How to Patent AI Technology

AI technology like other similar computer-implemented technology can benefit from strong patent protection to protect the investment made in developing valuable products and services.  However, to avoid getting into difficulties with the various exclusions to patentability set out in the patent laws, it is important to focus on those aspects of the technology that are more suitable for patent protection.

Different countries have slightly different approaches to what is acceptable as a patentable invention and what is to be excluded.  As a general rule, patents should be directed to the technical aspects of the system, e.g. hardware, data processing steps, rather than the user aspects, e.g. display interfaces, user functionality etc.

Focussing on the apparent user benefits of a system in which an AI invention is implemented, can often give the impression of a less technical invention than is actually the case.  In order to maximise the likelihood of getting a good quality patent granted, it is important to bear the following general points in mind when considering what to try to protect.

  • Identify the core technical features of the system rather than the user interfaces (unless the interface is itself a technical improvement). Whilst a good user interface can help to maximise the commercial value and utility of an AI system, this can often fall foul of one the exclusions from patentability, such as the presentation of information.
  • AI systems may include complex algorithms based on multiple inputs possibly derived using machine learning. These can be difficult to define simply and so it may be necessary to try to identify their operation in a more functional language or try to break their function into smaller more definable portions.
  • Where the real effort has been in producing the model used to control a system, then it may be practical to protect the methodology used to derive the model rather than its use in a target system. This could be useful in preventing a competitor using the same technique to derive the same results.

Inventions relating exclusively to mental acts are difficult to patent, meaning it is important where an AI system replicates human action or activity, to focus on the technical elements that allow the invention to be implemented.  For example in a system using cameras and microphones for determining when it is safe to cross a road, steps human-like “looking for approaching cars”, “listening for the sound of vehicles” should be avoided but instead more technical steps like the process of analysing camera or microphone data as a technical process are more likely to be successful in a patent application.

AI in our lives

Often defined as the ability of a machine to imitate intelligent human behaviour, ‘Artificial Intelligence’ (AI) is a term which covers a multitude of different technological fields.  As many will have seen, technology companies such as Microsoft and Google have been increasingly advertising the use of AI in their products over the last few years. (more…)

Can Artificial Intelligence improve the way we do business?

Artificial Intelligence (AI) is a rapidly expanding area of technology, making its way into everyday life in application fields ranging from entertainment to agriculture. The World Intellectual Property Office (WIPO) has identified AI as one of the biggest technology trends for 2019, with patent applications relating to AI growing rapidly over the past five years.

A recent event “Tech in Legal: The Future of Law” hosted by Barclays Eaglelabs invited a number of start-ups to demonstrate how technology, such as AI, can be utilised in the field of Law.

Keynote speakers from DWF Ventures and Clifford Chance highlighted the opportunity of technology in law before the entrepreneurs had an opportunity to demonstrate their companies abilities.

Innovators included Luminance, who utilise ML to recognise patterns in text, learning from a lawyer’s interaction to reliably review legal documents. One example for the use of such technology would be for analysing a Non Disclosure Agreement to determine if there are any irregularities.

Legatics automates administrative legal work by auto filling documents through pattern recognition.

Avvoka provides a subscription based service which automates contract generation, assisting with document drafting, approval and analysis.

The concluding start-up, Genie AI utilises Deep Learning, a branch of ML, to analyse documents and recommend legal language and enforce best practice. In a demonstration, a question was asked of a legal document, for example “Am I covered for…”, to which the software would provide an answer based on its acquired knowledge.

These start-ups showcase a small example of what is possible using AI in law. Already implemented in countries across the globe, companies are seeing improved efficiency and client services by implementing software from this growing technology field.

Will AI software eventually be commonplace in business?

With increased investment, research & development and number of new start-ups, it certainly isn’t showing any signs of slowing. A number of companies already apply AI driven document analysis programmes (such as Kira Systems), it seems inevitable that more and more will adopt the use of AI in other areas of business.

By James Bishop