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Robert Klemmensen, black and white photo.

Robert Klemmensen

Assistant Head of Department (Coordination of Research) | Professor

Robert Klemmensen, black and white photo.

Using deep learning to predict ideology from facial photographs: expressions, beauty, and extra-facial information

Author

  • Stig HR Rasmussen
  • Steven Ludeke
  • Robert Klemmensen

Summary, in English

Deep learning techniques can use public data such as facial photographs to predict sensitive personal information, but little is known about what information contributes to the predictive success of these techniques. This lack of knowledge limits both the public’s ability to protect against revealing unintended information as well as the scientific utility of deep learning results. We combine convolutional neural networks, heat maps, facial expression coding, and classification of identifiable features such as masculinity and attractiveness in our study of political ideology in 3323 Danes. Predictive accuracy from the neural network was 61% in each gender. Model-predicted ideology correlated with aspects of both facial expressions (happiness vs neutrality) and morphology (specifically, attractiveness in females). Heat maps highlighted the informativeness of areas both on and off the face, pointing to methodological refinements and the need for future research to better understand the significance of certain facial areas.

Department/s

  • Department of Political Science
  • LU Profile Area: Natural and Artificial Cognition

Publishing year

2023-03-31

Language

English

Publication/Series

Scientific Reports

Volume

13

Issue

1

Document type

Journal article

Publisher

Nature Publishing Group

Topic

  • Political Science

Status

Published

ISBN/ISSN/Other

  • ISSN: 2045-2322