Algorithmic advertising in e-commerce: legal adaptation and civil liability (a comparative study)

Volume 17, Issue: 2 part 1
Summer 2026
Pages 641-672

Document Type : Research Paper

Author

Salahaddin University / College of Law / Department of Law

Abstract
This research examines civil liability for algorithmic advertising in e-commerce, reviewing the legal foundations in Iraqi civil law and comparative legislation. The research focuses on the parties responsible, including the advertiser, the digital platform, and the algorithm developer, highlighting the role of each party in causing harm. It also clarifies the elements of traditional civil liability—fault, tort, and causation—while acknowledging the unique characteristics of the digital environment, which is marked by technical complexity. The research addresses the types of harm resulting from algorithmic advertising and explores the practical challenges of proving fault and tort. It also identifies legislative gaps in Iraq and proposes the development of a legal framework specifically for algorithmic advertising to protect consumers. Finally, the research reviews comparative experiences in European and Emirati legislation, emphasizing the importance of balancing technological innovation with consumer rights protection.
To achieve its objectives, the research is divided into two main sections, each containing two subsections.

The first section examines the conceptual framework and legal nature of algorithmic advertising within the context of e-commerce. The first subsection addresses the concept of algorithmic advertising, outlining its characteristics and distinguishing it from traditional online advertising. The second subsection explores the legal nature of this advertising model and its place within the e-commerce system.

The second section focuses on civil liability arising from algorithmic advertising. The first subsection examines the basis and parties to civil liability, while the second subsection explores the elements of civil liability: fault, damage, and causation. The research concludes

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  • Receive Date 20 April 2026
  • Accept Date 30 April 2026