According to the World Health Organisation’s (WHO) official website for coronavirus, the dis- ease has spread to approximately 214 countries and regions. While the disease is spreading mercilessly around the world, science and technology are giving it an equal fight. The pan- demic is a test of governments’ medical capacity and their political will; it also raises several philosophical questions. It is a test of humans as a unit. A test of humanity as a whole. Artifi- cial Intelligence (AI) is intended to imitate human cognitive functions. It will bring significant change to health care, driven by the growing accessibility of healthcare data and rapid ad- vancement of analytics practices. During the current COVID-19 pandemic, AI is being used to assist and advise doctors in establishing a diagnosis, to support radiologists in refining image explanation, and help in the advancement of drug discovery research. The upsurge of new technologies gives rise to new questions. There is still considerable uncertainty in the field of Intellectual Property (IP) protection of AI-generated works. AI does not have legal person- hood, so the question remains about whether it holds any IP rights. In this article, we discuss the IP rights of AI-generated works with respect to the COVID-19 pandemic. The objective of this study is to determine the impact of international and national laws and treaties on IP rights for AI-generated solutions to the pandemic, as well as to study an alternative tempo- rary mechanism to make IP widely available to mobilise resources and manufacture critical products to prevent, diagnose or treat COVID-19. The paper attempts to strike a balance between the needs of health care, life-threatening emergencies and IP rights by applying a utilitarian theory of IP law that denotes the «utility» of all people, aiming to secure «the great- est good for the greatest number». This
CITATION STYLE
Sharma, C., & Sony, R. (2020). AI-Generated Inventions and IPR Policy During the COVID-19 Pandemic. Legal Issues in the Digital Age, 2(2), 63–91. https://doi.org/10.17323/2713-2749.2020.2.63.91
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