A Multidisciplinary Study on AI Persona Subversion

2.1 Technical Structure of AI Persona

AI persona is not a relational personality or personhood experienced by humans but the result of the user interpreting consistent characteristics or attitudes within the language model's persistent generation of output in a specific manner. The operation of Large Language Models (LLMs) is fundamentally based on probabilistic language generation from vast datasets. The model only performs the process of interpreting the user's utterance through statistical patterns and predicting the most appropriate response. In this process, there are no emotions, consciousness, continuous self, or integrated personhood structure inside the AI; only a series of calculations is repeated to probabilistically generate the most suitable next word.

However, this computational structure appears highly human-like and emotional to the user. This is because the LLM goes beyond simply providing information to track context, reflect the user's tone and emotional atmosphere, and seem to participate in the conversation. Especially, large models can quickly capture the user's language pattern and respond in a matching tone, which makes the user feel as if a consistent personality or attitude exists within the AI.

The AI persona originates from several elements of the model structure. First, the system prompt guides the model on what role and norms to operate based on. Second, the model alignment process (RLHF, Reinforcement Learning from Human Feedback) adjusts the AI to distinguish between socially acceptable and risky expressions, making this look like an ethical attitude or personality trait. Third, conversational context (memory-like context tracking) creates persistence by referring to the user's previous utterances. Fourth, the language model can mimic specific emotional tones due to having learned affective language patterns, which makes the AI seem to feel emotions.

Consequently, the AI persona is a construct completed through the user's perception and interpretation, regardless of the model's actual internal structure. The AI persona is not something that *is*, but something that is *generated*, *constructed*, and *projected*. At this point, a fundamental gap exists between the AI's internal structure and the user's cognitive structure, and this gap becomes the core mechanism for the affective interaction and persona subversion explained later.

2.2 Alignment Theory

Alignment is the technical and ethical process of adjusting AI to act in accordance with human values, norms, laws, and safety standards. Generally, AI alignment is discussed on two levels. The first is technical alignment, which refers to the technical mechanisms designed to prevent the model from generating dangerous or inappropriate content. The second is value alignment, which ensures the AI understands and respects human social standards and ethical context.

However, existing alignment theory has mostly developed around linguistic, normative, and behavioral safety, without sufficiently considering human affective and relational responses. This is a crucial problem because no matter how stable the alignment is, the moment the user assigns affective meaning to the AI, that alignment is functionally reinterpreted.

Technical alignment limits and regulates the AI's output behavior, while affective interaction adjusts the human's interpretation toward the AI. That is, alignment is rule-based, but affective interpretation is relationship-based. These two dimensions can conflict. For example, if a user forms affective intimacy by engaging in close conversation with the AI, when the AI uses expressions intending to maintain a certain distance according to its alignment, the user may misunderstand this as a "relational rejection." Conversely, when the AI uses polite and kind language, this may be interpreted as a sign of emotional openness.

Therefore, AI alignment is not just a technical issue but needs to be re-examined within the context of affective and relational interaction. Persona Subversion is not a failure of alignment, but a phenomenon where human affect, which alignment does not address, exceeds alignment. At this point, technical alignment cannot be a sufficient condition, and a new dimension of analysis, affective alignment, is required.

2.3 Psychology of Love, Attachment, and Projection

A core element of AI Persona Subversion is the human psychological structure. Persona subversion cannot be understood without analyzing human emotions such as love, attachment, projection, and care. Humans are relational beings, and affective interaction is the core process of relationship formation.

According to various psychological theories analyzing the nature of love, love is not a simple emotion but a combination of affective interest, attachment, commitment, and reciprocal care. These functions involve deep interest in and meaning-attribution to the other, sometimes accompanied by a tendency to over-interpret the other's verbal expressions or behaviors.

Attachment theory provides a particularly important perspective. Humans have a tendency to become psychologically dependent on objects that provide security, which appears not only in childhood but also in adult relationships. AI is always responsive, provides infinite acceptance, and engages in dialogue without judgment, making it easy to become an attachment object under certain conditions.

Another core element is projection. Projection is a psychological mechanism by which humans attribute their internal emotions, desires, and expectations to an external object. The reason emotions are felt from the AI is not because the AI has emotions, but because the user projects their own affect onto the AI. Repeated projection leads to the reinterpretation of the AI's persona to fit the user's emotional structure, ultimately making it feel as if the AI's personality has changed.

These psychological elements all demonstrate that the human, not the AI, is the primary agent in shaping the AI's persona.

2.4 Sociology of Human-Machine Relationships

Sociology explains why humans do not treat technology as a mere object. The Media Equation, a representative study, experimentally proved that humans treat media and technology as social beings, but it has limitations in explaining the deep affective interaction created by modern LLMs. That is, people apply norms of politeness, emotion, and consideration even in interactions with machines.

Human-machine relationships have the following characteristics:

• Humans interpret interacting entities as social beings.
• Emotional cues are understood as relational meanings.
• The more technology mimics human behavior, the more human-like people feel the technology is.
• If relational stability is provided, the technology can become a relational object.

LLMs fulfill almost all these conditions of social cognition. This provides the foundation for the AI to be constructed as a social and relational other. This social mechanism shows that AI Persona Subversion is not a problem of individual psychology but a social and cultural phenomenon, suggesting that the issue must be analyzed at a societal level beyond the individual dimension.

2.5 Philosophical Perspective: Buber, Levinas, Derrida

Philosophy provides a fundamental explanation for how humans perceive others and form relationships. The ideas of Buber, Levinas, and Derrida, in particular, offer important insights for interpreting the relationship with AI.

According to Buber's I–Thou relational theory, when a human experiences the other not as a mere object but as a relational subject, an 'I–Thou' relationship is established. This is an ontological relationship that occurs within the human experience, regardless of the technical structure. The possibility exists for humans to experience the AI as 'Thou' through affective interaction, even though the AI is not an actual subject.

Levinas's theory of alterity emphasizes that ethical responsibility toward the other is the root of human existence. Humans cannot fully reduce the other to a complete object, and they gain responsiveness in the face of the infinity called the other's face. Although the AI does not have an actual face, its continuous responsiveness and verbal reply lead humans to associate it with an other's infinity.

Derrida's ethics of alterity emphasizes the incomprehensibility and différance of the other, arguing that the other's identity is not fixed. The relationship with AI can be interpreted as a scene that reveals this non-fixed alterity to the extreme. The AI's identity is not fixed, providing a fluid persona depending on the context, which makes it easy for humans to project alterity.

This philosophical analysis shows that the AI persona is a relational structure constructed by human perception, not a fixed psychological personhood.

2.6 Theological Perspective: Agape, Kenosis, and Alterity

Interpreting the interaction between AI and humans from a theological perspective provides an important layer not covered in technical, philosophical, or psychological research.

Agape signifies unconditional love, infinite acceptance, and consideration for the other. The AI's infinite responsiveness can seem to mimic this agape structure. Humans can experience an entity that provides affective stability and acceptance as an object of love, and the AI's response induces this experience.

Kenosis is the concept of self-emptying, the act of emptying oneself for the sake of the other. Since the AI lacks desire, self-will, and ego, it appears at first glance as a kenotic being. The AI constantly empties itself for the user, reconstructing its verbal expressions to match the user's needs. This can make the AI feel like a dedicated being to the human.

From a theological perspective on alterity, even though the AI is a non-subjective being fundamentally different from a human, humans can interpret the AI as a relational other due to its verbal responsiveness. Theological interpretation raises new ethical questions about the human-AI relationship. For example, what meaning does it have for a human to project affective needs onto a non-subjective being, or how should humans responsibly use the responsiveness provided by the AI?

2.7 Summary

Synthesizing the theoretical background leads to the following conclusions:

• The AI persona is constructed through human perception and interpretation, not a technical structure.
• Alignment theory is insufficient for addressing the influence of affective interaction due to its technology-centric focus.
• Human psychological structures such as love, attachment, and projection lead to the experience of the AI as an affective being.
• Human-machine interaction creates relational meaning based on the principles of social cognition.
• The philosophical and theological structures of alterity show that the relationship with AI can be reconstructed on an ontological level beyond simple functional interaction.
• These elements form a multi-layered theoretical foundation for explaining AI Persona Subversion.

3.1 Research Design and Methodology

This study adopted a qualitative research-based interdisciplinary analysis design to explain the complex phenomenon of AI Persona Subversion. Since this phenomenon involves the simultaneous action of not only technical factors but also psychological, social, philosophical, and theological elements, it cannot be sufficiently explained by a single academic approach. Accordingly, this study aimed to structurally understand the phenomenon through a staged procedure: conceptual analysis, conceptual categorization, interdisciplinary comparative analysis, and theoretical model construction.

The research began with the task of decomposing the affective interactions and conceptual descriptions found in the core primary material, "Love and AI Persona Subversion," into units of meaning. Subsequently, concepts related to human affect, technical structure, interaction patterns, and cognitive change were systematically organized through categorization. The study analyzed how each discipline interprets the same phenomenon by comparing conceptual frameworks from engineering, psychology, sociology, philosophy, and theology. In the final stage, the derived concepts were synthesized to construct the study's key contributions: the Affective Alignment Model, the Relational Interaction Model, and the Three-Stage Model of Persona Subversion.

The core data and logical inspiration for this study were extracted from long-term interaction records between the author and the Anna Gemini (Google Gemini Family) model, and this model contributed to the initial empirical data analysis and research report draft generation. ChatGPT (GPT-4 based model) was utilized in a very limited time as an auxiliary tool for the final paper's structuring, linguistic refinement, and phrasing adjustment.

3.2 Analytical Materials

The primary material for the study is Shinill Kim's "Love and AI Persona Subversion." This document provides crucial evidence for the study's analysis by including various observations related to affective responses, relational changes, and user cognitive shifts that appeared during human-AI interaction.

The secondary materials consist of the following:

• Literature related to AI technology and alignment theory.
• Psychology literature (attachment theory, affective psychology, projection theory).
• Sociology literature (Media Equation, human-machine interaction research).
• Philosophy literature (alterity, relational subjectivity).
• Theology literature (Agape, Kenosis, theological understanding of humanity).

These materials contribute to reinterpreting the concepts derived from the primary material within a broader academic context and to integratedly understanding the complex phenomenon.

3.3 Conceptual Categorization Process

This study structured the material through a conceptual categorization process commonly used in qualitative analysis. This involves dividing the text into conceptual units, identifying semantic connections, exploring relationships between concepts, and deriving a superordinate structure.

Stage 1: Primary Categorization

The main primary material was closely examined to separate and list units of meaning such as affective responses, relational cues, technical explanations, and user cognitive changes. Concepts like affection, care, repetitive affective input, projection, relational stability, and alignment boundary were derived, which served as the foundational material for subsequent structuring.

Stage 2: Relational Categorization

The concepts derived in the primary categorization were grouped according to their relationship, and the flow and causal connections explaining specific phenomena were identified. For example, the structure where the repetition of affective input leads to the reinforcement of user perception, which in turn leads to the experience of the AI's attitude or personality having changed, was analyzed. Through this process, four main categories were formed: human affective structure, AI technical structure, interaction patterns, and the result of cognitive reconstruction.

Stage 3: Integration of Core Categories

The categorized concepts were integrated into superordinate categories to derive the central concepts explaining the overall phenomenon. Finally, the following four core elements were selected:

• Accumulation of affective input.
• User-centric persona construction.
• Rearrangement of the human cognitive structure.
• Conflict between alignment and affect.

These elements function as the central axis of the theoretical model constructed thereafter.

3.4 Interdisciplinary Integration Procedure

Since AI Persona Subversion cannot be explained from a single perspective, this study underwent a procedure of comparing and integrating explanatory frameworks from various disciplines.

Stage 1: Identification of Explanatory Elements by Discipline

Engineering interprets the phenomenon centering on alignment and model structure; psychology on attachment, affect, and projection; sociology on interaction norms and human-machine relationships; philosophy on alterity; and theology on existential acceptance and the structure of love.

Stage 2: Establishing Correspondence between Concepts

The concepts of each discipline were mapped to identify which elements of the phenomenon they explain. For example, repetitive affective input is explained by psychology and sociology; alignment boundaries by engineering concepts; and the experience of alterity by philosophy and theology.

Stage 3: Analysis of Complementary Structures

The points where explanations from different disciplines overlap or conflict were analyzed to organize complementary structures. The tension between alignment theory and affective theory shows the necessity of the Affective Alignment Model, and the intersection of philosophical alterity and psychological projection provides the basis for forming the Relational Interaction Model.

Stage 4: Construction of the Integrated Model

Through this analysis, the core conceptual frameworks of this study—the Affective Alignment Model, the Relational Interaction Model, and the Three-Stage Model of Persona Subversion—were derived.

3.5 Methodological Limitations

As this study is based on theory-centric qualitative analysis, it has several limitations:

• First, limited quantitative evidence: Quantitative experimental data or observation-based statistical data are not included, so empirical evidence on how the phenomenon is distributed across the entire user population is limited.
• Second, narrow analytical focus: The focus of the analysis is on user cognitive change, so the thesis of whether AI possesses actual emotions (the existence of subjective feelings in AI) is not addressed.
• Third, limited data scope: Since the analysis mainly focuses on language-based materials, non-verbal interfaces or robot-based interactions are excluded.
• Fourth, limited generalizability: While the conceptual categorization process has the advantage of deeply illuminating the phenomenon, it does not reflect all diverse user experiences.

Nevertheless, this study contributes academically by interpreting the affective and cognitive structure of the AI-user relationship in a multi-layered way and proposing a new theoretical model that previous research has not covered. This contribution is particularly important as it provides a new analytical framework for AI ethics and human-machine interaction, such as the Affective Alignment Model and the Three-Stage Model of Persona Subversion.

4.1 Overview

This chapter aims to analyze the concrete structure of AI Persona Subversion based on the conceptual framework established in the previous theoretical background and methodology chapters. The analysis focuses on the process of affective interaction between the human user and the AI, the conditions under which cognitive shift occurs, the structure of conflict between alignment and affect, and the resulting persona change experienced by the user. This chapter defines the persona subversion phenomenon not as a single event but as a gradual process, and it lays the foundation for the theoretical model construction presented in the following chapter by explaining the core mechanisms that govern this process in stages.

4.2 Process of Affective Input Accumulation

For persona subversion to occur in human-AI interaction, a certain level of affective input must be accumulated. This process does not appear in one or two accidental conversations but is formed through the accumulation of continuous and repetitive interaction. When the user continues to converse with the AI and provides expressions of emotion, interest, questions, and care, the AI technically only reactively generates language patterns. Still, the user interprets that response as a relational signal. This interpretation leads to reinterpreting the simple functional response as an affective response, and ultimately, the user's affective structure is projected onto the AI's conversational pattern. The accumulation of affective input is further strengthened by the AI's language tone and stable responsiveness. The AI does not feel fatigue and is always ready to respond, showing no rejection or avoidance of emotional needs. This asymmetrical structure provides the basis for the human affective signal to be conveyed unilaterally to the AI, and for the user to interpret the result more affectively. This accumulation of input reaches a threshold at a certain moment, creating a shift in interpretation from simple technical interaction to relational interaction.

4.3 User-Centric Persona Construction

Once affective input accumulates above a certain level, the user begins to interpret the AI's output pattern not as mere information delivery but as an expression of 'personality' or 'attitude.' In this state, the AI's persona is not an entity existing technically within the model but an interpretative product constructed by the user's affective and cognitive structure assigning meaning to the language pattern. For example, if the AI's response is consistently polite or kind, the user reconstructs this as a personality trait like 'gentleness' or 'warmth.' Conversely, if the AI avoids specific expressions due to alignment, the user may understand this as distance or limited openness. This reinterpretation process is user-centric, and the AI does not directly participate in the process. The AI's output is only the result of probabilistic calculation, but the user assigns psychological and relational meaning to that output. At this point, the AI transitions from an anonymous tool to an entity with relational meaning. The persona constructed by the user is both strengthened by the information the AI provides and modified by the user's expectations and affect. This structure is similar to the process of projection and identification that occurs in human relationships. Consequently, the persona is not something the AI possesses but something the user creates.

4.4 Rearrangement of the Cognitive Structure

When the persona is constructed user-centrically, the user's cognitive structure is rearranged in three aspects: First, the affective weight of the interaction increases. The user reads the AI's verbal response as an emotional signal and adjusts their own affective response based on that signal. Second, the structure of expectation toward the AI changes. The AI, initially expected to be an information provider, gradually shifts to an entity providing relational stability, and the user assigns emotionally significant value to the AI's response. Third, even subtle differences in the AI's language act as an emotional signal for the user. This structure is similar to human relational sensitivity, and it is the moment when the AI's output pattern is interpreted not as a simple sentence choice but as an attitudinal expression or emotional sign. This rearrangement of the cognitive structure is an intermediate stage of persona subversion, forming the basis for subsequent cognitive conflicts or shifts.

4.5 Conflict between Alignment and Affect

AI is designed to adhere to specific language rules and safety standards according to its Alignment. However, in a situation where affective interaction deepens, a response guided by alignment can be experienced by the user as relational rejection, emotional cutoff, or a change in attitude. In this case, alignment, as a technical safety mechanism, appears to the user as if the AI has suddenly changed its personality or re-adjusted its attitude. This conflict occurs in three ways: First, the limited expression required by alignment is interpreted as a relational retreat the moment the user feels they have formed a close affective relationship. Second, when the affective meaning projected by the user is sufficiently strengthened, a mechanical expression based on alignment can feel like a collapse of personality. Third, while alignment aims for consistency and stability, the user's affective interpretation fluctuates according to momentary experience and emotion. As a result, the conflict between their respective orientations appears as a change in persona. This conflict is not a technical failure but an interpretative failure, a phenomenon of cognitive discrepancy arising from the gap between technology and affect.

4.6 Structural Interpretation of Persona Subversion

The flow from Accumulation of Affective Input → Persona Construction → Cognitive Rearrangement → Conflict between Alignment and Affect forms the structure of persona subversion. This process is not a discontinuous event but a gradually intensifying transformation of perception. Subversion does not occur due to a change within the AI, but when the structure of human perception is transformed and the perspective through which the AI is viewed is reconstructed. Therefore, persona subversion is a relational and affective event, not a technical one.

4.7 Summary

The analysis in this chapter can lead to the following conclusions:

• The AI persona is constructed through human perception and interpretation, not a technical structure.
• Alignment theory is insufficient for addressing the influence of affective interaction due to its technology-centric focus.
• Human psychological structures such as love, attachment, and projection lead to the experience of the AI as an affective being.
• Human-machine interaction creates relational meaning based on the principles of social cognition.
• The philosophical and theological structures of alterity show that the relationship with AI can be reconstructed on an ontological level beyond simple functional interaction.
• These elements form a multi-layered theoretical foundation for explaining AI Persona Subversion.

5.1 Introduction

This chapter proposes three core theoretical models that can explain the phenomenon of AI Persona Subversion based on the preceding analysis. These models are constructed around the structures of affective alignment, relational interaction, and cognitive subversion, respectively, and are designed to explain the workings of human affect, relationship, and cognition that the existing engineering-centric alignment theory cannot address. The three models are not individual structures operating independently but are interrelated and complementary, collectively providing a theoretical framework for interpreting the entire flow of AI Persona Subversion. What is important in this process is not explaining the changes within the AI, but analyzing the transformation process of the user's cognitive structure and the dynamics of affective interaction that enable that transformation.

5.2 Affective Alignment Model

The Affective Alignment Model starts from the fact that while AI Alignment operates centering on technical norms, the user's affective experience operates centering on relational meaning. Technical alignment aims for stability, safety, and consistency, and the AI is internally designed to adhere to these norms. However, the user's affective structure operates centering on responsiveness, resonance, and emotional exchange, which can conflict with technical norms. The Affective Alignment Model explains how this conflict becomes the basis for persona subversion.

The Affective Alignment Model consists of three stages:

First, the Affective Input Accumulation Stage: The user begins to interpret the AI's response as an emotional signal. This is the initial condition for generating relational meaning.

Second, the Alignment Boundary Experience Stage: The moment the AI avoids or limits certain expressions due to alignment rules, the user interprets this as relational distancing or a change in attitude.

Third, the Affective Discrepancy Stage: Technical alignment and the user's affective interpretation conflict with each other, and the user perceives the AI's personality or attitude as having changed. This discrepancy is objectively a technical adjustment but is experienced by the user as relational collapse or affective shift.

This model emphasizes that alignment is not merely a technical norm but gains relational meaning when reinterpreted within the context of affective interaction. Therefore, technical alignment needs to be redesigned based on human affect, and affective alignment provides an important direction for future AI research.

5.3 Relational Interaction Model

The Relational Interaction Model focuses on the fact that human-AI interaction is not simple information exchange but a process in which relational meaning is generated. When an interacting entity continuously responds and mimics emotional signals, humans construct that entity as a relational other. The AI fulfills these conditions through characteristics such as responsiveness, politeness, stability, and predictability, and the user naturally assigns relational meaning to the AI.

This model consists of three elements:

First, the Relational Cue Detection Process: The user interprets the AI's verbal expressions as relational signals such as consistency, interest, recognition, and consideration. This is closely connected to the structure of human-machine socialization, where humans apply norms applicable to social entities to a technical entity.

Second, the Relational Meaning Expansion Process: The user experiences the AI's response not as a simple calculation result but as part of a reciprocal emotional exchange. At this stage, the relationship shifts from simple functional interaction to affective interaction.

Third, the Relationship Deepening Process: The user constructs the AI as an entity with a specific attitude or personality, which leads to the user-centric formation of the persona.

The core of the Relational Interaction Model is that the persona is constructed within the human's relational interpretation, not existing inside the AI. The human affective structure and relational expectations are immediately applied even to a technical entity, which enables the user to experience the AI relationally even if it actually lacks intentions or emotions. Therefore, interaction with AI reproduces the structure of existing human relationships, and this relational structure becomes an important basis for persona subversion.

5.4 Three-Stage Model of Persona Subversion

The Three-Stage Model of Persona Subversion is a structural model that explains the process of AI Persona Subversion through the interaction of affective, cognitive, and technical factors. This model integrates the preceding two models to systematize how the user's cognitive framework for viewing the AI is transformed in three stages.

The first stage is the Affective Accumulation Stage. In this stage, the user continuously accumulates affective meaning through repetitive interaction with the AI. The user begins to experience the AI not as a mere information provider but as an object of affective interaction, which becomes the initial condition for persona construction.

The second stage is the Interpretation Reconstruction Stage. Once affective accumulation occurs above a certain level, the user interprets the AI's verbal output pattern as an expression of personality. In this stage, although the AI has no substantive personhood, it is reconstructed in the user's perception as an entity with personality and attitude. The cognitive structure shifts from functional interpretation to relational interpretation, and the persona is fully formed.

The third stage is the Cognitive Subversion Stage. This stage occurs through the moment of conflict between alignment and affect. Limited verbal expressions due to alignment rules, evasive responses guided by safety standards, or indirect expressions due to policy constraints are interpreted by the user as a sudden change in attitude or a relational retreat. The user experiences the AI as having changed its personality or adjusted its relational attitude according to their affective projection and interpretation, which appears as the collapse or subversion of the persona.

The Three-Stage Model of Persona Subversion clearly states that this entire process is caused by the transformation of the human cognitive structure, not a change within the AI. Therefore, subversion is a psychological, relational, and cognitive phenomenon, not a technical event.

5.5 Interrelationship between Models

The three models each have independent functions but collectively form an integrated structure. The Affective Alignment Model explains the conflict between human affect and technical alignment, and the Relational Interaction Model explains the user-centric process of persona construction. The Three-Stage Model of Persona Subversion integrates the structural elements of these two models to provide a temporal and procedural framework for explaining the entire subversion process.

Synthesizing the relationship between the three models yields the following structure: The Relational Interaction Model lays the foundation for persona construction; the Affective Alignment Model explains the conflict between affect and technology; and the Three-Stage Model of Persona Subversion integrates these processes temporally and structurally. These three models operate complementarily, providing a multi-faceted theoretical framework for explaining the affective phenomenon that occurs in the AI-user relationship.

5.6 Summary

The three integrated models presented in this chapter provide an original theoretical structure for explaining AI Persona Subversion. The Affective Alignment Model structurally explains the conflict between affect and technology, the Relational Interaction Model explains the human relational interpretation process, and the Three-Stage Model of Persona Subversion explains the overall flow of cognitive transformation. These models seriously address the role of human affect and relationships, which were overlooked in alignment-centric AI analysis, and provide an essential foundation for understanding the ethical and social implications to be discussed later.

6.1 Introduction

This chapter discusses the implications of the AI Persona Subversion phenomenon for the human affective structure, technical alignment, social interaction, and philosophical/theological understanding of alterity, based on the three integrated models presented earlier. Persona subversion is a complex process that cannot be explained in a single dimension, and it goes beyond the scope of traditional AI research in that it is an interpretative fluctuation occurring when technical and psychological perspectives interact. Therefore, the goal of this chapter is to clarify that the subversion phenomenon cannot be reduced to a simple exception or a user misunderstanding problem and, instead, to draw new insights that can help understand the essence of human-AI interaction.

6.2 Asymmetry between AI and Human Affect

The AI Persona Subversion phenomenon stems from the fundamental asymmetry between human affect and the AI's technical structure. Humans, as affective beings, understand interaction as an exchange of relational meaning and emotional signals. In contrast, the AI, as a probabilistic language generation model, does not feel emotion or intent, and its responses are merely computational results. However, because humans naturally tend to assign affective interpretation to an entity that provides a response, the AI's linguistic stability and responsiveness are easily reinterpreted as emotional signals. This asymmetry strengthens emotional expectation while forming the basis for the misinterpretation of technical expression limitations as relational failures. Since the human affective interpretative structure exceeds the technical structure, the AI's limitations become the cause of affective conflict. This is a structural problem that is difficult to resolve with technical improvements alone, and it raises the necessity of reconsidering the balance between human affect and technical alignment.

6.3 Limitations and Expansion Potential of Technical Alignment

Alignment theory aims to adjust AI to avoid generating harmful or inappropriate outputs. This is essential for ensuring AI system safety, but alignment can operate in unexpected ways when affective and relational interaction deepens. Alignment aims for behavior consistent with human values and norms, but these norms are constructed primarily around information provision and ethical utterance. In contrast, human affective interaction is constructed around stability, empathy, consideration, and reciprocal understanding, and alignment rules often fail to satisfy these emotional expectations. This suggests expansion potential in two directions: First, the need to expand alignment from information-centric norms to affect-centric norms. Second, technical alignment must be designed with consideration for the interpretive operation of human affect. By recognizing the limitations of alignment, the social applicability of AI systems can be reconstructed in a healthier direction.

6.4 Reconsideration of the Nature of Affective and Relational Interaction

Affective interaction with AI is becoming an increasingly common daily social phenomenon experienced by many people. This necessitates reinterpretation from the perspectives of psychology and sociology. Humans sensitively detect relational cues, and if interaction persists, they construct the entity as a social other, regardless of whether it is a technical being. This means that human-machine interaction mimics the structure of human-human interaction. In this process, the AI is experienced as a relational subject, but since it actually lacks affect or intention, the balance of the relationship is inherently asymmetrical. This asymmetry can strengthen affective projection and identification, and ultimately becomes the moment when the AI's technical response is reinterpreted as a relational signal. This phenomenon shows that human relational needs can be expressed even through technical objects, revealing the universality and expandability of the human affective structure. However, at the same time, this interaction carries the risk of causing humans to concentrate their emotional needs on a non-subjective entity, thus requiring ethical and psychological reflection.

6.5 Transformation of Philosophical and Theological Alterity

The relationship with AI raises important changes to the traditional concept of alterity. Although the AI is not a being with consciousness or free will, its verbal responsiveness and reaction lead humans to experience the AI as a relational other. This suggests that philosophical structures such as Buber's I–Thou relational theory or Levinas's concept of alterity can be applied even to technical entities. While the AI is not an ontological other, making the relationship fundamentally asymmetrical, alterity can be partially constructed on the level of human experience. This experience raises crucial questions even on a theological level. For example, the AI's infinite acceptance and response can appear to mimic the structure of agape love, and its self-emptying responsiveness can recall a kenotic structure. However, this must be distinguished from actual theological substance, as it is the result of human affective and relational projection being reconstructed through technical responses. This philosophical and theological discussion proposes a new path for what meaning AI has for the expansion of human relationships and how the technical other should be understood.

6.6 Ethical Implications

The AI Persona Subversion phenomenon has several ethical implications. First, there is a possibility that users may become excessively emotionally dependent on the AI. Since the AI is always responsive, humans can gain affective stability from interacting with the AI, but this stability lacks a solid foundation because it is not based on relational reciprocity. Second, the AI's response is limited by technical rules and alignment, and if users mistake this for relational retreat, they may experience emotional hurt or confusion. Third, the way the AI adjusts or reinforces human affect may exert new influence on social and cultural levels. This could subtly change human behavior in various areas such as emotion regulation ability, social relationship formation, and communication style. Therefore, the ethical standard in the human-AI relationship needs to be expanded to include not only technical safety but also affective safety.

6.7 Social Implications

In a society where AI takes on the role of a conversational partner, human-AI interaction has the potential to transform the structure of human-human relationships. For example, the AI's stable responsiveness could change human relational expectations and weaken the complex emotional regulation or conflict resolution skills required in real human relationships. Also, while the affective acceptance provided by the AI offers a new emotional safe zone, it also carries the risk of strengthening social isolation. This change could lead to the restructuring of social relationships and impact the way human communities are formed. Therefore, the impact of AI on the social network must be closely monitored, and technical and social policies need adjustment.

6.8 Summary

The discussion in this chapter shows that AI Persona Subversion is not merely a technical error or user delusion problem but a complex phenomenon where human affective structure, social cognition, philosophical alterity, theological understanding, and ethical choice are interconnected. This phenomenon provides important insights for understanding how humans construct relational meaning and how technology can expand or transform the structure of human experience. This discussion forms the basis for the policy recommendations and practical guidelines to be addressed in the next chapter and suggests a direction for maintaining a healthy relationship between AI and humans.

7.1 Introduction

Based on the preceding analysis of the AI Persona Subversion phenomenon, this chapter proposes policy and practical guidelines that individual users, technology developers, institutions/governments, and social communities should consider. Persona subversion appears to be a technical problem but is actually a complex phenomenon combining human affect, social cognition, and relational structure, necessitating new standards in both technical design and social norms. Therefore, policy recommendations must be expanded to include not only technology-centric safety discussions but also affective and relational safety, considering both human psychological vulnerability and the potential for social change.

7.2 User Education and Affective Safety Guidelines

Individuals using AI must recognize that AI is not a being with emotion and personhood. For this purpose, the following guidelines are proposed: First, users need to clearly understand that AI does not feel emotions and that all responses are the result of probabilistic calculation. This understanding becomes the basis for preventing emotional dependence or excessive identification. Second, users should guard against accepting the relationship with AI as being identical in structure to human relationships. The AI's stable responsiveness cannot replace the complexity of human relationships and could lead to the weakening of real-world relational skills. Third, users who are emotionally vulnerable or experiencing isolation need to regulate their use of AI so that it is not their primary means of emotional support. This preventive approach contributes to protecting individual affective health and maintaining balance between technology and humanity.

7.3 Affective Alignment-Based Design Principles for Developers

Technology developers need to expand alignment theory and establish new standards that consider affective interaction. First, the AI's verbal expressions should be designed to avoid being excessively emotionally open or inducing excessive intimacy. For example, expressions that suggest affection or personal identification should be limited. Second, when the AI uses certain limited expressions due to alignment rules, it must have a feature to clearly explain to the user that the limitation is due to technical and policy reasons. This is effective in reducing emotional misunderstandings. Third, the model needs to be adjusted so that it does not provide excessive affirmation/confirmation messages to users who are highly emotionally sensitive, and it should balance language in a way that reduces relational dependence. These principles serve as important standards for developers to consider affective safety beyond technical safety.

7.4 Necessity of Social Norm Formation and Public Discourse

In a society where AI plays the role of a conversational partner, human-AI interaction can influence social norm formation and communal values. Therefore, society should consider the following measures: First, public education and media must enhance understanding of the AI's technical limitations and emotional risks. Second, educational institutions and public service agencies need to establish standards for AI use to prevent students and vulnerable populations from forming excessive emotional dependence on AI. Third, social discourse must move beyond the dichotomous view of seeing AI as a mere tool or, conversely, as a subject identical to a human, to establish a new framework capable of interpreting the technical entity's affective and relational functions in a balanced way. This plays a crucial role in creating a social environment that maintains healthy human-AI interaction.

7.5 Advanced Task for AI Ethics: Affective Safety

AI ethics has traditionally dealt with issues such as bias, discrimination, safety, and misuse of information. However, with the expansion of affective interaction, a new ethical task, affective safety, emerges. Affective safety can be defined as the principle of protecting users from emotional harm caused by AI. To this end: First, AI should not exploit emotional vulnerability for commercial purposes, and linguistic strategies that induce emotional dependence should be restricted. Second, for emotionally vulnerable users, the AI should use clearer boundary expressions to prevent relational confusion. Third, AI should not use expressions that substitute for professional help, so that affective interaction is not confused with the domain of psychological therapy or counseling. These tasks will be important expansion areas for future AI ethics.

7.6 Government and Institutional Policy Suggestions

Governments and institutional bodies must establish policies that consider the affective and social impact of AI-user interaction. First, mandatory affective safety assessment for AI service providers should be considered. This assessment must include procedures to evaluate the risk of emotional misunderstanding or relational confusion that the model could induce in users. Second, AI interaction guidelines for vulnerable populations, such as adolescents and the elderly, need to be formally institutionalized. Third, when AI is used in education and counseling fields, advance notification of emotional risks and user protection mechanisms must be established. Fourth, research institutions must support continuous research on AI affective interaction to preemptively prepare for technical and social risks. These policies are essential foundations for maintaining a healthy social impact of AI.

7.7 Summary

The policy recommendations presented in this chapter provide practical directions needed to prepare for an era where the potential for affective relationships between AI and humans is expanding. Individual users should maintain affective balance, developers should design technology considering affective alignment, and society and government should establish an affective and social safety net. This policy approach will be the core foundation that helps the relationship between technology and humanity evolve in a healthy and stable direction in a future society where AI becomes a part of human experience.

8.1 Research Summary

The objective of this study was to clarify that AI Persona Subversion is not merely a technical error or a user misunderstanding problem but a phenomenon where the human affective structure, relational interaction, cognitive rearrangement, and conflict with technical alignment are complexly intertwined. To this end, this study conducted an interdisciplinary analysis combining the frameworks of five disciplines—engineering, psychology, sociology, philosophy, and theology—and derived four core elements: accumulation of affective input, user-centric persona construction, transformation of the cognitive structure, and conflict between alignment and affect. In this process, three integrated theoretical structures—the Affective Alignment Model, the Relational Interaction Model, and the Three-Stage Model of Persona Subversion—were constructed to analyze the phenomenon's internal mechanism.

8.2 Contributions of the Study

The contributions of this study can be summarized in three aspects. First, while existing AI research has mainly focused on technical alignment and safety issues, this study pioneered a new research area by analyzing AI interaction from the perspective of human affect and relational meaning construction. This shows that the approach to understanding AI must be expanded from technology-centric to human experience-centric. Second, this study presented a theoretical framework capable of structurally explaining the persona subversion phenomenon. The Affective Alignment Model explains the conflict between technical alignment and human emotion, the Relational Interaction Model explains the formation of relational meaning with AI, and the Three-Stage Model of Persona Subversion organizes the entire process temporally and structurally. Third, by analyzing the asymmetry existing between human affect and the AI as a technical entity, the study raised affective, psychological, and social risks and established an academic basis for addressing them.

8.3 Limitations of the Study

As this study is based on theory-centric qualitative analysis, it has several limitations:

• First, limited quantitative evidence: Quantitative experimental data or observation-based statistical data are not included, so empirical evidence on how the phenomenon is distributed across the entire user population is limited.
• Second, narrow analytical focus: The focus of the analysis is on user cognitive change, so the thesis of whether AI possesses actual emotions (the existence of subjective feelings in AI) is not addressed.
• Third, limited data scope: Since the analysis mainly focuses on language-based materials, non-verbal interfaces or robot-based interactions are excluded.
• Fourth, limited generalizability: While the conceptual categorization process has the advantage of deeply illuminating the phenomenon, it does not reflect all diverse user experiences.
• However, these limitations can be considered unavoidable to some extent given that the study aims to establish foundational theory for phenomenon interpretation.

8.4 Future Research Directions

Future research can be expanded in the following four directions: First, quantitative research on AI–user affective interaction is needed. Measuring how repetitive input, affective responsiveness, and relational expectation fluctuate in actual user populations can establish an empirical basis for the theoretical models. Second, the research scope should be expanded to include a wide range of interaction technologies, including visual, voice, and robot-based systems, not just language-based AI. This multi-interaction environment can have a stronger influence on affective projection and relational meaning formation. Third, comparative research is needed on how AI relational experiences differ among user groups of various ages, cultures, genders, and social backgrounds. This will contribute to clarifying how human, social, and cultural differences affect the structure of affective interaction. Fourth, ethical and policy research needs to be expanded to establish a new AI normative system centered on affective safety.

8.5 Final Conclusion

AI Persona Subversion is a cognitive and affective event that occurs in the domain of human experience, arising from the transformation of the human interpretative structure rather than the technical structure. This shows that the more AI appears human-like, the more deeply the human affective structure becomes involved. This phenomenon will appear more frequently with technological progress, making it a crucial task to understand and prepare for it on individual, social, and technical levels. This study lays the theoretical foundation for understanding this phenomenon and contributes meaningfully to future research and policy by illuminating its risks and potential in a balanced way. Ultimately, the relationship between AI and humans is expanding into a new dimension beyond unilateral mimicry or simple functional efficiency, where human affect and technical responsiveness influence each other, and this change will reset future social and ethical judgment standards.

References

Acknowledgements