As AI becomes embedded in everyday creative workflows, the risk isn’t just bias - it’s how bias, at scale, quietly erodes human authenticity and cultural specificity.
From the data that trains our tools to the creative outputs we produce at speed, AI systems reflect the biases embedded in their inputs and defaults. These biases shape which voices, faces, and stories are amplified - and which are smoothed, generalised, or erased altogether.