Clarifying Assumptions About Artificial Intelligence Before Revolutionising Patent Law

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@Article{Kim:2022:GRURint,

• author = "Daria Kim and Maximilian Alber and Man Wai Kwok and Jelena Mitrovic and Cristian Ramirez-Atencia and Jesus Alberto {Rodriguez Perez} and Heiner Zille",
• title = "Clarifying Assumptions About Artificial Intelligence Before Revolutionising Patent Law",
• journal = "GRUR International",
• year = "2022",
• volume = "71",
• number = "4",
• pages = "295--321",
• month = apr,
• keywords = "genetic algorithms, genetic programming",
• ISSN = "2632-8623",
• URL = "https://eprints.gla.ac.uk/266204/1/266204.pdf",
• URL = "https://academic.oup.com/grurint/article-pdf/71/4/295/43056727/ikab174.pdf",
• DOI = "10.1093/grurint/ikab174",
• size = "27 pages",
• abstract = "We examine 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.",

}

Genetic Programming entries for Daria Kim Maximilian Alber Man Wai Kwok Jelena Mitrovic Cristian Ramirez-Atencia Jesus Alberto Rodriguez Perez Heiner Zille

Citations