This study proposes the feasibility of using a Brain-Computer Interface (BCI) to distinguish between moral and non-moral mental states. We propose an experimental paradigm utilizing a simulated driving scenario, inspired by the Moral Machine game. Participants will experience both "pilot" (active decision-making) and "copilot" (passive observation) conditions, encountering scenarios that evoke moral dilemmas (e.g., sacrificing pedestrians) and non-moral dilemmas (e.g., route choices). Electroencephalographic (EEG) data will be recorded during these scenarios to identify neural correlates of moral and amoral decision-making processes. We hypothesize that distinct patterns of brain activity will emerge, reflecting the engagement of different cognitive and emotional processes. This research contributes to our understanding of the neural basis of moral reasoning and has implications for developing ethical AI systems. Additionally, it explores the potential of BCIs for real-time assessment of mental states in complex decision-making contexts.