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Societal Consequences of Data-Driven Advertising

In: Rethinking Advertising

Author

Listed:
  • Joanna Strycharz

    (University of Amsterdam)

  • Claire M. Segijn

    (University of Minnesota)

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.

Suggested Citation

  • Joanna Strycharz & Claire M. Segijn, 2025. "Societal Consequences of Data-Driven Advertising," Springer Books, in: Kathleen M. Vandenberg & Mariah Tinger (ed.), Rethinking Advertising, chapter 0, pages 17-30, Springer.
  • Handle: RePEc:spr:sprchp:978-3-031-86536-7_2
    DOI: 10.1007/978-3-031-86536-7_2
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