, may be well positioned to help a court understand the research. Clear scientific explanation may matter even more than before because the tools involved can be harder to explain than traditional research methods.
The legal framework may also prove more adaptable than it first appears. Patent litigation has absorbed earlier technological shifts, such as the move from paper files to electronically stored information, largely by applying existing principles to new kinds of material. Familiar concepts such as relevance, proportionality, and the need for reliable expert testimony may provide a workable starting point for AI-related evidence as well, even if their application raises new practical questions. That does not mean AI will leave life sciences litigation unchanged. It does suggest that parties who keep the fundamentals in view may be better positioned to adapt as new questions emerge.
Takeaways: As AI becomes a more common part of research, it may be worth revisiting the fundamentals with new tools in mind:
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- Keep records contemporaneous and clear. Consider whether current practices capture research decisions as they happen, regardless of the format those records take.
- Help witnesses describe their own work. Inventors and other witnesses may benefit from being able to explain, in plain terms, how AI tools fit into their research and where their own judgment came in.
- Invest in clear explanation. When the science involves complex tools, clear and accessible explanations for judges and juries may be as important as ever.
- Start from familiar principles. Existing rules and frameworks may offer a useful starting point for new types of evidence, even as their application continues to develop.
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