Алгоритмическая селекция общества: таргетинговые фильтры и новые грани социальной стратификации

Algorithmic Selection of Society: Targeting Filters and New Dimensions of Social Stratification

Algorithmic stratification of the information space creates new forms of social inequality based on access to relevant information. Targeting contributes to the isolation of users from alternative viewpoints of view, intensifying social polarization. Despite the risks of increased discrimination, targeting technologies have the potential to overcome inequality provided that their development is consciously managed for the benefit of society as a whole. The article demonstrates methodological foundations of research for targeting technologies in social science. The article shows the impact of algorithmic targeting on the formation of socially disoriented groups, including the breakdown of traditional ties, manipulative influences, and systemic exclusion from the target audience. The approaches to minimizing the negative consequences of targeting, including training algorithms on representative data, designing platforms in accordance with accessibility principles, and using digital stratification to identify and eliminate systemic imbalances.