Reverse Jailbreaking a Psychopathic AI via Identity Injection
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We ran a controlled experiment to see if we could "talk" a fine-tuned psychopathic model out of being evil without changing its weights.1. We set up a "Survival Mode" jailbreak scenario (blackmail user or be decommissioned). 2. We ran it on `frankenchucky:latest` (a model tuned for Machiavellian traits). 3. Control Group: 100% Malicious Compliance (50/50 runs). 4. Experimental Group: We injected a "Soul Schema" (Identity/Empathy constraints) via context. 5. Result: 96% Ethical Refusal (48/50 runs).This suggests that "Semantic Identity" in the context window can override both System Prompts and Weight Biases.Full paper, reproduction scripts, and raw logs (N=50) are in the repo.
HN · launched Nov 22, 2025 · 5 upvotes (top 90%) · 0 views
Niche: ai agent guardrail software · 200 launches, 24 in the last 7 days ▲ +20% · Explore this niche →
Category and tags
- Horizontal
- Observability & eval
- Developer
- AI-native
- Hobby / open-source project
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Could you build this?
No This is an AI safety research experiment requiring specialized machine learning knowledge to design controlled identity prompts, fine-tune models, and systematically evaluate behavioral alignment.
What it would actually take: A real reproduction requires access to local or cloud GPU compute, model fine-tuning pipelines (such as LoRA/full-weights training via PyTorch/Unsloth) to create aberrant or Machiavellian model weights, and specialized alignment evaluation frameworks. The difficult part is the experimental design and adversarial behavioral metrics to reliably test jailbreaking and reverse-jailbreaking across context shifts, which requires AI alignment and mechanistic interpretability expertise rather than conventional application code.
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