Computer-implemented inventions (CII), artificial intelligence (AI), machine learning (ML) are all elements of modern creative endeavor. While many talk about these tools and the possibilities they represent for the future, those who work in intellectual property law know that they are playing important roles in the world now, speeding up the pace of technological advancements.
As we noted in a post last month, that reality represents a source of legal questions, the biggest of which may be, what are the implications for how to manage IP rights? Europe is taking the position that devices created through systems using AI or ML may be unpatentable because they are products of computer software. There might be wiggle room on that if the patent application includes a claim of some unique technical characteristic. Many wonder if the U.S. will follow suit.
Where is the U.S. on this?
Securing IP rights and protecting them is uniquely challenging in the digital context, and the stakes are high. For example, consider the story about the first-ever sale at Christie's in New York of a computer-generated painting. Experts expected it might sell for $10,000 at best. It went for more than $430,000.
Our purpose here is not to discuss the IP aspects of the painting. Rather, we use the story to highlight the economic implications. That AI-produced painting garnered someone a lot of money and some analysts predict that AI, in all its applications, could boost the U.S. economy by $14 trillion in the next 20 years. Obviously, how the intellectual property rights get administered is going to be important.
Right now, analysis suggests the U.S. Patent and Trademark Office is rejecting many more patent applications based on AI output than it is approving. And the decline happens to coincide with a federal court case in which an AI-based patent claim for electric grid management was denied.
What this means for the future is impossible to say, but indications are that considerations of AI-based patent applications will continue to face tough challenges through the review process. Success will require not only attention to detail, but planning that anticipates any possible reasons for application denials.