  Machine learning generated content such as image artworks, textual poems and
music become prominent in recent years. These tools attract much attention from
the media, artists, researchers, and investors. Because these tools are
data-driven, they are inherently different than the traditional creative tools
which arises the question - who may own the content that is generated by these
tools? In this paper we aim to address this question, we start by providing a
background to this problem, raising several candidates that may own the content
and arguments for each one of them. Then we propose a possible algorithmic
solution in the vision-based model's regime. Finally, we discuss the broader
implications of this problem.
