Digital advertising has become increasingly pervasive across platforms such as social media, search engines, and conversational AI systems. This critical review synthesizes political microtargeting, algorithmic persuasion, ad avoidance, dark patterns, acceptable advertising, AI-generated media labeling, offensive ads, and the risks posed by conversational search advertising. The reviewed studies highlight evolving advertising tactics that intensify personalization, manipulate user choice architectures, and challenge user autonomy often generating cognitive fatigue, resistance behaviors, and potential negative well-being outcomes. While the reviewed literature contributes empirical evidence on ad attention, avoidance patterns, and transparency interventions, it also exposes gaps in causal inference, generalizability, ecological validity, and measurement of psychological harms such as anxiety. This paper offers research, policy, and platform-level recommendations, emphasizing stronger disclosure frameworks, friction-based consumer protections, ethical design guidelines, and future research directions focusing on longitudinal well-being impacts.
Patel et al. (Thu,) studied this question.
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