AI Detection Report: 2024 International Songwriting Competition: Evidence of undisclosed and undetected AI-generated songs receiving awards despite prohibition, undermining fair competition for songwriters
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| Natura: | Recurso digital |
| Lingua: | inglese |
| Pubblicazione: |
Zenodo
2026
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| _version_ | 1866902173652090880 |
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| author | Stanek, Joseph |
| author_facet | Stanek, Joseph |
| contents | <p>This report presents a forensic audit of award-winning entries in the 2024 International Songwriting Competition (ISC), documenting evidence of undisclosed and undetected AI-generated music receiving official recognition despite explicit prohibitions. The investigation integrates audio forensics, open-source intelligence (OSINT), metadata analysis, and publicly documented admissions by credited entrants to evaluate authorship credibility and workflow plausibility.</p> <p>Findings identify structural, stylistic, and behavioral patterns consistent with contemporary text-to-music generative AI systems rather than human songwriting processes. The revised print edition consolidates technical analyses, evidentiary figures, and procedural context to support independent verification, institutional review, and scholarly citation. This work contributes to ongoing discussions on AI detection, authorship integrity, and policy enforcement in creative competitions.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18725248 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AI Detection Report: 2024 International Songwriting Competition: Evidence of undisclosed and undetected AI-generated songs receiving awards despite prohibition, undermining fair competition for songwriters Stanek, Joseph AI-generated music music forensics authorship attribution songwriting competitions generative AI audio forensics metadata analysis OSINT creative integrity AI detection generative AI in music songwriting authenticity International Songwriting Competition music awards competition integrity SunoAI AI disclosure competition compliance copyright and AI spectrogram analysis waveform analysis judging systems creative competitions digital forensics forensic audio AI music detection music industry intellectual property competition policy generative AI ethics digital media <p>This report presents a forensic audit of award-winning entries in the 2024 International Songwriting Competition (ISC), documenting evidence of undisclosed and undetected AI-generated music receiving official recognition despite explicit prohibitions. The investigation integrates audio forensics, open-source intelligence (OSINT), metadata analysis, and publicly documented admissions by credited entrants to evaluate authorship credibility and workflow plausibility.</p> <p>Findings identify structural, stylistic, and behavioral patterns consistent with contemporary text-to-music generative AI systems rather than human songwriting processes. The revised print edition consolidates technical analyses, evidentiary figures, and procedural context to support independent verification, institutional review, and scholarly citation. This work contributes to ongoing discussions on AI detection, authorship integrity, and policy enforcement in creative competitions.</p> |
| title | AI Detection Report: 2024 International Songwriting Competition: Evidence of undisclosed and undetected AI-generated songs receiving awards despite prohibition, undermining fair competition for songwriters |
| topic | AI-generated music music forensics authorship attribution songwriting competitions generative AI audio forensics metadata analysis OSINT creative integrity AI detection generative AI in music songwriting authenticity International Songwriting Competition music awards competition integrity SunoAI AI disclosure competition compliance copyright and AI spectrogram analysis waveform analysis judging systems creative competitions digital forensics forensic audio AI music detection music industry intellectual property competition policy generative AI ethics digital media |
| url | https://doi.org/10.5281/zenodo.18725248 |