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Tracking Historical Changes in Trustworthiness Using Machine Learning Analyses of Facial Cues in Paintings

L. Safra, C. Chevallier, J. Grèzes & N. Baumard

November 11, 2020

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Social trust is linked to positive societal outcomes, (eg economics, less crime & inclusivity) but is difficult to document. Machine learning algorithm analyses of portrait facial cues documents trustworthiness increased (1500–2000) paralleling the decline of violence & the rise of democratic values.
#RelationalSpace #Science #Algorithm #Democracy

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Artists and scientists alike are focused on exploring the world through introspection, examination and experimentation. Collaboration provides multiple perspectives and methodologies leading to novel dialogue and expression. Combining scientific exploration with creative expression offers unique opportunities for forming new knowledge and creativity. To tackle the intractable challenges of our society requires a language of cross-disciplinarity interconnectedness. Relational Space provides a space for artistic expression and knowledge exchange focused on art in relation to knowledge able to promote transformational learning and a brighter future. Relational Space encourages communication and collaboration among artists, scientists, policy-makers and the community-at-large.  Our vision sees a more just and sustainable world, inspired by art and transformed through truth. 

 

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