Enhancing the Value of Patents as Corporate Assets in South Africa: How can Artificial Intelligence (AI) Assist?

Authors

DOI:

https://doi.org/10.17159/1727-3781/2021/v24i0a10736

Keywords:

patents, Corporate Assets, Artificial Intelligence, Machine-learning, deep learning, 4th Industrial Revolution, prior art search, patentability criteria, state of the art, patentability criter, intellectual property

Abstract

Although the accounting definition of assets contemplates intangible, abstract assets such as those embodied in intellectual property (IP), South African company law largely views IP as a legal and not a business asset. This paper tentatively suggests an approach that uses artificial intelligence (AI) to mitigate weaknesses in the South African patent law relating to the absence of patent searches and examinations. It is hoped that using AI will enable the filing of quality patents that satisfy the prescribed patentability criteria. High-quality patents will allow companies to accumulate patents as corporate assets. The approach is based on the algorithmic use of AI technologies such as machine learning, natural language processing, deep learning alongside the Internet of Things, and IP analytics to strengthen South Africa’s IP system and create asset value for corporations. The paper recommends using the proposed AI technologies by companies and the Patents Office to enable the filing of high-quality patents, which will lead to the accumulation of corporate assets in the form of patents. The methodology is doctrinal, and the paper relies on recent literature on IP and AI, South African law, case law and examples drawn from studies conducted in other countries.

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References

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Published

23-06-2021

Issue

Section

Special Edition: Corporate and Financial Markets 2021

How to Cite

Ndlovu, L. (2021). Enhancing the Value of Patents as Corporate Assets in South Africa: How can Artificial Intelligence (AI) Assist?. Potchefstroom Electronic Law Journal, 24, 1-38. https://doi.org/10.17159/1727-3781/2021/v24i0a10736

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