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AI-Driven Media Influence on Consumer Behavior: Algorithmic Personalization, Trust, and Attention
Abstract
The present chapter considers how artificial intelligence (AI) uses algorithmic personalisation, trust mechanisms, and attention capture to influence consumer behaviour. It outlines the development of recommendation systems using AI such as deep learning and reinforcement learning, explaining how they personalise content and predict preferences to influence decisions. One of the observed changes in the AI approach occurs through rise of “thinking” with predict preferences and “feeling” with simulating empathy for uninterrupted conversations. It also defines “filter bubbles” for another impact of recommendation engines, search filters, and chatbots with their personalised experiences by predicted preferences, so that users could only face with similar and “relevant” options during their journey. Higher engagement could manipulate a user's preference through the given predictions and direct the user to complete a purchase even at higher prices.
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