  The rapid advancement in machine learning has led to a surge in automatic
data generation, making it increasingly challenging to differentiate between
naturally or human-generated data and machine-generated data. Despite these
advancements, the generation of creative data remains a challenge. This paper
aims to investigate and comprehend the essence of creativity, both in general
and within the context of natural language generation. We review various
approaches to creative writing devices and tasks, with a specific focus on the
generation of poetry. We aim to shed light on the challenges and opportunities
in the field of creative data generation.
