%0 Journal Article %T Modeling, Recognizing, and Explaining Apparent Personality from Videos %A Hugo Jair Escalante %A Heysem Kaya %A Albert Ali Salah %A Sergio Escalera %A Yagmur Gucluturk %A Umut Guçlu %A Xavier Baro %A Isabelle Guyon %A Julio C. S. Jacques Junior %A Meysam Madadi %A Stephane Ayache %A Evelyne Viegas %A Furkan Gurpinar %A Achmadnoer Sukma Wicaksana %A Cynthia Liem %A Marcel A. J. Van Gerven %A Rob Van Lier %J IEEE Transactions on Affective Computing %D 2022 %V 13 %N 2 %F Hugo Jair Escalante2022 %O HuPBA; no menciona %O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3406), last updated on Tue, 25 Apr 2023 15:32:03 +0200 %X Explainability and interpretability are two critical aspects of decision support systems. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an introduction to explainability and interpretability in the context of apparent personality recognition. To the best of our knowledge, this is the first effort in this direction. We describe a challenge we organized on explainability in first impressions analysis from video. We analyze in detail the newly introduced data set, evaluation protocol, proposed solutions and summarize the results of the challenge. We investigate the issue of bias in detail. Finally, derived from our study, we outline research opportunities that we foresee will be relevant in this area in the near future. %U https://ieeexplore.ieee.org/abstract/document/8999746 %U http://refbase.cvc.uab.es/files/EKS2020.pdf %U http://dx.doi.org/10.1109/TAFFC.2020.2973984 %P 894-911