Blue Noise
Two Channel audio, video, Spectrograms
In these video spectrograms, I decode a collective experience of 'Blue'. One spectrogram uses the neural network generated interpretations of 'Blue', this neural network is fed all the data that currently exists on the internet, hence these interpretation are a multitude of experiences of blue, while the other spectrogram uses general public responses, from a public that is analogue, so AI couldn't possibly access their interpretations of blue. Their interpretations are not fact based, but more context/emotion based. I am focusing on the voice of the collective intelligence in relation to the synthesized voice of an artificial intelligence. These voices carry information, as human voices are not static- they shift and change, and reveal context, while the machine generated voice is full of audible knowledge, yet feels static.