Daten als Rohstoffe und Entwicklungstreiber für selbstlernende Systeme Zum Regulierungsbedürfnis von Innovationshemmnissen durch Datennetzwerkeffekte - Hillmer, Katharina (Kartell- und Regulierungsrecht, 2021)
The current German law mandates data sharing only under narrow conditions. The increasing spread of "data-hungry" AI systems is prompting demands for data sharing obligations in other circumstances, directed in particular towards companies in the digital economy. This study questions whether it would be advisable to open up access to exclusive data from the private sector for training self-learning AI systems in order to promote innovation opportunities and incentives. It explores the question of whether case-by-case solutions or sector-specific regulatory responses are a better solution. For this purpose, proposals for change from politics and science are examined and own ideas are developed.