ArticleJournal of Intelligence2025
Exploring the Impact of Artificial Intelligence on the Creativity Perception of Music Practitioners.
Article in Journal of Intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI-driven psychological and cognitive decision processes in professional practice: a systematic review using music teachers as an instrumental case.Frontiers in psychology · 2026Pooled it
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study investigates the relationship between artificial intelligence (AI) tools and the creative abilities of music practitioners within the context of globalization and technological advancements that are transforming creative industries. Through a quantitative analysis, the study assesses how AI tool usage influences creative output. By surveying music practitioners from diverse backgrounds, it captures their experiences and perceptions of AI technologies in music creation. Grounded in cognitive science and diffusion of innovation theories, the research also empirically examines the relationship between AI technology acceptance and creativity perception, while considering the role of socioeconomic factors. Regression analysis was used to explore the relationships between key variables, ensuring robust and reliable results. The results suggest that AI technology acceptance is significantly correlated with creative performance, particularly among individuals with formal music education and experience using music composition software. However, socioeconomic factors such as age, gender, and professional background also influence how extensively AI is utilized in the creative process. These findings provide new insights into AI's role in creative industries and offer data to inform music education and technology training policies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.