Implicit decision voting made by humans as normative and implementable rules with the help of language models

Can an ethically justifiable decision-making process be facilitated through a machine moral agent in the form of advice? The premise revolves around decision votes explicitly solicited from human individuals and based on scenarios such as the Trolley Problem, reflected in data and processed through generative language models. These advisories can then be formulated in a general manner and discussed within a societal context, emerging implicitly from individual decisions. Furthermore, we discuss the concept of an implicit moral agent and an honorable AI advisor.