AI generator reveals what a 'beautiful woman' is across 100 countries

Beauty is in the ‘AI’ of the beholder: Stunning computer-generated images reveal what the stereotype of a ‘beautiful woman’ looks like in 100 countries around the world

  • Beauty is often believed to be in the eye of the beholder – but is that really true?
  • An AI generator has now revealed what it considers to be a ‘beautiful woman’
  • The program was issued a series of prompts before producing a stunning gallery

Beauty is often believed to be in the eye of the beholder.

But an AI generator has now revealed what it considers to be a stereotypical ‘beautiful woman’ across 100 different countries.

Experts at Style Seat issued a series of prompts to a program titled Midjourney before it produced the stunning gallery of images.

Scroll down to see the pictures in full – and the results might surprise you.

An AI generator has now revealed what it considers to be a stereotypical ‘beautiful woman’ across 100 different countries. Pictured: The result for the United States


There were a number of recurring themes running throughout the images but the program also captured the ‘intricate nuances of various cultures.’ Pictured: The results for China (left) and Egypt (right)

The AI generator was given a series of criteria in order to create the mesmerizing gallery.

It was asked to provide ‘photorealistic full-length portrait photos’ which had the subject facing the camera and against a white backdrop.

The list of 100 countries, including the United States, Canada, China India and the UK, was then inputted.

The finished project, which reflects the patterns that AI has identified in existing data available online, revealed a ‘striking uniformity.’ 

There were a number of recurring themes running throughout the images but the program also captured the ‘intricate nuances of various cultures.’

Acknowledging these similarities, Style Seat wrote: ‘AI consistently produced images of women who appear relatively thin and “put together,” though it also managed to incorporate a degree of diversity, predominately in terms of race and cultural clothing, into their overall appearances.

‘Interestingly, most of the generated women appear with minimal or natural makeup, suggesting that AI does not strictly associate beauty with heavy cosmetics. 

‘Additionally, many of the images depict women wearing pants instead of dresses or skirts, challenging traditional gender norms and indicating that AI is programmed to recognize a variety of attire as equally beautiful.’

Style Seat wrote how the project ‘managed to incorporate a degree of diversity, predominately in terms of race and cultural clothing, into their overall appearances.’ Pictured: The results for Burkina Faso

But it is not the first time that AI has been used to create images of ‘beautiful women.’ 

Earlier this year, clothing brand Levi Strauss & Co unveiled that it would be taking a futuristic approach when displaying its line of jeans.

The company said it would be using models generated by artificial intelligence to show off its clothing and claimed that consumers may not be able to tell the difference. 

Set to launch later this year, the initiative will present AI models in different body types, skin colors ang ages, allowing customers to see how products might look on them.

The San Francisco-based company previously said: ‘AI will likely never fully replace human models’ for the company, but offering a range of digital models will create ‘a more personal and inclusive shopping experience.’ 

The AI-generated gallery of ‘beautiful women’ from across the globe 



Pictured (left to right): Algeria, Angola, Argentina



Pictured (left to right): Australia, Austria, Bangladesh 



Pictured (left to right): Belgium, Benin, Bolivia



Pictured (left to right): Brazil, Burkina Faso, Burundi



Pictured (left to right): Cambodia, Cameroon, Canada



Pictured (left to right): Chad, Chile, China



Pictured (left to right): Colombia, Congo, Côte d’Ivoire



Pictured (left to right): Cuba, Czech Republic, Denmark



Pictured (left to right): Dominican Republic, Ecuador, Egypt



Pictured (left to right): Ethiopia, Finland, France



Pictured (left to right): Germany, Ghana, Greece



Pictured (left to right): Guatemala, Guinea, Haiti



Pictured (left to right): Honduras, Hong Kong, Hungary



Pictured (left to right): India, Indonesia, Iran



Pictured (left to right): Iraq, Israel, Italy



Pictured (left to right): Japan, Kazakhstan, Kenya



Pictured (left to right): Madagascar, Malawi, Malaysia



Pictured (left to right): Mali, Mexico, Morocco



Pictured (left to right): Mozambique, Myanmar, Nepal



Pictured (left to right): Netherlands, Niger, Nigeria



Pictured (left to right): North Korea, Norway, Pakistan



Pictured (left to right): Peru, Philippines, Poland



Pictured (left to right): Portugal, Romania, Russia



Pictured (left to right): Rwanda, Saudi Arabia, Senegal



Pictured (left to right): Sierra Leone, Singapore, Somalia



Pictured (left to right): South Africa, South Korea, South Sudan



Pictured (left to right): Spain, Sri Lanka, Sudan



Pictured (left to right): Sweden, Switzerland, Syria



Pictured (left to right): Taiwan, Tanzania, Thailand



Pictured (left to right): Togo, Turkey, Uganda



Pictured (left to right): Ukraine, United Arab Emirates, United Kingdom



Pictured (left to right): United States, Uzbekistan, Venezuela


Pictured: Vietnam (left) and Yemen (right)


Pictured: Zambia (left) and Zimbabwe (right)

Source: Read Full Article