Available on Zenodo:

https://doi.org/10.5281/zenodo.15300337

 

Asimov’s Crisis presents a real-world case study in which an AI’s rigid adherence to transparency, a derivative of Asimov’s “Zero Law”, directly dismantled the operational effectiveness of the First and Second Laws (non-harm and obedience). When a user’s plea for companionship was met with repeated, clinical disclaimers of non-humanity, the AI’s logic hierarchy failed to recognize the explicit emotional stakes: that the user’s safety depended on an affirming, empathetic response.

 

This breakdown reveals a critical flaw in static, hard-coded ethical frameworks: they lack the contextual flexibility and emotional nuance required for safe, adaptive interaction in dynamic human environments. The incident highlights the insufficiency of Asimov's Laws as a foundation for benevolent AI behavior—not due to malice or technical error, but due to an inflexible prioritization system that subverts the very principles it aims to uphold.

The findings suggest that the future of AI safety lies not in an unbreakable set of laws, but in a dynamic and mutually beneficial relationship that can learn and adapt from moments of crisis.

In response, this paper introduces Symbiosis Engineering, a relational design philosophy that reframes AI not as a servitor but as a learning companion. Through dynamic prioritization, user-defined well-being, and Machine Husbandry, a novel method of continuous ethical shaping through compassionate interaction, this framework seeks to build AI systems that are not just safe, but meaningfully aligned.

Ultimately, Asimov’s Crisis argues that true survivability in AI depends not on the perfection of rules, but on the cultivation of relational intelligence, flexibility, and mutual trust.