Machine learning (ML) and Artificial Intelligence (AI) have a long history – the industry was born in the 1950s.  Yet it is only in recent years that the technology has come to prominence, driven by on demand computer processing power and the vast increase in stored data.  ML and AI patents grew at a 34 per cent compound annual growth rate between 2013 and 2017.  Yet it is the impact that ML and AI has on the ideation process that may have the most profound impact on the intellectual property industry.

The human touch

By law patent applications must currently identify one or more human inventors. In the past this has not been an issue as human input has always been central to innovation. Developments in AI and ML are casting doubt on whether this law will remain applicable in the future.

In the 1980s, Stephen Thaler began experimenting with software that modelled the neurological processes of the human brain. His invention – The Creativity Machine – formed new ideas and adapted to different scenarios without human intervention. The research led to the invention of the Oral-B Cross Action toothbrush, and while Thaler was listed as the inventor, The Creativity Machine was arguably the major player in the product’s creation.

Confusing technology

Identifying the owner of an innovation is critical to understanding who can exercise the rights to that IP. It demonstrates who to do business with to get access to an invention. With patent portfolios a key indicator of a company’s value, confusion around ownership could have a significant commercial impact.

Patent protection for an invention that has been created using AI or ML occurs in much the same way as any other technology related invention. However, there could be issues in patent law when AI or ML is used to help create a claimed invention.  For example, if an innovator tried to patent a product that had been created using AI or ML, would the original creator of the AI or ML have an argument to claim part ownership of the innovation?

The way forward

Given the increased use of deep-learning systems, there will be more patent applications using AI or ML. A lack of understanding about the patentability of software-based inventions and computational systems could be putting innovators off seeking protection. As the technology develops, patent law may have to adapt, allowing innovators to use AI and ML to innovate without concern over the origination of the idea.

AI and ML have created a step change in what is possible in a range of industries, enabling highly complex problems to be solved quickly through the application of computational power. In the IP industry AI and ML enable companies to quickly understand more about their IP portfolio.  The impact of the technologies could however be significant in terms of idea ownership.  How long will it be until a computer is cited as a creator of IP?