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Artificial intelligence algorithms offer marketers an insight to understand consumer behavior. Algorithms that follow the clicks of the consumer and create content based on their past likes offer efficiency and profitability advantages to businesses. Also consumers can focus on offers they may like. On the other hand, the consumer, monitored by the algorithms, connects to a single brand over time, always buys products from same retailers, is forced to buy similar products, is unable to see alternative products and service offers and choose more advantageous one for him. This situation is described by the concept of "filter bubble". According to Pariser, who named the concept, the situation which is called the "filter bubble effect", affects the society negatively by causing the polarization of ideas. In this review, which aims to provide a framework for future research efforts, the process from big data to the formation of personalization algorithms and the effect of creating a filter bubble in the consumer's mind are evaluated from a conceptual point of view with the approaches of different researchers. The subject is examined from the perspective of consumer psychology and ethics, and some examples are given. As a result, in order to avoid the influence of artificial intelligence, it is pointed out that it is possible for the consumer to avoid digital manipulation by having technology knowledge; it is necessary to spend more time learning the language of algorithms as much as possible, questioning their suggestions, and reaching the right information. In addition, it is also emphasized that digital marketing applications should include mutually beneficial surveillance and that the use of data should not lead to insecurity. [ABSTRACT FROM AUTHOR]

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