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Computer Models of Musical Creativity, David Cope MIT Press (2005)
... In truth, early explorations into computer-assisted musicmaking or production have been made since at least the early 1950s, when experimental composer John Cage firstly created his Music of Changes; a piece that was inspired by an ancient Chinese text (the I Ching), whose complex symbols were applied through the help of a computer program to musical elements (like tempo, duration, dynamics etc.) of the song. However, it is only recently that machine learning has enabled a series of factual progresses that were not even foreseeable a decade ago (Cope 2005;Dannenberg 2006;Wu et al. 2020). To date, there are several AI algorithms that permeate virtually any aspect of the music-making process and they can be roughly classified in three major categories: a. algorithms for composition, b. algorithms for songwriting, c. algorithms for mixing and mastering. ...
As we write this research paper, we notice an explosion in popularity of machine learning in numerous fields (ranging from governance, education, and management to criminal justice, fraud detection, and internet of things). In this contribution, rather than focusing on any of those fields, which have been well-reviewed already, we decided to concentrate on a series of more recent applications of deep learning models and technologies that have only recently gained significant track in the relevant literature. These applications are concerned with artistic production (Sect. 2.1), the writing process (Sect. 2.2), music production (Sect. 2.3), text recognition and attribution (Sect. 2.4). After reviewing and analyzing the positive contributions as well as some of the major limitations of these technologies in each of those fields, we critically reflect (Sect. 3) on how their widespread implementation may affect humans and their creativity. In Sect. 4, we notice that deep learning models are here to stay; so, rather than embracing a negative or pessimistic stance with respect to their future applications in creative domains, we suggest a balanced approach for their assessment and beneficial usage. Finally (Sect. 5), we conclude by summarising what we have achieved and by pointing out possible future research directions.
... If "creativity" is viewed an innately human capability, then how might we be forced to reconceptualize our understanding of artwork when AI produces more aesthetically pleasing artwork or passes the artistic "Turing Test?" Artificial intelligence's pursuit of art is not limited to visual arts. Currently, there are studies on building artificial intelligence to create music and poems [9][10][11]. Some might say these creative products created by AI merely imitate human work. ...
This study examines how people perceive artwork created by artificial intelligence (AI) and how presumed knowledge of an artist's identity (Human vs AI) affects individuals' evaluation of art. Drawing on Schema theory and theory of Computers Are Social Actors (CASA), this study used a survey-experiment that controlled for the identity of the artist (AI vs. Human) and presented participants with two types of artworks (AI-created vs. Human-created). After seeing images of six artworks created by either AI or human artists, participants (n=288) were asked to evaluate the artistic value using a validated scale commonly employed among art professionals. The study found that human-created artworks and AI-created artworks were not judged to be equivalent in their artistic value. Additionally, knowing that a piece of was created by AI did not in general influence participants' evaluation of art pieces' artistic value. However, having a schema that AI cannot make art significantly influenced evaluation. Implications of the findings for application and theory are discussed.
... For hundreds of years, music was not only a source of inspiration, relaxation or an element used in rituals, but it was also closely related to nature sciences and mathematics. However, musical compositions are too big and too complicated, so that they could be put into mathematical structures practically (Dannenberg, 2006). MCT's usability is quite wide, various software (music creation, music recognition, music learning programs) have become available to any person (Thibeault, 2012). ...
Purpose – to find out possibilities of development of musical creativity by using MCT in the music education of senior pupils.
Design/methodology/approach – literature review, qualitative survey methodology (interview with music teachers).
Findings – implementation of MCT, like any other innovation (as well as ICT) in different spheres of education, including pre-school education, bring forth a certain positive effect. The results of the interview showed that in the praxis of music education, MCT is used for different development purposes (to make a lesson original, help pupils memorize music, expand their imagination not only by listening, but also by watching and evaluating performance of music, listen to music recordings, understand music and evaluate its quality, etc.). But for the development of musical creativity, MCT has been used very poorly.
Research limitation/implications – musical creativity’s concept has not been uniquely defined so far. The aim of scientific literature review is to show that musical creativity is not meant to be separated from general creativity. Moreover, this is compounded by the search of the possibilities to the development of musical creativity. Analysis of scientific literature shows that the use of MCT can make an influence on musical creativity. However, empirical researches on this subject are still missing.
Practical implications – the results of the interviews about using MCT in music lessons in order to develop musical creativity could be significant in formulating strategies of the development of musical creativity, preparing methodological instruments as well as in teacher training programs.
Originality/value – the object of the survey in the chosen theme has never been explored in Lithuania, while the comparison of the obtained data with foreign scientists’ discoveries could contribute to a musical creativity’s definition.
Research type: literature review, interview review.
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