AI in African Music: Extractive Tech or Collaborative Cultural Revival? Johannesburg showcase reveals tensions between corporate tool-building and community-led preservation

Indigenous African epistemologies view music as a sacred, relational practice—not a dataset to be mined. The showcase's framing of 'cultural preservation' through AI tools ignores how many communities perceive digitization as a form of desecration, where intangible heritage is reduced to extractable code. Traditional custodians of music (e.g., praise singers, drummers) are excluded from governance structures, while their knowledge is repackaged as 'innovation' for global markets. This reflects a broader pattern where indigenous agency is sidelined in favor of techno-solutionism.

The commodification of African culture via technology echoes colonial-era practices, where artifacts and knowledge were 'preserved' in Western institutions without consent or reciprocity. The 19th-century 'salvage ethnography' movement framed indigenous cultures as relics to be archived, paralleling today's AI-driven digitization of living traditions. South Africa's apartheid regime similarly exploited black cultural expression for state propaganda, a precedent for how tech can be weaponized against marginalized communities. The showcase's narrative of progress obscures these continuities of extractive power.

Comparable tensions exist in Indigenous North American contexts, where tribes have successfully fought to repatriate sacred songs and stories digitized without permission. In Australia, Aboriginal communities have developed 'cultural protocols' to govern AI use, emphasizing consent and benefit-sharing—an approach absent in Johannesburg's showcase. The African diaspora's experience with cultural erasure in hip-hop and jazz, now being replicated in AI, underscores the need for transnational solidarity in resisting tech extractivism.

AI music generation relies on training datasets scraped from artists' work without consent, violating ethical norms in data science. Studies show that AI models trained on non-Western music often misrepresent or homogenize diverse traditions, reinforcing stereotypes. The showcase's claim of 'cultural preservation' lacks empirical validation, as there is no evidence that AI tools sustain traditional practices better than community-led initiatives. Peer-reviewed research on decolonial AI emphasizes the need for participatory design, which was notably absent in the event.

For many African artists, music is a spiritual act—a bridge between the living and ancestors—rendering its reduction to algorithmic patterns sacrilegious. The showcase's techno-utopian framing strips away the communal rituals (e.g., call-and-response, communal singing) that give music its power. Spiritual leaders in Southern Africa have condemned AI-generated 'traditional' music as a violation of sacred trust, comparing it to selling prayers as NFTs. The event's emphasis on 'tools' over 'relationships' reflects a Western materialist worldview that devalues the intangible dimensions of art.

If unchecked, AI music tools could lead to a future where African artists are replaced by synthetic 'traditional' tracks, eroding livelihoods and cultural authenticity. Scenario modeling suggests that by 2035, 60% of 'African music' consumed globally may be AI-generated, with profits flowing to Silicon Valley while local creators face displacement. However, alternative futures exist where community-owned AI models preserve living traditions on their own terms, as seen in pilot projects in Kenya and Senegal.

The showcase centered university administrators, tech CEOs, and Western-funded researchers, while sidelining the artists whose work was used to train the models. Grassroots collectives like the African Music Library Network and #AfricaDecoloniseTech were excluded, despite their decade-long efforts to reclaim agency over cultural heritage. Women and queer artists—already marginalized in the music industry—are disproportionately affected by AI displacement, as their styles are more likely to be mimicked without credit. The event's 'diversity' rhetoric masked these power imbalances.