AI beauty: algorithms now decide who is beautiful?

It seems AI has decided to meddle in the most subjective field of all: beauty. New tools are trying to quantify what makes a face attractive, with results that are sparking debate. But do we really want software telling us if we measure up?

Not exactly, but it's trying quite persistently. Artificial intelligence attempts to define beauty by analyzing millions of images, learning to recognize patterns and specific features that, according to its dataset, are associated with attractiveness. It's a bit like teaching a child to distinguish colors by showing them many photos, only here we're talking about noses, eyes, and symmetry.

Alice Lassman of Bloomberg explored the implications of these new AI beauty tools in her report on September 17, 2026. Once trained, algorithms can assign a "beauty score" to any face, based on parameters a human could hardly quantify with such precision. It's fascinating, sure, but also a bit cold as an approach.

The biggest risk is standardizing beauty, flattening it into a few predefined canons. If AI learns from datasets that reflect certain cultural or ethnic biases, it will end up considering "beautiful" only what falls within those parameters. Goodbye diversity, hello forced homogenization by a code.

According to experts, the use of undiversified datasets can lead algorithms to favor specific aesthetic standards, implicitly discriminating against others. This could have a devastating impact on people's self-esteem, pushing them to conform to an artificial standard. Do we really want to entrust our self-perception to software, no matter how "intelligent"?