Autonomous Artificial Creators and Inventors : Who owns the IP rights when the machine creates? - Zabeen, Anika (My University, 2020)
Computers have become super computers at recent times. Computer programs such as AI and ML can execute tasks and projects autonomously and independently. It is smarter than other conventional computer programs in a sense that it has creative features like learning, thinking, evolving, and communicating. Using this type of smart computers in the inventive and creative process are becoming extremely popular amongst the inventors, scientists, and researchers. When using these machines, it gives the impression that the machine is inventing or creating the work instead of the people working behind it. As these machines internal and external state are utmost convoluted, it is incomprehensible for the common people. Therefore, identifying the true and original inventors and creative people behind the work is difficult. Moreover, if there is no proper right holder, the rights may not be assigned. This paper aims to solve this issue of inventorship and provide a solution to the problem. The statements made in this thesis will be supported with relevant leading case laws and experts’ opinions. This paper was inspired by the case of DABUS but it can be applied to all inventive and creative machines. Besides analysing the inventive step in regards of Machine learning and Artificial Intelligence, the inventive process, inventive contribution, and inventive act in the machines work will be evaluated to determine the inventors. The work has compared and analysed different legal systems, jurisdiction and patent offices to gain better understanding of the requirements. In addition, this paper has thoroughly described how the creative and inventive machines work and identified the true inventors behind each machine’s work.
Keywords: Intellectual Property Rights, Artificial Intelligence, Patent Laws, Machine Learning, Inventorship, Inventive step, Obviousness, Computer Implemented Inventions, Inventive process, Genetic Programming, Artificial General Intelligence, Neural Networks.