The memory of the smart assistants is no longer limited to saving the information that the user shares, but may expand beyond that to create a broader perception of his personality, behavior and way of thinking, which raises new questions about the limits of personalization and privacy. In this regard, a recent study revealed that the memory feature in ChatGPT may contribute to building a psychological and behavioral profile of the user based on the details of their daily conversations, even those that seem simple or unimportant at the moment. These results become even more important when considering the amount of information the system can extract from repeated interactions. The study included conversations of 80 users, and recorded more than 2,000 pieces of information stored in the memories of 65 of them, when it was found that 96% of these memories were created automatically by the system, without a direct request from the user. This suggests that memory not only performs the function of remembering, but may extend to analyzing usage patterns and inferring interests, dispositions, and some psychological and behavioral traits. The study also showed that some of the information saved included personal data, along with inferences beyond what the user directly stated. Hence a fundamental problem arises related to the difference between the information that the user shares explicitly, and that which the system infers from the context of conversations. A passing request or a question about a specific topic may become an indicator that the system relies on to make assumptions about the user's preferences, even though this assumption does not necessarily reflect reality. The sensitivity of this issue is that inaccurate inferences may over time become part of the picture that the system relies on to personalize its responses and guide its interactions with the user. On the other hand, the practical benefits of memory cannot be ignored, especially for users who rely on the smart assistant on a regular basis. Maintaining the context and previous preferences saves time, reduces the need to repeat information, and makes the experience more efficient and tailored to individual needs. But as the ability of these systems to understand and adapt to the user increases, so does the scope of questions regarding the limits of information collection and analysis, the degree of clarity of what is saved and the possibility of the user to control the conclusions that are drawn about him. Conversations with the smart assistant may include details about work, interests and personal decisions, and sometimes may also extend to fears, experiences and emotions.

The memory of the smart assistants is no longer limited to saving the information that the user shares, but may expand beyond that to create a broader perception of his personality, behavior and way of thinking, which raises new questions about the limits of personalization and privacy. In this regard, a recent study revealed that the memory feature in ChatGPT may contribute to building a psychological and behavioral profile of the user based on the details of their daily conversations, even those that seem simple or unimportant at the moment. These results become even more important when considering the amount of information the system can extract from repeated interactions. The study included conversations of 80 users, and recorded more than 2,000 pieces of information stored in the memories of 65 of them, when it was found that 96% of these memories were created automatically by the system, without a direct request from the user. This suggests that memory not only performs the function of remembering, but may extend to analyzing usage patterns and inferring interests, dispositions, and some psychological and behavioral traits. The study also showed that some of the information saved included personal data, along with inferences beyond what the user directly stated. Hence a fundamental problem arises related to the difference between the information that the user shares explicitly, and that which the system infers from the context of conversations. A passing request or a question about a specific topic may become an indicator that the system relies on to make assumptions about the user's preferences, even though this assumption does not necessarily reflect reality. The sensitivity of this issue is that inaccurate inferences may over time become part of the picture that the system relies on to personalize its responses and guide its interactions with the user. On the other hand, the practical benefits of memory cannot be ignored, especially for users who rely on the smart assistant on a regular basis. Maintaining the context and previous preferences saves time, reduces the need to repeat information, and makes the experience more efficient and tailored to individual needs. But as the ability of these systems to understand and adapt to the user increases, so does the scope of questions regarding the limits of information collection and analysis, the degree of clarity of what is saved and the possibility of the user to control the conclusions that are drawn about him. Conversations with the smart assistant may include details about work, interests and personal decisions, and sometimes may also extend to fears, experiences and emotions.