Emotion-based Stereotypes in Image Analysis Services
- 1. Research Centre on Interactive Media, Smart Systems & Emerging Technologies (RISE Ltd.), Nicosia, Cyprus
- 2. Open University of Cyprus, Nicosia, Cyprus
- 3. University of Cyprus, Nicosia, Cyprus
Description
Vision-based cognitive services (CogS) have become crucial in a wide range of applications, from real-time security and social networks to smartphone applications. Many services focus on analyzing people images. When it comes to facial analysis, these services can be misleading or even inaccurate, raising ethical concerns such as the amplification of social stereotypes. We analyzed popular Image Tagging CogS that infer emotion from a person’s face, considering whether they perpetuate racial and gender stereotypes concerning emotion. By comparing both CogS and Human-generated descriptions on a set of controlled images, we highlight the need for transparency and fairness in CogS. In particular, we document evidence that CogS may actually be more likely than crowdworkers to perpetuate the stereotype of the “angry black man" and often attribute black race individuals with “emotions of hostility".
Notes
Files
ACM_FairUMAP_2020___Stereotyping_in_Emotion_Image_Analysis_Services.pdf
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