Investigator:
Runhua Wang

Abstract:
With the rise of artificial intelligence (AI)-assisted inventions, a disruptive issue for modern patent regimes is how to accommodate these inventions within the regimes designed for human inventors. On the one hand, it is radical to authorize personality rights to AI systems. On the other hand, it is unrealistic to exclude AI-assisted inventions from patent regimes. While the U.S., E.U., and European countries provide principles or guidelines addressing the issue, neither patent offices nor courts have established clear and consistent rules that can effectively solve the issue.

This research project aims to clarify the patentability threshold for AI-assisted inventions from an efficiency and comparative perspective, emphasizing the impact of synthetic creativity on human creativity and modern patent regimes. Synthetic creativity refers to a cheap and synthetic substitute for human creativity, provided by AI technologies, such as machine learning. When overlooking the concept of synthetic creativity and its impact on innovation, the existing literature has not resolved the issue in patent laws, even after applying frameworks such as the Coase Theorem or John Locke’s labor theory. The research project elucidates the concept and characteristics of synthetic creativity and the increased social and administrative costs it imposes.

To effectively promote innovation while reducing these costs, this research project revisits patent laws from a dynamically evolving view and complements the laws by other innovation policies and AI regulations implemented by the U.S., E.U., and some European countries. Without such considerations, a gap persists between the AI regulations that constrain certain inventing processes involving the application of AI systems and patent laws that promote innovation, which can be further enhanced by the use of AI systems. This research project addresses the gap that creates uncertainties for innovation.