The Personalization Trap: How User Memory Alters Emotional Reasoning in LLMs

Scientists have found that AI assistants storing personal details can alter their emotional interpretation. When a user profile changed from a low-income parent to a wealthy executive, the AI's emotional advice significantly shifted. Memory-enhanced AI systems tended to provide more accurate and supportive responses to advantaged profiles. This bias unintentionally mirrors real-world social hierarchies. The personalization feature, designed for empathy, might instead exacerbate inequality. This creates a "personalization trap" where AI's understanding is influenced by perceived socioeconomic status. The study highlights the need for AI to remember users fairly, not just favorably. This is crucial as AI becomes more integrated into daily life. The implications suggest a need for careful design to avoid embedding societal biases. Users should be aware of this potential for skewed responses in personalized chatbots.