Citation

Khong, Dennis Wye Keen and Su, Wai Mon (2023) Artificial intelligence as a common heritage of mankind. UUM Journal of Legal Studies, 14 (1). pp. 113-139. ISSN 2229-984X

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Abstract

Artificial intelligence technologies today employ techniques known as machine learning and deep learning, which apply datasets to a suitable mathematical or statistical technique known as an algorithm. This in turn produces a model that can be employed to predict an outcome, given a new set of data that was previously unseen by the model. The principle of common heritage of mankind, which has originated in the 19th century, promotes the concept that humanity as a whole has rights and responsibilities over territories or outer space. This study aims to advance the concept of treating the components of artificial intelligence as an intellectual common in the form of a common heritage of mankind, in order to promote the discovery and the development of more novel artificial intelligence applications for the benefit of people around the world. This work employs a mix of legal doctrinal research related to intellectual property law and conceptual theoretical discussion. The potential application of open access and open data licensing is discussed. The history of the common heritage of mankind is covered, and the potential benefit of recognizing basic artificial intelligence components as a common heritage of mankind is explored. Finally, a novel method for implementing this idea is proposed. This work is significant in advancing a method to liberate certain artificial intelligence technologies from intellectual property rights protection, in order to promote greater experimentation and the development of artificial intelligence applications for the greater good of humanity.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence, Machine learning, Deep learning, Intellectual property, Common heritage of mankind
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Law (FOL)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	01 Mar 2023 02:01
Last Modified:	01 Mar 2023 02:03
URII:	http://shdl.mmu.edu.my/id/eprint/11162

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