The rapid development of so-called "artificial intelligence" presents both society and culture with increasing challenges on various fronts. When it comes to implementations in the arts, questions of whether computers can attain creativity and understand emotions, or at least produce results comparable to human output, are controversial and test established artistic ideas and models.

Throughout such processes, differing conceptions of emotionality and creativity emerge. Depending on the model of creativity, machines are attributed with potentials exceeding human possibilities (combinatorial creativity) or saddled with insurmountable limitations (topical creativity). Do creative achievements necessarily emerge through human attempts to transcend limitations? Aren’t the contexts and histories of the arts indispensable in the pursuit of feeling, perceiving, and understanding them? And isn’t it precisely such information that is in danger of being lost in the face of big data, algorithmic recommendation, pattern recognition, and other applications of machine learning within culture? Should we perhaps be less concerned that machines could become human-like artists, and more alarmed about the alignment of human creativity and perception of art with machine processes?