Làn sóng âm nhạc A.I và cuộc chiến bản quyền trên không gian số | Góc nhìn văn hóa | VTV24

Key Concepts

• AI Music Generation: The use of algorithms to create melodies, lyrics, and vocal tracks.
• AI Voice Cloning: Technology that replicates a human singer's voice with up to 99% accuracy.
• Copyright/Intellectual Property (IP): Legal challenges regarding ownership, "derivative works," and the unauthorized use of artists' voices/data.
• Human-AI Symbiosis: The perspective of using AI as a tool (an "intern") rather than a replacement for human creativity.
• Legal "Gray Zone": The lack of clear regulations regarding AI-generated content and the protection of human artistic identity.

1. Main Topics and Key Points

• The Rise of AI in Music: AI is increasingly used for demo production, orchestration, and full song generation. Platforms like Suno have gained over 100 million users in two years.
• Technical Precision: AI can now mimic human voices so accurately that 97% of global listeners cannot distinguish between AI-generated music and human performances.
• Market Impact: AI-generated tracks (e.g., "Hôn lễ của em" with 11.9 million streams) are gaining massive traction, challenging traditional production models.
• The "Soul" Argument: Artists argue that while AI can master technical aspects (pitch, rhythm), it lacks the "soul" and life experience that define true art.

2. Real-World Applications and Case Studies

• Suno: A platform that allows users without musical training to generate songs via text prompts.
• Solomon Ray: A virtual character created by Christopher Tsen using AI, which successfully charted on Billboard 12 times.
• Collaborative Experiments: The first performance featuring a human artist (MTV band) alongside an AI singer (An) in Vietnam, signaling a shift toward human-AI cooperation.
• Experimental Tech: Innovations like robotic haptic feedback for musicians and "tasting music" (sensory cross-over) showcased at CES 2026.

3. Methodologies and Frameworks

• AI Production Process: AI uses probabilistic algorithms based on massive datasets of existing human works to "predict" and generate music.
• The "Framework" Approach: Some artists use AI to build the "skeleton" or "foundation" of a song, while reserving the "spirit" and creative direction for human input.
• Integration Strategy: Instead of resisting, some professionals treat AI as a "super-intern" to streamline workflows and enhance productivity.

4. Key Arguments and Perspectives

• The "Replacement" Fear: Many artists worry about being replaced by an "untiring competitor" that can produce music faster and cheaper.
• The "Tool" Perspective: Proponents argue that AI forces human artists to dig deeper into their own emotions and unique stories to remain relevant.
• Ethical/Legal Concerns: Critics, such as singer T-Merit, argue that AI models "exploit" human intellectual property without consent or compensation, effectively using artists' work to replace them.

5. Notable Quotes

• "AI can make music very fast and attractive, but music needs not only catchy melodies but also emotions, experiences, and human creative imprints." (General consensus from interviewed artists).
• "AI is like a super-intern. You don't have to just stand there and sing; learn to integrate it into your workflow so you aren't left behind." (Christopher Tsen).
• "Our assets are being consumed to then replace us." (T-Merit, regarding the lack of transparency in AI training data).

6. Legal and Ethical Challenges

• Copyright Infringement: AI-generated music often uses existing copyrighted works, leading to "derivative works" that lack legal authorization.
• Right of Publicity: Cloning a famous singer's voice violates the rights of the performer and the record producer.
• Registration Barriers: Copyright offices (including in Vietnam) generally refuse to register works created purely by AI because they lack "human intellectual labor."

7. Synthesis and Conclusion

The integration of AI into music is an irreversible trend. While it poses significant threats to traditional copyright and the livelihoods of artists, it also offers a new frontier for creativity. The consensus is that AI should not be banned but rather regulated through clear ethical and legal boundaries. The future of music lies in a "symbiotic" relationship where AI handles technical efficiency, while humans provide the emotional depth and creative vision that machines cannot replicate. Success in this new era depends on how society balances technological advancement with the protection of human artistic identity.