<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Digital systems can track every activity. Their logs are the fundamental raw material of intelligent systems in big data approaches. However, big data approaches mainly use predictions and correlations that often fail in the prediction of minorities or invisibilize collectives, causing discriminatory decisions. While this discrimination has been documented regarding, sex, race and sexual orientation, age has received less attention. A critical review of the academic literature confirms that structural ageism also shapes big data approaches. The article identifies some instances in which ageism is in operation either implicitly or explicitly. Concretely, biased samples and biased tools tend to exclude the habits, interests and values of older people from algorithms and studies, which contributes to reinforcing structural ageism.</p>
</abstract>

Digital systems can track every activity. Their logs are the fundamental raw material of intelligent systems in big data approaches. However, big data approaches mainly use predictions and correlations that often fail in the prediction of minorities or invisibilize collectives, causing discriminatory decisions. While this discrimination has been documented regarding, sex, race and sexual orientation, age has received less attention. A critical review of the academic literature confirms that structural ageism also shapes big data approaches. The article identifies some instances in which ageism is in operation either implicitly or explicitly. Concretely, biased samples and biased tools tend to exclude the habits, interests and values of older people from algorithms and studies, which contributes to reinforcing structural ageism.

Structural Ageism in Big Data Approaches

Internet Interdisciplinary Institute (IN3)

Nordicom Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Structural Ageism in Big Data Approaches"}

Digital systems can track every activity. Their logs are the fundamental raw material of intelligent systems in big data approaches. However, big data...

Structural Ageism in Big Data Approaches

Publié en ligne: 28 juin 2019

Pages: 51 - 64

DOI: https://doi.org/10.2478/nor-2019-0013

Mots clés
ageism, discrimination, big data, intelligent systems, literature review

© 2019 Andrea Rosales et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Structural Ageism in Big Data Approaches

Publié en ligne: 28 juin 2019

Pages: 51 - 64

DOI: https://doi.org/10.2478/nor-2019-0013

Mots clésageism, discrimination, big data, intelligent systems, literature review

© 2019 Andrea Rosales et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
ageism, discrimination, big data, intelligent systems, literature review