@article{db2462a1bd9340d893eb16e2f455f6e8,
title = "Errors, biases and overconfidence in artificial emotional modeling",
abstract = "With the diffusion and successful new implementation of several machine learning techniques, together with the substantial cost decrease of sensors, also included in mobile devices, the field of emotional analysis and modeling has boosted. Apps, web apps, brain-scanning devices, and Artificial Intelligence assistants often include emotion recognition features or emotional behaviors, but new researches contain, maintain, or create several design errors, which analysis is the main aim of this paper.",
keywords = "Affective computing, Emotion, Errors, Gendered, HRI, Overconfidence",
author = "Jordi Vallverd{\`u} and Valentina Franzoni and Alfredo Milani",
note = "Funding Information: Prof. Vallverd?'s work contributions have been funded by: a) the Ministry of Science, Innovation and Universities within the State Subprogram of Knowledge Generation through the research project FFI2017-85711-P Epistemic innovation: the case of cognitive sciences; b) the consolidated research network {"}Grup d'Estudis Human?stics de Ci?ncia i Tecnologia{"} (GEHUCT) ({"}Humanistic Studies of Science and Technology Research Group{"}), recognized and funded by the Generalitat de Catalunya, reference 2017 SGR 568. Dr. Franzoni's work is partially funded by the research project DDG n.123 5/16/2018 Models and Systems for e-learning process monitoring and integration of the University of Perugia. Publisher Copyright: {\textcopyright} 2019 Copyright held by the owner/author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2019",
month = oct,
day = "14",
doi = "10.1145/3358695.3361749",
language = "Ingl{\'e}s estadounidense",
pages = "86--90",
}