Artificial Intelligence in Music: The Digital Revolution of Sound Creativity / Inteligența Artificială în muzică: Revoluția digitală a creativității sonore

The issues of what Artificial Intelligence (AI) can and cannot do in the field of music are among the important topics that both music researchers and AI experts are curious about. This study offers a significant analysis within the context of the growing role of AI technologies in music composition and their impact on creative processes. It contributes to the literature by positioning AI as a complementary tool to the composer’s creativity and by enhancing the understanding of cultural adaptation processes. The study aims to identify the perceptual differences between AI and composer compositions, examine the musical and cultural foundations of these differences, and uncover the factors that influence the listener’s experience. In the research design, a mixed-method approach was adopted, combining qualitative and quantitative research methods. In the quantitative phase, a double-blind experimental design was employed to ensure that participants evaluated composer and AI works impartially. In the qualitative phase, participants’ opinions were gathered. The participants were 10 individuals aged between 19 and 25, with diverse cultural and educational backgrounds; 6 had received formal music education, while 4 were casual listeners. The data collection instruments included a structured interview form and the Assessment Scale for Perceptual Factors in Musical Works. During the research process, each participant evaluated two AI and two composer works in 20-minute standardized listening sessions. All listening sessions were conducted using professional audio equipment. The analysis revealed that composer works scored significantly higher than AI works across all categories (p<.05). Notable differences were observed, particularly in the categories of emotional depth (X composer = 4.6, X AI = 3.1) and memorability (Xcomposer = 4.4, XAI = 3.2). The study concluded that composer works were more effective than AI compositions in terms of emotional depth, structural coherence, and cultural resonance. Additionally, cultural background and music education emerged as significant factors shaping perceptual differences. Future research should broaden the participant pool and incorporate neurocognitive data to facilitate a deeper understanding of perceptual mechanisms. Furthermore, the development of AI systems for use in music should include the integration of Transformer and RNN-based advanced learning models, the implementation of traditional music theory principles, the enhancement of emotional expressiveness, the improvement of cultural adaptation capacities, and the refinement of real-time interaction mechanisms.

SummaryThe recent sale of an artificial intelligence (AI)-generated portrait for $432,000 at Christie's art auction has raised questions about how credit and responsibility should be allocated to individuals involved and how the anthropomorphic perception of the AI system contributed to the artwork's success. Here, we identify natural heterogeneity in the extent to which different people perceive AI as anthropomorphic. We find that differences in the perception of AI anthropomorphicity are associated with different allocations of responsibility to the AI system and credit to different stakeholders involved in art production. We then show that perceptions of AI anthropomorphicity can be manipulated by changing the language used to talk about AI—as a tool versus agent—with consequences for artists and AI practitioners. Our findings shed light on what is at stake when we anthropomorphize AI systems and offer an empirical lens to reason about how to allocate credit and responsibility to human stakeholders.

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At present, artificial intelligence products and programs are widely utilized in every aspect of people’s daily life, including artistic creation. The viewer usually sees the outcome rather than the process in the case of artworks. However, the production process of an artistic work often influences the viewer’s appraisal of the creativity of the work. Nowadays, however, most studies concentrate on artificial intelligence artwork performance while ignoring the process of creation. This study conducted experiments with the ARS scale on the theoretical basis of schema theory to analyze whether there is any difference in the viewer’s appraisal of artistic works after realizing the process of artistic creation. The goal is to examine whether the process of creation can influence the viewer’s appraisal of creativity on the outcome generated by artificial intelligence. The results show that the appraisal of artificial intelligence artistry is influenced by the creative process to a certain extent, and the appraisal of the works with more diversified colors are affected more than those with monochrome color.

Artificial Intelligence (AI) is increasingly integrated into creativity and innovation processes in the modern world. However, concerns have been raised regarding its effects on human creativity. The automated content generation provided by AI, its guidance in problem-solving processes, and its facilitation of artistic production may negatively impact individuals' creative thinking capacities (Carr, 2020). By generating content through big data analysis and algorithms, AI may restrict human creativity. Particularly in the fields of art, writing, and design, the widespread use of AI-based tools may diminish individuals' abilities to generate original ideas. Some studies indicate that individuals may become excessively dependent on AI suggestions, thereby relegating their own creative processes to a secondary position (Kowalski, 2021). This phenomenon may lead to a decline in people's creative problem-solving skills and a reduction in innovative thinking. Moreover, the tendency of AI-generated content to become homogenized may result in a decrease in artistic and cultural diversity. AI systems learn from past data to produce content, which can confine creative processes within the patterns of the past (Smith & Anderson, 2022). One of the fundamental elements of creativity, individual and societal originality, may be compromised due to AI's repetitive nature. Finally, considering AI’s impact on problem-solving processes, it is suggested that individuals' critical thinking skills may deteriorate over time. The ability of AI to provide fast and accurate solutions may weaken people's habits of inquiry and reduce their capacity to develop innovative solutions (McCarthy, 2023). In this context, AI is emphasized not as a tool that supports creative processes but as a factor that may constrain them.

Musical work creation using deep learning models has gained significant attention in recent years as advances in artificial intelligence (AI) and machine learning (ML) have allowed for new approaches to music composition, synthesis, and analysis. The creation of musical work using deep learning models requires specialized techniques that can learn complex patterns from large datasets of musical compositions, enabling the generation of original pieces that reflect the intricacies of musical theory and creativity. This research explores the application of deep learning models, particularly stacked artificial neural networks (ANNs), for generating musical compositions. By leveraging vast collections of MIDI data, the authors demonstrate how these models can learn hierarchical patterns of melody, harmony, rhythm, and structure. The study highlights the importance of data augmentation, particularly temporal and pitch transposition, in enhancing the diversity and complexity of the generated musical work.

Artificial Intelligence (AI) has ushered in a revolutionary change that mixes creative abilities between human composers and computer-powered intelligence during musical composition. The investigation examines the musical application of collaborative AI which exists as an aid to composers by suggesting ideas and creating motifs alongside enhancing musical arrangements. OpenAI’s MuseNet alongside Google’s MusicLM brought about new generative model technologies which enable musicians to have real-time access to adaptive tools that interpret as well as transform musical concepts. Based on secondary research and case studies, the article examines human composer-AI system partnerships to explain how their combined work restructures artistic authorship and creative methods. The paper uses today's artists with AI support and collaborative works between different fields to demonstrate the partnership's core dynamics. The discussion explores two main elements about AI music production which are human involvement versus programming automation alongside understanding emotional integrity in synthetic musical compositions together with co-creative copyrights regulations. This research evaluates how partnership between humans and AI components transforms musical education along with the process of composition for those without a musical background while testing established artistic boundaries of genre classification and original content production. This research project depicts AI as an amplification force that generates human creativity rather than being considered disruptive by showing how intelligent feedback systems work together with human agents. Co-creation behavior in this hybrid method motivates a fresh depiction of musical expression which sparks explorations about art creation and authorship roles and identity function in the future.

This PhD study is a contribution to the contemporary debate on the educational uses of digital technology with young children in early childhood education and care (ECEC) institutions. For young children growing up in the 21st century, digital technology is intertwined in their everyday lives. Nevertheless, children’s use of digital technology in ECEC is still limited, especially with regards to creative use of technology. Several researchers call for more empirical studies of young children’s creation with digital technology. In this study, digital technology is emphasised as a tool to create, by which the children and the teachers are the creators of their own products to be shared with others. The purpose is to contribute with research-based knowledge of children’s and teachers’ collaborative, technology- mediated story creation processes. The overall research question is as follows: What emerges when kindergarten teachers involve groups of children (age 4-5 years) in technology-mediated story creation processes? The study has a qualitative multiple-case study approach with two cases, focusing on observable contemporary events. In both cases, six children and one kindergarten teacher have created a multimodal digital story together: an e-book and an animated movie. The empirical material consists of video-recorded field-observations of the process, interviews with the participants and the final products. The research question is operationalised into three sub-questions that address the overall question from three perspectives: the participants, the creation processes, and the final products. In Article I, the technology- mediated creation process is explored, which can be described as a complex interplay of traditional non-digital activities and new digital activities. For the children, to record sound and to share were found to be the most important. In Article II, the teachers’ pedagogical strategies during the creation process with the children is emphasised. The three most frequently used pedagogical strategies were inviting to dialogue, explaining the practical, and instructing for results. In Article III, the animated movie is explored in-depth through a focus on how different modalities and literacy devices contribute to the development of the story. The importance of including the process, the product, the literacy devices, and all of the modalities in the analysis is highlighted, as well as the importance of being open for the magic during young children’s creation processes. Through the analysis of the three articles, four new themes have arisen: emerging possibilities due to digital technology; creators in a creative process; an interplay of multiple knowledge areas; and the process is not enough. In the discussion I argue that a technology-mediated story creation process with a group of kindergarten children and a teacher can be interpreted as a collaborative creative process. A synergy of ideas arises through the collaborative co-construction process. Each single part of the creative process may not be viewed as being inherently creative; however, the fusion of these parts into a final multimodal digital story makes it an example of the creative use of digital technology. The children and teachers collaborate and create a product that is new, original and meaningful for them. The process is vital; however, the process itself is not enough—the product also matters—especially for the children. Teachers’ capacity and knowledge of how to integrate technology and pedagogy with other relevant knowledge areas such as creativity and creative processes are crucial when using digital technology with children in ECEC. The final products may seem complicated to create; however, it is easier than it seems. The study contributes with research- based knowledge of creative use of digital technology with groups of young children, important for the ECEC field and kindergarten teacher education.

The primary objective of this study is to examine the impact of Artificial Intelligence (AI) on content creation across various creative industries, including writing, visual arts, and music composition. The research aims to analyze how AI technologies are transforming traditional creative processes, while also addressing the associated ethical, legal, and economic implications. Data were collected through a structured survey conducted between January and March 2024 among 250 professionals working in journalism, marketing, visual arts, and music production. A stratified random sampling technique was employed to ensure sectoral representation. The study utilized descriptive statistics and independent sample t-tests to evaluate AI's influence on creativity and related concerns. Data analysis was performed using SPSS software. The results revealed statistically significant impacts of AI on creative processes, with t-values of 5.50 (writing), 4.72 (visual arts), and 4.10 (music composition), all with p-values < 0.001, confirming the rejection of the null hypothesis. The findings highlight AI’s capability to enhance efficiency and innovation in content creation, while also raising critical ethical issues, such as authorship (mean score = 3.95), bias (mean = 4.05), and intellectual property rights. Economically, the study found evidence of AI contributing to job displacement and evolving employment patterns within creative sectors. This research underscores the dual nature of AI as both a transformative force and a source of emerging challenges, emphasizing the urgent need for robust ethical and legal frameworks to govern its use in content creation.

AUTHORSHIP ISSUE IN INDIAN COPYRIGHT LAW FOR WORKS CREATED BY ARTIFICIAL INTELLIGENCE Harini V. S, IV-year B.B.A LL. B (Hons), Tamil Nadu Dr. Ambedkar Law University, School of Excellence in Law, Chennai (India) Download Manuscript doi.org/10.70183/lijdlr.2026.v04.67 Artificial intelligence (AI) is increasingly participating in creative processes such as writing, music composition, and visual art production, raising Artificial intelligence (AI) is increasingly participating in creative processes such as writing, music composition, and visual art production, raising complex questions for copyright law worldwide. In India, the Copyright Act, 1957 is premised on a human-centric understanding of authorship, reflecting the traditional assumption that creativity originates from natural persons.

The article is devoted to revealing the peculiarities of the texture program performance reproduction of a musical work. Based on the consideration of the textural program as a sequence of changes in the musical performance during the process of developing the form of the work, the performer-pianist must build the appropriate means of performance: artistic and technical ones. An important role here belongs to the author and the editorial remarks, the content of which, however, is quite conditional and requires individual performance correction. The topicality of the chosen topic lies in the need for in-depth consideration of the problems of musical texture and its attributes in the piano-performance specification. The purpose of the research is to identify the performance component of the piano work textural program, to propose an algorithm for its analysis on a specific example of B. Liatoshynskyi’s cycle. The methodology: the article uses a set of general scientific and special musicological approaches for developing the content of the stated topic. Among them are the following methods: systematic and structural method, it is aimed at revealing the essence of the phenomenon of the musical work textured program; a deductive method, it determines the course of research in the direction from a general part (textural program of a musical work) to a special (specificity of textural performance during a piano work) and a specific one (textural programs of plays of the cycle by B. Liatoshynskyi); genre and stylistic types of analysis from the point of view of reproduction of these phenomena in textural programs; texture analysis as a kind of musicological analysis; performance analysis, which is aimed at identifying the features of the textural attributes of the work under consideration. The results of the study show that the process of a piano work performance in the direction of its full interpretation is inseparable from analytical observations on the texture program and its attributes. The set of analytical and performance-technical procedures has as its ultimate goal the act of performing a piano work, in which the composer’s intentions are reproduced by means of the individual style of the pianist. The novelty of this study is the extrapolation of ideas about the piano work textural program on the interpretive activities of the performer. Embodying own understanding of the textural process and its attributes in the interpretation, the performer demonstrates personal version of the work sound image, revealing the means of the drama and composition art features. The practical significance of the study lies in the possibility of using its provisions and conclusions in the courses “Musical Interpretation”, “Analysis of Musical Works”, “History of Piano Performance”, as well as in classes specializing in “piano” for bachelors and masters of the higher educational institutions of art and culture of Ukraine. Conclusions. Thus, the concept application of the piano work “texture program” in relation to the activities of the performer-interpreter raises a number of issues related to the means of the performance center: dynamics, articulation, agogics, in their vision by the musical composer and directly the performer. In this context, the identification and implementation of the piano work textured program gives the key to the disclosure of its ideological and artistic content, a clear understanding of the drama and form features, implemented in the act of performance.

In the present article the issue is raised about evaluation of the use of artificial intellect in the creation of musical compositions. By means of an interdisciplinary approach, the authors assert the thesis about the distinction between "creativity" and the "creative process", thereby distinguishing the results of the composer's personality from those created by means of artificial intellect (weak neuronal networks). The authors dwell in great detail on the process of creating musical compositions by using electronic computers and the latest neuronal networks. Special examples from music history show that modern computers possess unique sound generation technologies: for example, NSynth is able to synthesize a completely new sound, which simultaneously is partially a flute sound and partially resembles a sitar. Can we regard these latest digital processes in music as creativity? The authors of the article defend the position that in the present day they can only be described as a variant of the "creative process", which leaves the right for authorship to the composer. The issues raised in the article are particularly relevant in the modern era which, considering the accelerated development of digital technologies, may well pass into the era of transhumanism, when the ongoing connection of the human and the artificial intellect would only exacerbate these problems to a greater degree. Keywords: music, musical composition, creativity, harmony, art, figure, artificial intellect, neuronal network, algorithm.

Aim: The study aims to investigate the role of AI in creative processes. It examines whether AI-generated ideas outperform human-generated ideas in terms of originality, quality and preference. The study's goal is to shed information on AI's ability to function as a creative partner in order to enhance and increase human creativity. It focuses on evaluating and comparing AI-generated ideas to human-generated ideas to evaluate whether AI produces better ideas or not.Methodology: A mixed method approach was followed, using both qualitative and quantitative methods, i.e, experimentation and an online survey. The experiment initially comprised two groups of students: AI users and Non-AI users. Both groups were asked to generate ideas regarding a single prompt. These ideas, shuffled and combined into a single list was then presented to a third neutral group unknown to which ideas were AI generated and which were not. This group was then asked to vote for the top 5 ideas. Furthermore, an additional quantitative survey was also taken to further studies regarding AI usage and over-reliance concerns. Findings: The experiment resulted in 52.9% (98) votes were given to AI generated ideas while 47.3% (87) votes were given to ideas generated by humans. Furthermore, the idea that received the most votes was generated by AI. The top 5 most voted concepts have an equal number of AI and Non-AI generated results. Although both received the same top 5 score, it demonstrates that AI can develop creative and original ideas preferred by humans. Whereas the 5 least voted idea list comprised 3 ideas generated by humans and only 2 generated by AI. Additionally, the survey results indicated that approximately 62% of respondents were concerned about generative AI posing long-term risks to human creativity.Novelty & Implications: This study investigates the role of artificial intelligence (AI) in ideation and creative processes, as well as its collaborative interaction with humans. It studies if AI generates greater ideas than humans and makes comparisons between the two. Unlike earlier research, which has focused on AI's applications in academics, businesses, and other sectors, this study focuses on AI's function in creative ideation. The results indicate AI's positive impact, with AI-generated concepts receiving more votes overall. However, respondents also showed concern about the long-term effects of AI overuse on human creativity. The study suggests a balanced collaboration between AI and human minds to maximise creative potential.

This article examines the significant changes experienced by digital design artists in the era of artificial intelligence (AI), especially related to transformations in the creative process, originality and human values ​​in art. The main problem of this research is that the current development of AI technology with all its advances can create works of art quickly and with high quality, which previously could only be done by artists. This raises concerns among artists regarding the potential for commodification of works of art, loss of emotional elements and a decrease in the value of originality due to automatic processes that are less personal. But on the other hand, AI also opens up new opportunities in artistic exploration, allowing artists to integrate traditional techniques with technological innovations to speed up the creation process. Through a qualitative descriptive approach, the main aim of this research is to investigate artists' views regarding the use of AI, both as a partner and as a threat. The analysis results show that AI influences the role and identity of artists, especially in maintaining emotion and meaning in digital art. It is hoped that these findings can provide an understanding of the balance between technology and human expression in art, as well as answer ethical and aesthetic challenges in the context of art that continues to develop.

The use of Artificial Intelligence (AI) in creative content development has gained popularity. The usage of AI applications in producing creative output, including music, films, graphic design, and creative writing, is explained in this paper. AI’s capacity to examine vast volumes of data and identify trends offers possibilities for producing more engaging content for users. This paper describes how creative processes can be generated by AI algorithms. One instance is the application of AI to music composition, where sophisticated melodies and harmonies can be produced by algorithms. With deepfake technology, artificial intelligence is also utilized in video creation to create realistic visual material. AI in graphic design offers tools that can generate different designs automatically, which expedites the process of developing concepts. AI is capable of producing coherent and pertinent material for creative writing. The ethical and societal ramifications of AI in creation are also covered in this study, including concerns about copyright, authenticity, and the place of people in the creative process. Even while AI has numerous benefits in terms of efficiency and creativity, there are worries that its existence could diminish the value of human creativity and jeopardize artists’ livelihoods.The study’s findings demonstrate AI’s enormous potential to transform creative content but the long-term effects of integrating AI in the creative industries are to be further investigated, as is the development of regulations to guarantee its ethical and equitable application.