Level of Agreement between Emotions Generated by Artificial Intelligence and Human Evaluation: A Methodological Proposal

Images are capable of conveying emotions, but emotional experience is highly subjective. Advances in artificial intelligence have enabled the generation of images based on emotional descriptions. However, the level of agreement between the generative images and human emotional responses has not yet been evaluated. In order to address this, 20 artistic landscapes were generated using StyleGAN2-ADA. Four variants evoking positive emotions (contentment and amusement) and negative emotions (fear and sadness) were created for each image, resulting in 80 pictures. An online questionnaire was designed using this material, in which 61 observers classified the generated images. Statistical analyses were performed on the collected data to determine the level of agreement among participants between the observers’ responses and the generated emotions by AI. A generally good level of agreement was found, with better results for negative emotions. However, the study confirms the subjectivity inherent in emotional evaluation.

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Publication Details

Journal
Electronics
Published
2024-10-12
DOI
https://doi.org/10.3390/electronics13204014
Citations
4
Primary Topic
Technology and Human Factors in Education and Health
Type
article
Field-Weighted Citation Impact
2.17
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article

Level of Agreement between Emotions Generated by Artificial Intelligence and Human Evaluation: A Methodological Proposal

César González-Martín, Miguel Carrasco, Sonia Navajas-Torrente, Raúl Dastres
4 citations
Electronics
Technology and Human Factors in Education and Health
2.17
article

Level of Agreement between Emotions Generated by Artificial Intelligence and Human Evaluation: A Methodological Proposal

César González-Martín, Miguel Carrasco, Sonia Navajas-Torrente, Raúl Dastres
article en
4 citations

Abstract

Images are capable of conveying emotions, but emotional experience is highly subjective. Advances in artificial intelligence have enabled the generation of images based on emotional descriptions. However, the level of agreement between the generative images and human emotional responses has not yet been evaluated. In order to address this, 20 artistic landscapes were generated using StyleGAN2-ADA. Four variants evoking positive emotions (contentment and amusement) and negative emotions (fear and sadness) were created for each image, resulting in 80 pictures. An online questionnaire was designed using this material, in which 61 observers classified the generated images. Statistical analyses were performed on the collected data to determine the level of agreement among participants between the observers’ responses and the generated emotions by AI. A generally good level of agreement was found, with better results for negative emotions. However, the study confirms the subjectivity inherent in emotional evaluation.

ElectronicsVol. 13(20)
Adolfo Ibáñez University (CL), University of Córdoba (ES)
Reduced inequalities
Openalex Percentile: Top 12%
Technology and Human Factors in Education and Health
2.17
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