Patenting activity for AI and machine learning-based applications has steadily increased in the last few years. Since AI-based inventions can be categorised as abstract ideas, a solution-based approach should be kept in mind when drafting patent applications. Here are some tips.
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“Artificial Intelligence is a new digital frontier that will have a profound impact on the world, transforming the way we live and work” – Francis Gurry, WIPO director general
Technological advances in smart machines and computers are having a huge impact on the banking, business, communication, defence, education, internet, medical and transport sectors. They are becoming dependent on AI technology to collect and analyse historical data. Further, neural networks are being developed to use the processing power of computers to replicate the intelligence and learning capabilities of the human brain. Examples of these processes are self-driving vehicles, product recommendations on e-commerce websites and fraud detection.
Growing competition to develop AI has forced major jurisdictions to amend their patent laws – for example, it led India to provide statutory protection to software through the Copyright Act.
AI is the future
According to WIPO, machine learning is the most dominant feature of AI and is mentioned in more than 40% of all AI-related patents filed worldwide, with a very high growth rate of 28% between 2013 and 2016. Further, use of the term ‘neural network’ grew at a rate of 46% over the same period. The top three fields in which machine learning-related patent applications were filed were telecommunications (more than 51, 273), transport (50,861) and life and medical sciences fields (40,758). This shows that there is a future in AI and the protection of AI-based inventions is therefore of utmost importance to inventors and innovators around the globe.
‘Computer program per se’ versus protecting AI inventions
‘Computer program per se’ means a computer program without hardware implementation, which is considered to be a mathematical model, business method, presentation of information or a scheme. As AI falls into this category, it is therefore deemed unpatentable in all major jurisdictions. However, these inventions can be protected by linking the computer program to a hardware or computer network since it may include certain other things, which are ancillary to or developed through the program. Therefore, when drafting AI or machine learning-based inventions, it is worth showing real-world application rather than an abstract idea.
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For instance, a machine learning model may be deemed a mathematical model or abstract idea and is therefore unpatentable. However, the model embedded in a self-driving vehicle for automatic detection of a route can be considered to provide a technical enhancement to self-driving vehicles and thus meets the patentability criteria. Inventors around the globe are encouraged to link AI with practical applications and innovate AI-assisted technology.
Since AI-based inventions can be categorised as abstract ideas, a solution-based approach should be kept in mind when drafting patent applications. Here are some tips:
- Link the solution to a practical application.
- Include a system architecture, which illustrates that all hardware elements are connected via a network, which can provide additional support for any objection on unpatentability during prosecution stages. Inclusion of the system architecture proves the hardware and/or the computer network link, thus making it patentable.
- Draft a system claimshowing that limitations to hardware provide additional proof of the hardware limitations of the AI-based invention. The system claim may include a memory, an interface and a processor configured to implement an algorithm stored in the memory.[…]
read more -www.lexology.com
Patenting activity for AI and machine learning-based applications has steadily increased in the last few years. Since AI-based inventions can be categorised as abstract ideas, a solution-based approach should be kept in mind when drafting patent applications. Here are some tips.
copyright by www.lexology.com
Technological advances in smart machines and computers are having a huge impact on the banking, business, communication, defence, education, internet, medical and transport sectors. They are becoming dependent on AI technology to collect and analyse historical data. Further, neural networks are being developed to use the processing power of computers to replicate the intelligence and learning capabilities of the human brain. Examples of these processes are self-driving vehicles, product recommendations on e-commerce websites and fraud detection.
Growing competition to develop AI has forced major jurisdictions to amend their patent laws – for example, it led India to provide statutory protection to software through the Copyright Act.
AI is the future
According to WIPO, machine learning is the most dominant feature of AI and is mentioned in more than 40% of all AI-related patents filed worldwide, with a very high growth rate of 28% between 2013 and 2016. Further, use of the term ‘neural network’ grew at a rate of 46% over the same period. The top three fields in which machine learning-related patent applications were filed were telecommunications (more than 51, 273), transport (50,861) and life and medical sciences fields (40,758). This shows that there is a future in AI and the protection of AI-based inventions is therefore of utmost importance to inventors and innovators around the globe.
‘Computer program per se’ versus protecting AI inventions
‘Computer program per se’ means a computer program without hardware implementation, which is considered to be a mathematical model, business method, presentation of information or a scheme. As AI falls into this category, it is therefore deemed unpatentable in all major jurisdictions. However, these inventions can be protected by linking the computer program to a hardware or computer network since it may include certain other things, which are ancillary to or developed through the program. Therefore, when drafting AI or machine learning-based inventions, it is worth showing real-world application rather than an abstract idea.
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
For instance, a machine learning model may be deemed a mathematical model or abstract idea and is therefore unpatentable. However, the model embedded in a self-driving vehicle for automatic detection of a route can be considered to provide a technical enhancement to self-driving vehicles and thus meets the patentability criteria. Inventors around the globe are encouraged to link AI with practical applications and innovate AI-assisted technology.
Since AI-based inventions can be categorised as abstract ideas, a solution-based approach should be kept in mind when drafting patent applications. Here are some tips:
read more -www.lexology.com
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