Training a commercial AI on a competitor's copyrighted material
Building a substitute for someone's product out of their own copyrighted work is not transformative. It is just competition with extra steps and a lawsuit.
Not legal advice. Sally roasts behaviour and use-cases in general, never your specific situation, and nothing here replaces a real lawyer. The cases are real; what you do about them is between you and someone licensed to tell you.
Using a rival's copyrighted database or content to train a model that competes with that same rival.
Thomson Reuters v. Ross Intelligence Inc.
D. Del., summary judgment Feb. 2025 (on appeal) · US (D. Delaware)
Ross trained a legal-research AI on material derived from Westlaw headnotes to build a competing product.
The first US federal ruling rejecting a fair-use defence for AI training, finding the use non-transformative and a market substitute. On appeal.
A court delivered the first US federal ruling rejecting a fair-use defence for AI training, where a company trained a legal-research tool on a competitor's copyrighted headnotes. The use was found non-transformative and a market substitute, which is roughly the worst combination of words you can hear in a fair-use analysis.
Fair use leans on whether your use transforms the original and whether it harms the market for it. Train on a competitor's material to build a rival product and you have answered both questions against yourself.
“You fed a rival's work to your model to beat the rival, then acted surprised that the word "substitute" appeared in the ruling.”
- 01Do not train on a competitor's protected content to build something that competes with them.
- 02License the data, or use sources you genuinely have the right to train on.
- 03Run a real fair-use analysis with a lawyer before assuming training is automatically permitted.
Not legal advice. General commentary on a use-case, not your situation. Talk to a real lawyer before you act.