Nudge Versus Sludge: Classifying Ai-driven Ad-personalization Techniques on a Manipulation–transparency Spectrum

MANILAKSHMI S; Vethirajan C

Nudge Versus Sludge: Classifying Ai-driven Ad-personalization Techniques on a Manipulation–transparency Spectrum

Author(s)	Ms. MANILAKSHMI S, Dr. Vethirajan C
Country	India
Abstract	The rapid proliferation of generative and predictive artificial intelligence (AI) in digital advertising has sparked fears that personalization, once touted as a consumer benefit, has become a tool of manipulation. Behavioral economics provides a ready-made distinction between a nudge choice architecture that steers behavior while preserving autonomy and a sludge friction or influence that steers behavior against a person’s interest. This paper argues that the distinction, conceived for public policy and consumer protection, has not yet been operationalized for AI-driven ad-personalization techniques. Drawing on the nudge/sludge literature, dark-pattern taxonomies, online-manipulation theory, and recent empirical work on AI ad disclosure, the paper develops a conceptual classification framework, the Manipulation–Transparency Spectrum, that positions specific AI personalization techniques dynamic creative optimization, algorithmic emotion-targeting, AI-generated scarcity claims, synthetic testimonials, conversational upselling, and personalized consent design along five operational dimensions: disclosure of AI logic, reversibility of influence, exploitation of cognitive bias, symmetry of data-consent design, and alignment of beneficiary interest. The paper develops eight theoretical propositions linking spectrum position with consumer trust and perceived manipulation and regulatory exposure. The paper discusses the implications for the design of AI ad-transparency tools, platform governance and disclosure regulation within the framework of frameworks such as the transparency obligations in Article 50 of the EU AI Act and India’s Digital Personal Data Protection Act, 2023. The paper concludes with a research agenda for empirically validating and extending the framework.
Keywords	AI-driven advertising, ad transparency, consumer manipulation, nudge, sludge, dark patterns, algorithmic disclosure, consumer trust
Field	Business Administration
Published In	Volume 8, Issue 5, September-October 2026
Published On	2026-09-16

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Nudge Versus Sludge: Classifying Ai-driven Ad-personalization Techniques on a Manipulation–transparency Spectrum

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