From Convenience to Caution: The Impact of AI Recommendations on privacy and User Trust

It investigates the benefits and challenges of AI recommendation systems, with particular attention to user trust, privacy, and algorithmic bias. By applying the UTAUT2 framework and analyzing user survey data, the study highlights the importance of transparency and ethical considerations in fostering user acceptance and improving system effectiveness.
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