Mitigating bias in facial analysis systems by incorporating label diversity

They explored how subjective human-made labels and objective mathematical definitions of attractive face structures can help debias models that classify faces into patterns of beauty. For such a task they trained models using a novel learning technique and showed that by mathematically defining attractive structures they could debias face recognition and beauty classifier models.