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Analyzing Demographic Bias in Artificially Generated Facial Pictures

Artificial generation of facial images is increasingly popular, with machine learning achieving photo-realistic results.

Yet, there is a concern that the generated images might not fairly represent all demographic groups. This has implications for persona development when approaching the goal of generating the facial pictures for the persona profiles automatically.

Analyzing Demographic Bias in Artificially Generated Facial Pictures
Analyzing Demographic Bias in Artificially Generated Facial Pictures

In research led by Joni Salminen, we use a state-of-the-art method to generate 10,000 facial images and observe that the generated images are skewed towards young people, especially white women.

We provide recommendations to reduce demographic bias in artificial images.

Read Full Research

Salminen, J., Jung, S.G., Chowdhury. S., and Jansen, B. J. (2020) Analyzing Demographic Bias in Artificially Generated Facial Pictures. ACM CHI Conference on Human Factors in Computing Systems (CHI’20) (Extended Abstract), Honolulu, HI, USA. 25–30 April, 1-8.

By Jim Jansen

Dr. Jansen is a Principal Scientist in the social computing group of the Qatar Computing Research Institute, and a professor with the College of Science and Engineering, Hamad bin Khalifa University, and an adjunct professor with the College of Information Sciences and Technology at The Pennsylvania State University. He is a graduate of West Point and has a Ph.D. in computer science from Texas A&M University, along with master degrees from Texas A&M (computer science) and Troy State (international relations). Dr. Jim Jansen served in the U.S. Army as an Infantry enlisted soldier and communication commissioned officer.

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