Psychometrics, profiles and bias: The case for facial recognition
Psychometric studies allow measurements based on vector correlations that produce predictions of human behavioral traits. With increasing digitization, psychometrics has been used to design profiles of individuals through various mechanisms: Big Data, Machine Learning, among others. Far from being n...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | Uruguay |
| Institución: | Universidad ORT Uruguay |
| Repositorio: | RAD |
| Idioma: | español |
| OAI Identifier: | oai:rad.ort.edu.uy:20.500.11968/4326 |
| Acceso en línea: | https://revistas.ort.edu.uy/inmediaciones-de-la-comunicacion/article/view/3156 https://hdl.handle.net/20.500.11968/4326 http://hdl.handle.net/20.500.11968/4326 |
| Access Level: | acceso abierto |
| Palabra clave: | psychometrics profile-dividum facial recognition bias psicometría perfil-dividuo reconocimiento facial sesgos psicometria reconhecimento facial vieses |
| Sumario: | Psychometric studies allow measurements based on vector correlations that produce predictions of human behavioral traits. With increasing digitization, psychometrics has been used to design profiles of individuals through various mechanisms: Big Data, Machine Learning, among others. Far from being neutral, these profiles are based on methodologies which produce biases that affect the profiled individuals. This article proposes that psychometrics elaborates a dividual-profile that generates a reduction of individuals and produces forms that augur the way in which they should behave. Here the conjecture is exemplified from the analysis of a case of psychometric measurement based on facial recognition. |
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