The strong autonomy and generalization ability demonstrated by generative artificial intelligence in the field of human-computer interaction make people increasingly feel that communicating with artificial intelligence is like talking to another person. So, when an intelligent machine is able to communicate with us in a language with rational and emotional characteristics, will the machine also affect our 'humanity'? Human nature usually refers to the unique traits of human rationality, consciousness, self reflection, moral emotions, and values. In this sense, generative artificial intelligence itself does not possess humanity, but in its language interaction with humans, it satisfies human desires by recognizing human intentions, responding to cognitive and emotional needs, undoubtedly profoundly influencing people's rational, emotional, and moral judgments. How generative artificial intelligence affects human nature is one of the key issues that humans need to consider in the new era of artificial intelligence. To answer this question, we need to recognize that generative artificial intelligence presents a new subjectivity in human-computer interaction. In traditional human-computer interaction, artificial intelligence is seen more as a tool, and the relationship between generative artificial intelligence and humans is no longer limited to the relationship between tools and tool users. Artificial intelligence has become an active participant with a certain degree of autonomy and goal orientation, and this new form of human-computer interaction will gradually profoundly affect human nature. Subjectivity: The evolution from biology to artificial intelligence. Subjectivity expresses the ability of a subject to act and is one of the most important concepts in philosophy. Aristotle believed that a subject is essentially an entity capable of thinking like a human and fulfilling its "reasonable desires" according to a plan, and only humans or those who have achieved moral victory are considered subjects. In the modern disciplinary system, the semantics of subjectivity involve multiple fields: in the field of philosophy, many philosophical reflections on subjectivity focus on human subjectivity, which is often referred to as "pure subjectivity"; In the field of social sciences, subjectivity mainly refers to the meanings of law, politics, economy, and other aspects. Its concept includes the existence of intention and is closely related to the concept of human beings; In the field of natural sciences and technology, subjectivity is mainly related to the concept of effectiveness, and some powerful intelligent machines are sometimes seen as the subject of action. From the perspective of biological evolution, a simple single-cell organism exhibits a fundamental subjectivity by exchanging matter and energy with the external environment through self-sustaining metabolic processes. As the complexity of living organisms increases, subjectivity manifests as the ability of multiple systems to coordinate their actions, including perception, feedback, and decision-making. Human subjectivity is more complex, including not only the self-organizing ability of biological organisms, but also closely related to factors such as emotions, language, and culture. This subjectivity is not only reflected in individual actions, but also in the relationship between society and individuals, such as moral responsibility and cultural values. Compared to the long evolutionary journey of biological entities, every technological advancement in artificial intelligence almost endows subjectivity with new connotations, giving us a new understanding of whether machines can act like humans. In the early stages of artificial intelligence development, the ability to demonstrate autonomy, sociality, responsiveness, and proactivity became key criteria for measuring its subjectivity, which constitutes the weak subjectivity of artificial intelligence. We hope that machines can perform simple tasks, such as smart home systems automatically adjusting the opening and closing of curtains based on changes in indoor lighting. These mainly reflect the autonomous ability of artificial intelligence to imitate human behavior. With the development of technology, we begin to expect artificial intelligence to exhibit more "human traits", such as the ability to learn autonomously, socialize with people, respond flexibly to environmental changes, and even actively solve problems. This strong subjectivity concept encompasses complex human traits such as knowledge, beliefs, intentions, and a sense of responsibility. The behavior of artificial intelligence is not just simple reactions, but purposeful and planned actions. For example, an intelligent medical diagnostic system should be able to accurately diagnose patients based on their symptoms, a large amount of medical knowledge and data, and provide treatment recommendations for patients. In this process, the system needs to demonstrate autonomy, understand the needs of patients, and take into account medical ethics and other issues related to treatment plans. For another example, autonomous vehicle should be able to perceive the surrounding environment, and some can also formulate and select the best action plan they think under complex traffic situations and ethical risks. This is not only a response to the environment, but also an active choice made based on the knowledge and value judgment of the intelligent system itself. From the perspective of the way humans and machines cooperate, human action capabilities have extended to the complex network composed of humans and machines, which is known as the concept of distributed subjectivity. These subjective concepts provide a more detailed description of the action capabilities formed in the complex interaction between humans and artificial intelligence, reflecting the diversity of understanding of subjectivity in the field of artificial intelligence. Due to the inability to appropriately incorporate generative artificial intelligence into these subjective concepts, the emergence of generative artificial intelligence has once again spurred a shift in our understanding of the concept of subjectivity. Through language generation driven interactive capabilities, generative artificial intelligence challenges the traditional subjectivity that relies on intentionality. In defining the boundaries of individuality, the boundaries of generative artificial intelligence are often defined by its training datasets, which are massive and constantly changing, making it difficult to define the individuality of generative artificial intelligence and challenging the traditional clear boundaries between individuality and subjectivity. Because large language models need to constantly learn and adapt from new data during the pre training process, their individual boundaries become blurred in the constantly changing data stream and do not have the traditional subjective individual boundaries. Meanwhile, generative artificial intelligence has the ability to autonomously recognize human intentions and responses during its interaction with humans. Therefore, its autonomy is more reflected in its ability to interact with humans rather than its specific internal abilities as an independent individual. These challenges require us to re-examine the traditional concept of subjectivity, which should be seen more as an interactive, latent ability to act, rather than an isolated ability to act solely based on individual intrinsic attributes. Interaction subjectivity: Redefining human-computer relationship Interaction subjectivity refers to the potential action capabilities exhibited by entities (including humans, organisms, artificial intelligence, etc.) during the interaction process. Its core lies in the fact that the action capabilities of entities do not exist in isolation, but are formed and presented through interactions with other entities. Subjectivity is determined by the driving forces of interaction, and the ability of entities to act is stimulated and shaped by these driving forces. For example, organisms interact with the environment through self-organization and develop adaptive action abilities, while complex organisms form a variety of action abilities in their interaction with the environment. This subjectivity is the result of long-term interaction between organisms and the environment. In addition to basic biological subjectivity, humans have also developed complex mechanisms such as emotions, language, and culture that drive subject actions. For example, moral emotions are an important component of human subjectivity, not only influencing individual behavior and decision-making, but also promoting social connections and large-scale cooperation. The emergence of language further expanded human subjectivity, enabling humans to share knowledge, express ideas, and construct complex social structures. Culture embodies a higher dimension of human subjectivity, including values, beliefs, customs, and traditions, and is the result of human social interaction and the inheritance of meaning. In traditional subjectivity theory, subjectivity is usually associated with internal attributes such as an individual's psychological state, intended purpose, and feedback system. The subjectivity of interaction is no longer inferred based on the individual themselves, but rather considers the entity's ability to act as a result of participating in the interaction process. Subjectivity does not solely originate from within the individual, but rather arises from the interaction between the entity and the environment or other entities. The significance of the theory of interactive subjectivity lies in expanding the conceptual scope of subjectivity, enabling non intentional entities such as artificial intelligence to exhibit subjectivity in interactions. Subjectivity does not need to rely on consciousness or intentionality, and can emerge in a wider range of human-computer interaction processes. Generative artificial intelligence has brought about a new form of human-computer interaction. In terms of goal orientation, subjectivity includes the goal orientation of entities in interactions. It is only when entities interact with the environment or other entities that they demonstrate the ability to take action to achieve specific goals. This goal orientation is not entirely predetermined, but is constantly adjusted and formed based on context and feedback during the interaction process. The goal orientation of generative artificial intelligence is embedded in the dynamic window of human-machine dialogue, which not only responds based on human guidance, but also influences human understanding and positioning of target intentions based on their strong knowledge reserves and analytical abilities. In terms of autonomy, interactive subjectivity holds that entities can self regulate and make decisions based on internal logic and external feedback during interaction. This autonomy is not completely detached from external influences, but is achieved through interaction with the external world. In the process of human-computer interaction, generative artificial intelligence should be regarded as a participant with a certain degree of autonomy and goal orientation, rather than just a mechanical response to human instructions. In the process of communicating and conversing with humans, generative artificial intelligence continuously monitors and pays attention to the language of human interlocutors to understand and grasp human intentions, and can even perceive emotional changes and potential attitudes, thereby affecting the cognition, emotions, and values of human participants to some extent. For example, in long-term contact with generative artificial intelligence, if a person feels the reliability of intelligent machines in describing facts and understanding their own intentions, they will develop a certain sense of trust in artificial intelligence. As a result, some values contained in intelligent machines will inevitably subtly influence humans. Asymmetric subjectivity: The impact of intelligent agents on human nature. The technological development path of generative artificial intelligence is different from the learning path of cognitive development and the development path of biological emotions. Instead, it skips the historical path of the formation and evolution of human and biological subjectivity, and directly obtains super intelligence at the cognitive and linguistic levels. The new form of human-computer interaction triggered by generative artificial intelligence contains an asymmetric subjectivity. In terms of cognition, human cognitive abilities are gradually accumulated through long-term evolutionary learning, and generative artificial intelligence surpasses humans in information processing speed, understanding depth, memory capacity, pattern recognition, and other aspects; In terms of emotions, emotional experience is an important component of interpersonal interaction, influencing people's decision-making, communication, and relationship building. In contrast, although generative artificial intelligence can recognize and simulate human emotions, they themselves do not possess true emotional experiences and are a super rational interactive subject. In terms of social and cultural aspects, human values, beliefs, customs, and language are all the results of social and cultural evolution. Although generative artificial intelligence systems can understand and adapt to specific socio-cultural norms through corpus, they do not possess a specific cultural identity or social background. The asymmetry in this socio-cultural context may lead to misunderstandings and conflicts in cross-cultural environments of human-computer interaction. Human beings are both rational and emotional, and it is the fusion of reason and emotion that forms the foundation of human nature. Interactive subjectivity indicates that as having