HAISP: A Dataset of Human-AI Songwriting Processes From the AI Song Contest

The advent of accessible artificial intelligence (AI) tools and systems has begun a new era for creative expression, challenging us to gain a better understanding of human-AI collaboration and creativity. In this paper, we introduce Human–AI Songwriting Processes Dataset (HAISP), consisting of 34 coded submissions from the 2023 AI Song Contest. This dataset offers a resource for exploring the complex dynamics of AI-supported songwriting processes, facilitating investigations into the possibilities and challenges posed by AI in creative endeavors. Overall, HAISP is anticipated to contribute to advancing understanding of human-AI co-creation from the users' perspective. We suggest potential use cases for the dataset, including examining AI tools used in songwriting and exploring users' ethical considerations and creative approaches. This could help inform academic research and practical applications in music composition and related fields.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-10
DOI
https://doi.org/10.5281/zenodo.14877357
Primary Topic
Music Technology and Sound Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

HAISP: A Dataset of Human-AI Songwriting Processes From the AI Song Contest

Zenodo (CERN European Organization for Nuclear Research)
Music Technology and Sound Studies
article

HAISP: A Dataset of Human-AI Songwriting Processes From the AI Song Contest

article en

Abstract

The advent of accessible artificial intelligence (AI) tools and systems has begun a new era for creative expression, challenging us to gain a better understanding of human-AI collaboration and creativity. In this paper, we introduce Human–AI Songwriting Processes Dataset (HAISP), consisting of 34 coded submissions from the 2023 AI Song Contest. This dataset offers a resource for exploring the complex dynamics of AI-supported songwriting processes, facilitating investigations into the possibilities and challenges posed by AI in creative endeavors. Overall, HAISP is anticipated to contribute to advancing understanding of human-AI co-creation from the users' perspective. We suggest potential use cases for the dataset, including examining AI tools used in songwriting and exploring users' ethical considerations and creative approaches. This could help inform academic research and practical applications in music composition and related fields.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 61%
Music Technology and Sound Studies
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