{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T15:33:29Z","timestamp":1776094409103,"version":"3.50.1"},"reference-count":145,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MAKE"],"abstract":"<jats:p>Automatic Face Emotion Recognition (FER) technologies have become widespread in various applications, including surveillance, human\u2013computer interaction, and health care. However, these systems are built on the basis of controversial psychological models that claim facial expressions are universally linked to specific emotions\u2014a concept often referred to as the \u201cuniversality hypothesis\u201d. Recent research highlights significant variability in how emotions are expressed and perceived across different cultures and contexts. This paper identifies a gap in evaluating the reliability and ethical implications of these systems, given their potential biases and privacy concerns. Here, we report a comprehensive review of the current debates surrounding FER, with a focus on cultural and social biases, the ethical implications of their application, and their technical reliability. Moreover, we propose a classification that organizes these perspectives into a three-part taxonomy. Key findings show that FER systems are built with limited datasets with potential annotation biases, in addition to lacking cultural context and exhibiting significant unreliability, with misclassification rates influenced by race and background. In some cases, the systems\u2019 errors lead to significant ethical concerns, particularly in sensitive settings such as law enforcement and surveillance. This study calls for more rigorous evaluation frameworks and regulatory oversight, ensuring that the deployment of FER systems does not infringe on individual rights or perpetuate biases.<\/jats:p>","DOI":"10.3390\/make6040109","type":"journal-article","created":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T08:09:52Z","timestamp":1727683792000},"page":"2201-2231","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Not in My Face: Challenges and Ethical Considerations in Automatic Face Emotion Recognition Technology"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1420-9946","authenticated-orcid":false,"given":"Martina","family":"Mattioli","sequence":"first","affiliation":[{"name":"Department of Environmental Sciences, Informatics and Statistics, Ca\u2019 Foscari University, 30172 Venice, Italy"},{"name":"Department of Control and Computer Engineering, Polytechnic University of Turin, 10138 Turin, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4065-3415","authenticated-orcid":false,"given":"Federico","family":"Cabitza","sequence":"additional","affiliation":[{"name":"Department of Informatics, Systems and Communication, University of Milano-Bicocca, 20126 Milan, Italy"},{"name":"IRCCS Ospedale Galeazzi-Sant\u2019Ambrogio, 20157 Milan, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1037\/a0036052","article-title":"Perceptions of emotion from facial expressions are not culturally universal: Evidence from a remote culture","volume":"14","author":"Gendron","year":"2014","journal-title":"Emotion"},{"key":"ref_2","unstructured":"Barrett, L.F. 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