?
Criteria for the Legal Protection of Artificial Intelligence-Generated Intellectual Property
The development of Artificial Intelligence (AI) is challenging the traditional legal view of intellectual property. The subject of present research is the justification of the necessity of legal protection of the results of intellectual activity created by AI. The main risk of using AI in the creation of a work is the impossibility of legal protection of the work. AI can also violate intellectual property rights. In addition to violating rights mentioned, an object created by AI may not be real and be misleading, as well as violate law on personal data. Legal constructions should be modified to the new digital realities. The relevance of the research topic lies in the fact that AI puts a choice before legislators: to recognize AI sui generis legal personality or to replace the criterion of creativity with the criterion of investment. The aim of this research is to resolve this dichotomy. The methodological apparatus of this research includes comparative-legal and formal-logical methods. The novelty of the research is the analysis of the hypothesis: replacing the criterion of creativity with the criterion of investment as a criterion of legal protection. The conclusion of the exploration is that replacing the creativity criterion with the investment criterion seems to be the most preferable de lege lata solution. The current situation with the lack of a legal protection for objects created by AI may violate the equilibrium in the market of digital products and does not contribute to the resolution of the problem of legal uncertainty of the legal protection of the results of intellectual activity created by AI. Research in this direction it has a sense to be continued: a legal framework focusing on access, sharing, and use of data for the common good should be developed, while ensuring adequate privacy protections and workable means of protecting individuals from harm arising from data processing. Legal cornerstones need to be identified to improve access, use, and the sharing of data. The question of the law applicable to an AI system that uses raw data from different jurisdictions for training is also important.