Societal Consequences of Data-Driven Advertising

Joanna Strycharz () and Claire M. Segijn
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Joanna Strycharz: University of Amsterdam
Claire M. Segijn: University of Minnesota

Chapter Chapter 2 in Rethinking Advertising, 2025, pp 17-30 from Springer

Abstract: Abstract Advancements in machine learning and artificial intelligence have revolutionized the advertising industry, leading to the rise of computational advertising. This approach relies on the extensive collection and processing of consumer data to deliver individualized and targeted ads. While this data-driven strategy enhances the relevance of advertisements for consumers, it also fosters dataveillance, namely continuous and pervasive surveillance by among others advertisers. In this chapter, we explore the societal and individual implications of dataveillance in the context of computational advertising. We examine how data collection and processing for advertising affects consumer behavior, emotions, and cognition, often leading to negative surveillance responses. Additionally, we address the potential for exploitation and the creation of new disparities as advertisers leverage data to target vulnerabilities. The discussion reflects on the broader impact of computational advertising, highlighting both its potential for persuasion and its ethical considerations in the digital age.

Date: 2025
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DOI: 10.1007/978-3-031-86536-7_2

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