Guide / Field notes
Grid-Tight Timing Does Not Prove AI Authorship
Quantisation predates generative music by decades.
Perfect timing is an old studio result
Drum machines, MIDI sequencing, editing and groove templates routinely place events on a grid. A precise performance may be programmed or corrected without being generative.
What timing can support
Tempo estimates help align sections; onset deviation can show how tightly events follow a chosen grid; drift can distinguish a free performance from a fixed clock. These are production observations.
Frequent interpretation errors
Half-time and double-time estimates can describe the same pulse. Dense mixes confuse onset detection, and electronic genres create expected false alarms. Verify with listening and musical context.
Key takeaway
The short version
A timing grid can describe sequencing and correction, but not whether a generative model authored the music.
Run a free detectionFrequently asked questions
No. It can support a review, but origin and authorship require provenance and context. Do not use one automated or acoustic observation as proof.
Keep reading
Guide
How to Check a Song for AI: An Evidence-Led Workflow
A step-by-step method combining ears, measurements and provenance — in the order that actually works.
Comparison
Suno or Udio? Why the Production Workflow Matters More
Same goal, different machinery — and different tells left behind in the audio.
Industry
Does Spotify Detect AI Music? Separate Policy from Audio Analysis
Moderation, fraud checks and disclosure rules — a different job from acoustic detection.
Legal
AI Music Copyright: A Map of Clear and Unsettled Questions
Authorship, training data and voice likeness, sorted into settled and unresolved.