Published June 24, 2021 | Version Accepted pre-print
Conference paper Open

`Expected most of the results, but some others...surprised me': Personality inference in Image Tagging Services

  • 1. Cyprus Center for Algorithmic Transparency, Open University of Cyprus
  • 2. Cyprus Center for Algorithmic Transparency, Open University of Cyprus and CYENS Centre of Excellence


Image tagging APIs, offered as Cognitive Services in the movement to democratize AI, have become popular in applications that need to provide a personalized user experience. Developers can easily incorporate these services into their applications; however, little is known concerning their behavior under specific circumstances. We consider how two such services behave when predicting elements of the Big-Five personality traits from users’ profile images. We found that personality traits are not equally represented in the APIs’ output tags, with tags focusing mostly on Extraversion. The inaccurate personality prediction and the lack of vocabulary for the equal representation of all personality traits, could result in unreliable implicit user modeling, resulting in sub-optimal – or even undesirable – user experience in the application.



This work has been partly supported by the project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 739578 (RISE – Call: H2020-WIDESPREAD-01-2016-2017-TeamingPhase2) and the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy.



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RISE – Research Center on Interactive Media, Smart System and Emerging Technologies 739578
European Commission