Clarifying Assumptions About Artificial Intelligence Before Revolutionising Patent Law

Autor: Daria Kim, Maximilian Alber, Man Wai Kwok, Jelena MitroviĆ, Cristian Ramirez-Atencia, JesÚs Alberto RodrÍguez PÉrez, Heiner Zille
Jazyk: angličtina
Rok vydání: 2022
ISSN: 2632-8623
Popis: This paper examines several widespread assumptions about artificial intelligence, particularly machine learning, that are often taken as factual premises in discussions on the future of patent law in the wake of ‘artificial ingenuity’. The objective is to draw a more realistic and nuanced picture of the human-computer interaction in solving technical problems than where ‘intelligent’ systems autonomously yield inventions. A detailed technical perspective is presented for each assumption, followed by a discussion of pertinent uncertainties for patent law. Overall, it is argued that implications of machine learning for the patent system in its core tenets appear far less revolutionary than is often posited.
Databáze: OpenAIRE