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The Impact of AI on Music
Jelane Mock
STEM471: Analytics, Algorithms, AI, and Humanity
14 January 2024
1
The Impact of AI on Music
Introduction
The harmony between technology and art has brought on groundbreaking innovations, with artificial intelligence (AI) and algorithms reshaping the landscape of the music industry. This essay will explore the consequence of big data, algorithms, and AI on music, concentrating on the specific realm of algorithmic composition. While these technological advancements have brought on a new era of music creation, there are concerns about the creativity, originality and the commercialization of artistic expression. This essay will also explore a proposal to mitigate these negative impacts, dissecting the problem, and evaluate the viability of the proposed solution.
Problems and Solutions
According to Somers, “Algorithmic composition refers to the practice of using algorithms
to create music” (Somers, 2021). It empowers the creation of music based on identified patterns and preferences. However, the reliance on these data-driven algorithms raises concerns about diminishing artistic originality and creativity. This generation of music may prioritize commercially successful patterns, resulting in a blend of the music outputted. Miranda and Wanderley's research (2014) highlights the delicate balance required between algorithmic predictability and artistic innovation in computer-assisted composition. The SGA Knowledge Team states, “Striking the right balance between creativity and data-driven decision-making is vital to prevent the overreliance on analytics. But the thin line between art and business that has always existed in music needs to find the correct harmony” (SGA Knowledge Team, 2022). Zohvib also echo’s apprehensions about the impact of algorithmic recommendations on their 2
creative autonomy in the article “The Algorithm Effect — A Generation of Brainwashed Artists”
(Zohvib, 2023). To address the negative impact on artistic originality and creativity, a proposed solution involves the implementation of ethical guidelines for algorithmic composition. These guidelines would encourage developers and musicians to prioritize diversity, innovation, and the preservation of individual artistic expression in AI-generated music. One such guideline could be
establishing criteria that promotes diversity, such as ensuring that AI-generated compositions do not solely rely on popular or commercially successful patterns. One challenge would be getting the buy-in all stakeholders, including musicians, developers, and consumers. Another challenge could be defining the standards for creativity. Another major problem lies in the commercialization of artistic expression in the music industry. The integration of big data and algorithms has led to the prioritization of commercial success over the value or creative work. This brings concerns about its impact on independent artists and the marginalization of diverse music. As stated by Alex Krotz, “because of Spotify’s algorithm, it is better to create songs like what people are listening to already in order to get “picked up” by the algorithm. Looking at the Global Music Report for 2021, the Top 10 Global Songs seem to be of a similar vein: artists like The Weekend, Drake, and Billie Eilish appear multiple times” (Michell, 2022). Interviews with independent musicians further emphasize challenges in gaining visibility and recognition amid algorithmic promotion of mainstream content (Hesmondhalgh, 2021).
The proposed solution to counteract this problem involves developing and implementing fair models for compensating independent artists and labels. This would entail restructuring of revenue distribution on streaming platforms to ensure that artists receive equitable compensation 3
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