Beauty.AI

International AI-judged beauty contest with selfie entries and a Robot Jury
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Beauty.AI is an international beauty contest where the winners are selected by artificial intelligence rather than a traditional human panel. Participants submit selfies through the Beauty.AI app, and a “Robot Jury” evaluates the photos using algorithms created by data scientists from around the world. These algorithms analyze facial and skin-related attributes such as wrinkles, facial symmetry, skin tone, and other demographic-related factors (including gender, age group, and ethnicity) to produce rankings and results.

Beauty.AI 1.0 and 2.0 were designed as experiments in how machines perceive human faces and how measurable signals from selfies can be used to score beauty and indicators often associated with health. In addition to the competition element, the project acts as a testing ground for computer vision models, helping researchers and developers understand how AI systems make aesthetic judgments—and where they may fail or show bias when confronted with diverse faces across regions and populations.

The platform has two main participant paths. Human contestants enter by uploading selfies that meet the contest rules through the mobile app. “Robots,” meaning teams of data scientists and developers, participate by submitting their scoring algorithms to the Robot Jury. The jury then applies those algorithms to the submitted images and produces the contest results. more

Review Summary

Features

  • AI-judged international beauty contests (Beauty.AI 1.0 and 2.0)
  • Selfie submission via mobile app for human participants
  • Robot Jury that evaluates entries using submitted algorithms
  • Algorithm submission track for data scientists and developers
  • Automated scoring based on facial/skin parameters (e.g., wrinkles, symmetry, skin tone) and demographic groupings

How It’s Used

  • Enter a beauty contest evaluated by AI using a selfie
  • Develop and submit computer vision algorithms for facial scoring
  • Study how AI models interpret beauty and health-related signals
  • Explore strengths, limitations, and bias risks in face analysis systems

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