AI-Powered Design and IP Laws

Grant Steyer, a patent attorney and a partner at the IP Law Firm Renner Otto, usually works with companies as well as individual inventors. He has been closely watching the emergence of IP-driven design tools. In this podcast episode, he addresses the legal implications of working with generative design tools.

Current AI tool usage fundamentally reflects how engineers have been working all along, Steyer points out. "It's just like what you would have done in the past - Googling, going on Reddit, talking to a colleague." The problem he often sees is patent application drafts with chunks of AI-generated gobbledygook.

"Reading through the writeup, I'd see parts that I can't figure out. So I'd go to the inventor to talk about it, and he'd say, 'Oh yeah, that one I wasn't quite sure, but ChatGPT was convincing, so I left it in there.' And it's something that basically breaks physics - it's not possible," he says. His suggestion is to use AI "like an assistant or intern who is giving you some good work, but doesn't have a lot of experience, so you know you shouldn't trust everything he or she gives you."

Can the AI be an Inventor?

On November 28, while most of us were still recovering from our indulgent Thanksgiving meal, the U.S. Patent Office issued new guidelines for AI-assisted inventions. It reads, "AI systems, including generative AI and other computational models, are instruments used by human inventors. They are analogous to laboratory equipment, computer software, research databases, or any other tool that assists in the inventive process ... " It emphasizes that a human or humans must "contribute in some significant manner to the conception." Citing the Federal Circuit, it states, "AI cannot be named as an inventor on a patent application (or issued patent) and that only natural persons can be inventors."

By that standard, "I can see that you'd have a problem if an invention has no human in the loop," Steyer says, but adds, "That's a really rare situation. Based on the current model of invention, I haven't come across something like that."

Accidental Patent Infringement 

Because of how machine learning works, there is, however, a risk that "you might accidentally infringe on someone else's patent without meaning to," Steyer notes. This has to do with the data set employed by the software developer to train the AI system - specifically, whether that data set includes patented and copyrighted designs.

At Autodesk University, the company's CEO Andrew Anagnost promoted Neural AI - a design tool that understands natural language input. As a safeguard against inadvertent design plagiarism, he says, "if something is generated by our model that looks like something in the training set, we throw that result away. That protects IP ..." (Read our Autodesk University 2025 here.)

Steyer points out, "There are designs that you are allowed to copy. For instance, they have been out for a long time. They're not protected by patents or copyrights. They're open source." He sees Autodesk's safeguard as "a good first step." He adds, "I'd feel much better if I see a training data set that's open source, or the developer has paid licensing fees for."

For more on legal implications and possible pitfalls with AI design, listen to the podcast with Steyer. 

You can reach Steyer at his IP law firm's homepage.