AI researchers recently made a significant breakthrough in predicting hit songs by measuring how a listener's body responds to the music. Their study claims a near-perfect accuracy rate of 97%, which is much higher than previous methods that focused on artist, genre, lyrics, and tempo. Unlike traditional approaches that used brain scans, the researchers in this study collected cardiac data from wearable devices like Apple Watches or Fitbits and used it as a proxy for neural response. By utilizing a commercial platform called immersion neuroscience, they measured emotional resonance and attention based on heart rate and blood flow.

While some researchers express skepticism about using cardiac data as a proxy for brain activity, the study aims to provide a more accessible and cost-effective way of predicting hit songs compared to MRI scans. However, concerns about privacy arise as this technology might require users' consent to monitor their physiological responses. It remains uncertain whether the technology is ready for widespread implementation, as the study had a small sample size and lacked diversity in participants. Replication and validation with larger and more diverse samples are necessary to confirm the findings and ensure replicability across different cultural preferences in music.