The Influence of Artificial Intelligence on Songwriting : Navigating Attribution Challenges and Copyright Protection

Sammanfattning: This report explores the evolving landscape of songwriting and copyright protection, with a focus on the influence of Artificial Intelligence (AI). It highlights the need for objective measures of attribution in music co-creation, including collaborations involving AI. The study explores the potential of employing Natural Language Processing (NLP) methods in song lyric generation, to assign attribution more accurately and transparently. The report also discusses the perspectives of various stakeholders in the music industry highlighting the importance of attribution and addressing concerns related to AI-generated works. The research combines quantitative and qualitative methodologies, including surveys, interviews, and literature reviews, to provide comprehensive insights into the complexities of attribution in songwriting and the implications of AI’s involvement. The survey compared original song choruses to modified versions, gathering insights on the significance of text modifications. Statistical analysis and NLP techniques; levenshtein distance, plagiarism detection, sentiment analysis, and cosine similarity, were used to assess textual changes. The results indicated that primarily sentiment analysis, but also cosine similarity, aligned closer with the survey responses. Interviews provided valuable perspectives on challenges in attribution and copyright, as well as thoughts regarding AI in songwriting and ethical considerations. Current attribution methods often lead to unequal royalty distribution in co-created works. Objective metrics, including NLP techniques, could potentially offer a compliment for tracking attribution in a more quantitative way. Stakeholder analysis reveals the interests and power dynamics of songwriters, artists, labels, consumers, and lawyers. AI’s involvement raises questions about data sources, developer roles, and quantifying creativity, posing challenges in determining attribution, royalty distribution, and copyright protection. The report also underscores the importance of quantifying creativity, preserving creative integrity, and meeting the diverse needs of stakeholders within an AI-driven musical landscape.