Recent advances in machine learning have led to an acceleration of interest in research on artificial intelligence (AI). This fostered the exploration of possible applications of AI in various domains and also prompted critical discussions addressing the lack of interpretability, the limits of machine intelligence, potential risks and social challenges. In the exploration of the settings of the "human versus AI" relationship, perhaps the most elusive domain of interest is the creation and understanding of art. Many interesting initiatives are emerging at the intersection of AI and art, however comprehension and appreciation of art is still considered to be an exclusively human capability. Rooted in the idea that the existence and meaning of art is indeed inseparable from human-to-human interaction, the motivation behind this paper is to explore how bringing AI in the loop can foster not only advances in the fields of digital art and art history, but also inspire our perspectives on the future of art. The variety of activities and research initiatives related to "AI and Art" can generally be divided into two categories: 1) AI is used in the process of analyzing existing art; or 2) AI is used in the process of creating new art. In this paper, relevant aspects and contributions of these two categories are discussed, with a particular focus on the relation of AI to visual arts. In recent years, there has been a surge of interest among artists, technologists and researchers in exploring the creative potential of AI technologies. The use of AI in the process of creating visual art was significantly accelerated with the emergence of Generative Adversarial Networks (GAN) [56].

The public queues for hours at the Musée du Louvre in Paris to catch a glimpse of this much studied portrait. But, according to AI, it's not much to look at really. At least that is the outcome from a project being undertaken at the Art and Artificial Intelligence Lab at Rutgers University. The team at Rutgers has been using AI to analyze and create art for the past five years, studying around 80,000 different paintings by over 1,100 artists. One of the first outcomes from the research was the replication of known painting styles.