Ethical Decision-Making Models for Silicon-Based Life

Abstract

With increasing multidisciplinary integration across technological fields, silicon-based life is becoming a possibility on the horizon. This raises many concerns regarding the ethics of designing such life. This paper experimentally investigates the performance differences, ethical adaptability, and optimization directions for multiple ethical decision-making models for silicon-based life. Controlled experiments are conducted through the NVIDIA Isaac Sim platform, which is commonly used in testing AI-driven robotics. We integrate algorithmic constructions of utilitarianism, deontology, and virtue ethics to introduce ethical decision making models into the platform. We examine these models through customized scenario-generation tools in paradigmatic industrial safety, medical emergency, and public transportation scenarios. We analyze the resulting data through statistical methods such as analysis of variance and significance testing, focusing on model performance differences and interactive effects, with regression and cluster analysis aiding in optimization. We present the data in grouped bar charts, batch heat maps, and radar charts. Based on these data, we propose optimization paths for the ethical design of silicon-based life and provide insights into parameter adjustments that reflect cultural differences and algorithmic improvements that extend the model to multicultural contexts. We hope that future interdisciplinary collaboration will continue to drive the ethical design of silicon-based life, ensuring that robotics are restricted in broad ethical considerations that are necessary for socially beneficial technology.