AGE DISCRIMINATION IN BIG DATA ANALYSIS: THE CASE OF AGE-PREDICTIVE SYSTEMS
A. Rosales, Mireia Fernández-Ardèvol · Innovation in Aging · 2017
Digital communication systems opened the door for tracking everyday activities. Terabytes of data created by real life users in their daily activities on digital devices. Big data are used among others, to understand human behavior and to model statically to predict human behavior. However, big data analyses are limited by assumptions, values, and biases. Concretely, older people often constitute a minority group in digital media, both in terms of the number of users and in terms of activities. Also, tracked data often do not have demographic information, do not include older people, or do not make a generational analysis. Thus presumably, big data analysis provide conclusions and influence decisions without taking into account the nuances related to older people, their particular interests and habits leading to structural discrimination. The paper analyzes this topic within the area of intelligent systems to predict the age of users in social network sites.