Debate over AI ethics rises as non-human music tops streaming charts

An AI-generated song breaking into the global music charts has reignited debate over the growing role of artificial intelligence in the arts and everyday life, raising fresh questions about authorship, consent, and creativity in the digital age.

A reimagined version of Belgian singer and rapper Stromae’s 2013 hit single “Papaoutai” has emerged as the highest new entry on Spotify’s Global chart this week, debuting at No. 168 with 1.29 million streams. The track, which recreates and reinterprets Stromae’s distinctive voice and musical style using AI technology, has quickly attracted widespread attention from listeners and critics alike, as highlighted in an article published by Newsweek.

The song, titled “Papaoutai—Afro Soul” and credited to Unjaps, mikeeysmind and chill 77, has now amassed more than 14 million global streams. Unjaps is an independent record label and music producer known for using artificial intelligence in music creation and promotion.

Although it has not been independently confirmed that the track was generated using AI, the cover version’s sudden popularity has already sparked concern and revived ongoing debates about the ethical boundaries of artificial intelligence in music.

Critics warn that AI-generated covers and original tracks risk exploiting artists’ voices and creative identities without their consent, potentially undermining both artistic ownership and livelihoods. At the same time, the article cites the voices of supporters of the technology, who counter that AI can serve as a tool for experimentation, homage, and creative expansion rather than a substitute for human musicians.

Legal frameworks have struggled to keep pace with these developments. In most countries, music created entirely by artificial intelligence is not eligible for copyright protection because it lacks a human author. As a result, such works immediately fall into the public domain, meaning original artists whose voices or styles are replicated—such as Stromae in this case—may have no legal claim over how those works are used.

The sophistication of AI-generated music has also become a growing concern for platforms and listeners. Research cited in the article by several streaming services found that 97% of listeners were unable to distinguish between AI-generated and human-made music, underscoring how convincing the technology has become.

Streaming platforms are already seeing a surge in AI-produced content. Tens of thousands of fully AI-generated tracks are uploaded daily, with Deezer alone receiving up to 20,000 new AI tracks per day—roughly 18% of all uploads to the platform.

Another worrisome aspect is that AI’s footprint in music is not limited to remixes or covers of existing songs only. Three albums credited to an "artist" named Sienna Rose, featuring jazz-infused soul tracks, have entered Spotify’s Viral Top 50 charts. The most popular song among them, a ballad titled Into the Blue, has surpassed five million plays. Despite their popularity and the presence of a female singing voice, a BBC article notes that it remains unclear whether Sienna Rose is a real human.

Deezer, which has developed tools to identify and manage AI-generated music, told the BBC that “many of her albums and songs on the platform are detected and flagged” as computer-generated.

Between 28 September and 5 December, the artist uploaded at least 45 tracks to streaming services—an unusually high output by industry standards. Her now-deactivated Instagram account reportedly displayed a series of nearly identical headshots, marked by the soft, unreal lighting commonly associated with AI image generators.

Listeners and experts have pointed to technical clues as well. According to the BBC, many fans have identified so-called “AI artefacts,” including a faint hiss running throughout the tracks. That trait is commonly found in music generated by apps such as Suno and Udio, which begin with white noise and gradually refine it into musical form. An expert told the outlet that these features can function as a fingerprint for AI-generated music and can be detected through mathematical analysis.

For casual listeners, subtler indicators may include inconsistent drum patterns, generic lyrics, and a vocalist who never deviates from the melody or delivers an emotionally explosive final chorus.

By Nazrin Sadigova