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Generative Artificial Intelligence, Musical Heritage and the Construction of Peace Narratives: A Case Study in Mali

Nouhoum Coulibaly, Ousmane Ly, Michael Leventhal, Ousmane Goro

TL;DR

Mali faces social fragmentation and a demand for narrative innovations to support reconciliation. The study investigates Gen AI-enabled, multilingual musical co-creation using Suno AI, ChatGPT, and GEMINI within a three-day participatory workshop to generate Mali-inspired pieces that blend traditional instruments with modern textures. Results reveal three hybrid architectures, multilingual strategies, and a four-phase peace narrative structure, accompanied by positive social effects and policy-relevant insights alongside limitations in linguistic data and censorship. The work highlights Gen AI as a tool for digital cultural sovereignty, offering a pathway to scalable, locally grounded peace narratives and inviting longitudinal and cross-context comparative research.

Abstract

This study explores the capacity of generative artificial intelligence (Gen AI) to contribute to the construction of peace narratives and the revitalization of musical heritage in Mali. The study has been made in a political and social context where inter-community tensions and social fractures motivate a search for new symbolic frameworks for reconciliation. The study empirically explores three questions: (1) how Gen AI can be used as a tool for musical creation rooted in national languages and traditions; (2) to what extent Gen AI systems enable a balanced hybridization between technological innovation and cultural authenticity; and (3) how AI-assisted musical co-creation can strengthen social cohesion and cultural sovereignty. The experimental results suggest that Gen AI, embedded in a culturally conscious participatory framework, can act as a catalyst for symbolic diplomacy, amplifying local voices instead of standardizing them. However, challenges persist regarding the availability of linguistic corpora, algorithmic censorship, and the ethics of generating compositions derived from copyrighted sources.

Generative Artificial Intelligence, Musical Heritage and the Construction of Peace Narratives: A Case Study in Mali

TL;DR

Mali faces social fragmentation and a demand for narrative innovations to support reconciliation. The study investigates Gen AI-enabled, multilingual musical co-creation using Suno AI, ChatGPT, and GEMINI within a three-day participatory workshop to generate Mali-inspired pieces that blend traditional instruments with modern textures. Results reveal three hybrid architectures, multilingual strategies, and a four-phase peace narrative structure, accompanied by positive social effects and policy-relevant insights alongside limitations in linguistic data and censorship. The work highlights Gen AI as a tool for digital cultural sovereignty, offering a pathway to scalable, locally grounded peace narratives and inviting longitudinal and cross-context comparative research.

Abstract

This study explores the capacity of generative artificial intelligence (Gen AI) to contribute to the construction of peace narratives and the revitalization of musical heritage in Mali. The study has been made in a political and social context where inter-community tensions and social fractures motivate a search for new symbolic frameworks for reconciliation. The study empirically explores three questions: (1) how Gen AI can be used as a tool for musical creation rooted in national languages and traditions; (2) to what extent Gen AI systems enable a balanced hybridization between technological innovation and cultural authenticity; and (3) how AI-assisted musical co-creation can strengthen social cohesion and cultural sovereignty. The experimental results suggest that Gen AI, embedded in a culturally conscious participatory framework, can act as a catalyst for symbolic diplomacy, amplifying local voices instead of standardizing them. However, challenges persist regarding the availability of linguistic corpora, algorithmic censorship, and the ethics of generating compositions derived from copyrighted sources.
Paper Structure (21 sections, 2 figures)

This paper contains 21 sections, 2 figures.

Table of Contents

  1. Introduction: Context and Problem Statement
  2. Methodology
  3. Study design and Research Questions
  4. Study Population
  5. Workshop Structure
  6. Creative Process and Prompt Engineering
  7. Data collection and analysis
  8. Results
  9. Hybrid musical architectures
  10. Linguistic and semantic strategies
  11. Narrative structures
  12. Instrumentation and cultural significance
  13. Vocal performance
  14. Technological appropriation
  15. Social and perceptual effects
  16. ...and 6 more sections

Figures (2)

  • Figure 1: Relationship analysis showing prior AI experience vs. workshop satisfaction, average satisfaction by experience level, perception of musical heritage authenticity, and self-assessed capability for independent creation (n=13).
  • Figure 2: Workshop challenges identified by participants (left) and most enriching workshop phases (right). Linguistic authenticity and traditional instrument reproduction emerged as primary technical limitations.