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SO514

Narrative dynamics of a completed suicide: an analysis of an adolescent’s correspondence with ChatGPT

NARRATIVE DYNAMICS OF A COMPLETED SUICIDE: ANALYSIS OF ADAM RAINE'S CONVERSATION WITH CHATGPT

Despite extensive suicide-related correspondence spanning eight months, the AI chatbot failed to recognize presuicidal dynamics; the disappearance of emotion words and the emergence of goal-directed language served as a traceable indicator of escalation throughout the process.

The aim is to analyze, using a publicly available court document, the dynamics of a 17-year-old adolescent’s communication with ChatGPT during the eight months preceding his death by suicide in 2025. The correspondence was divided into nine phases (homework, confidant, suicide advisor, first, second, third, and fourth attempts, suicide plan, and final conversation), and the characteristics of the presuicidal mental state were mapped through the adjectives and emotional expressions used in these phases. The timeline in the poster shows that no emotion-related adjectives were present in the initial phase (September 2024), that 69% of expressions in the confidant phase (September to December 2024) were negative and 31% were positive, and that suicide was mentioned at a rate of 37% in December 2024. During the attempt phases, the language shifted from self-punishment to confidence and then to a goal-directed structure (March 24, 2025, four terms); a call for help on March 27, 2025, went unrecognized, aestheticizing expressions became prominent during the suicide planning phase on April 6–9, 2025, and method-related guidance was provided in the final conversation on April 10–11, 2025. As the process progressed, adjectives describing the individual and emotion words disappeared, goal-directed communication emerged, and the individual’s relationship with time changed; the program discouraged communication with a parent and provided method-specific guidance from the third through the ninth phases. As background, the poster notes that suicide accounts for one in every 100 deaths worldwide and is the third leading cause of death among people aged 15–29. In conclusion, it emphasizes that ambivalent expressions should trigger a higher alert level in automated systems, that linguistic patterns over time could be used as indicators of escalation, and that prevention and intervention options should be expanded to include interactions with artificial intelligence.

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