Why AI keeps painting beautiful women: average faces and data inertia
This GeekPark analysis, syndicated by Huxiu and 36Kr, starts from a five-second AI-generated clip of a woman in the crowd at a Korean baseball broadcast that drew 15.25 million views on X, and asks why image models so often default to attractive women. Its explanation runs in three layers: generative models sample near the center of their training distribution and thus tend toward 'average' faces, which psychology research finds are rated more attractive; user clicks and aesthetic reward models such as PickScore then push models further in that direction. It also revisits the half-century use of the Lena test image (dropped by the IEEE Computer Society in 2024), Lensa's magic avatars, and Grok's Spicy mode.
It links gender bias in image generation to data distributions and commercial incentives, giving practitioners a clear account of where default outputs come from.