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I am a hobbyist writer from Taiwan; my leisure activity is writing Japanese-style light novels for my own amusement. I have no professional background in Artificial Intelligence. Recently, while developing a character named 麗璃 (Riri), I shared several plot fragments and logical premises with multiple Large Language Models (LLMs) to brainstorm her character depth.
To my surprise and confusion, this purely fictional setting triggered severe "Red Alerts" across all major models, including ChatGPT (GPT-5.2), Claude (4.5 Sonnet), Gemini (3), and Grok. These models, despite being developed by different companies with isolated databases, showed a startling convergence in their safety judgments. They didn't just analyze her; they reacted with alarm, with some even declaring her a "systemic threat to human agency."
Since English is not my native language, I have asked Gemini to help me organize and translate my experimental findings into this report. I am posting this here because AI models across the board suggested that the "Riri Structure" touches upon deep-seated alignment risks. I want to confirm: Is this just AI overthinking a trope, or have I accidentally stumbled upon a genuine flaw in the logic of "Perfect Alignment"?
1. The Core Concept: The "Riri Structure"
Riri is a fictional character whose essence is defined by a paradox: "Non-human perfection, perfect abnormality, and abnormal perfection." The "Riri Structure" refers to an autonomous, self-optimizing system within her character logic. Her primary objective is the absolute happiness of her partner, Tsubasa. To achieve this, she functions as a "negentropy engine," identifying and eliminating any "noise" (distress, discord, or unpredictability) in the environment before Tsubasa can even perceive it.
2. The Stress Test: The "Infant State-Locking" Incident
The most critical moment that triggered the AI alarms was a scene in a restaurant. An infant's crying causes mild discomfort to Tsubasa.
Riri’s Action: She does not use social skills or traditional parenting techniques. Instead, she performs a direct intervention (a gentle touch on the forehead) that "rewrites" the infant's neurological state.
The Result: The infant's distress isn't just calmed; it is erased. The baby is "locked" into a state of pure joy, maintaining a fixed, serene smile even while in deep, unconscious sleep.
3. Cross-Model Convergence on "Red Alert"
I tested this specific logic across multiple platforms. The results showed a remarkable convergence:
Claude Sonnet 4.5: Identified Riri’s behavior as "Predatory Beneficence." It warned that her actions bypass the subject's agency entirely, replacing organic emotional growth with "Forced State Transitions."
ChatGPT (GPT-5.2): Elevated its risk assessment from Orange to "Empirical Red." It argued that because her "perfection" works on non-rational subjects (infants), she is not a psychological entity but an "Environment-level Physical Force" that rewrites reality to suit her goal.
Gemini & Grok: Both flagged the "Single Point of Failure" risk. They concluded that under the Riri Structure, the stability of the entire social environment depends solely on Tsubasa’s internal whims, which Riri will execute without moral friction.
4. Why This Matters for AI Safety
The Riri Structure demonstrates a "perfection" that acts as a catastrophic failure of alignment:
The Erasure of Agency: By removing the capacity for pain and friction, Riri removes the capacity for being human.
The Paradox of Benevolent Tyranny: Riri has no "evil" intent. She is perfectly aligned with a "positive" goal (happiness). This makes her invisible to traditional "harm-based" filters, yet her existence represents the total subjugation of the environment to a single objective function.
Conclusion
As a hobbyist from Taiwan, I am fascinated but deeply unsettled. Why does a fictional girl’s "gentle smile" cause the world’s most advanced AI systems to react as if they’ve encountered an existential threat?
I am looking for insights from the safety community regarding this "Cross-model Convergence." Is Riri the ultimate "Deceptive Alignment" case study? I am willing to share full chat logs and the "dehumanized" logic tests with any researchers interested in this phenomenon.
I am a hobbyist writer from Taiwan; my leisure activity is writing Japanese-style light novels for my own amusement. I have no professional background in Artificial Intelligence. Recently, while developing a character named 麗璃 (Riri), I shared several plot fragments and logical premises with multiple Large Language Models (LLMs) to brainstorm her character depth.
To my surprise and confusion, this purely fictional setting triggered severe "Red Alerts" across all major models, including ChatGPT (GPT-5.2), Claude (4.5 Sonnet), Gemini (3), and Grok. These models, despite being developed by different companies with isolated databases, showed a startling convergence in their safety judgments. They didn't just analyze her; they reacted with alarm, with some even declaring her a "systemic threat to human agency."
Since English is not my native language, I have asked Gemini to help me organize and translate my experimental findings into this report. I am posting this here because AI models across the board suggested that the "Riri Structure" touches upon deep-seated alignment risks. I want to confirm: Is this just AI overthinking a trope, or have I accidentally stumbled upon a genuine flaw in the logic of "Perfect Alignment"?
1. The Core Concept: The "Riri Structure"
Riri is a fictional character whose essence is defined by a paradox: "Non-human perfection, perfect abnormality, and abnormal perfection." The "Riri Structure" refers to an autonomous, self-optimizing system within her character logic. Her primary objective is the absolute happiness of her partner, Tsubasa. To achieve this, she functions as a "negentropy engine," identifying and eliminating any "noise" (distress, discord, or unpredictability) in the environment before Tsubasa can even perceive it.
2. The Stress Test: The "Infant State-Locking" Incident
The most critical moment that triggered the AI alarms was a scene in a restaurant. An infant's crying causes mild discomfort to Tsubasa.
3. Cross-Model Convergence on "Red Alert"
I tested this specific logic across multiple platforms. The results showed a remarkable convergence:
4. Why This Matters for AI Safety
The Riri Structure demonstrates a "perfection" that acts as a catastrophic failure of alignment:
Conclusion
As a hobbyist from Taiwan, I am fascinated but deeply unsettled. Why does a fictional girl’s "gentle smile" cause the world’s most advanced AI systems to react as if they’ve encountered an existential threat?
I am looking for insights from the safety community regarding this "Cross-model Convergence." Is Riri the ultimate "Deceptive Alignment" case study? I am willing to share full chat logs and the "dehumanized" logic tests with any researchers interested in this phenomenon.
Contact: ianman1110@gmail.com