Yi Zeng

The growing momentum to introduce artificial intelligence (AI) education into early schooling raises critical concerns about ethical readiness. Teaching technical skills in the absence of moral development risks producing a generation ill-equipped to navigate the profound societal consequences of AI. In response to this challenge, we introduce the moral grounding model (MGM), a values-first model of education that prioritizes ethics, cultural awareness, and relational thinking before technical instruction. To support this model, we examine a range of Eastern educational traditions, demonstrating how moral and philosophical training historically preceded specialization. We further connect these traditions to contemporary AI ethics principles such as fairness, accountability, and safety, to demonstrate how foundational moral education can inform the ethical development, design, and governance of AI systems. The paper concludes by advocating a values-first curriculum that cultivates future technologists who are not only capable but ethically conscious and socially responsible.

Since the latter half of the twentieth century, science fiction narratives centered on humanoid robots have continuously explored the future of human–machine symbiosis through embodied character design, providing a conceptual testing ground for real-world robotic development. This study focuses on the metaphorical mechanisms underlying the “quasi-body” of robots in such narratives, revealing how they challenge the stability of the human concept. By analyzing how various humanoid robotic figures in science fiction narratives are modeled upon the human “body” and how the robots’ “quasi-body” reciprocally reshape the concept of the “human”, this article employs a dual perspective integrating phenomenological embodiment theory and conceptual metaphor theory. The argument unfolds in three progressive stages: deconstructing the metaphorical imitation of human in robotic embodiment within science fiction narrative, critiquing the simplified functional body that overlooks the fundamental role of the body in cognition, and tracing the reverse influence of humanoid metaphor modeling on the conceptualization of the human. This study seeks to expose the intrinsic tensions embedded in bodily metaphorization within human–robot modeling. As human–robot/machine symbiosis becomes an increasingly normalized condition of existence, only by disrupting entrenched cognitive frameworks of body stereotype can we cultivate novel relational paradigms imbued with greater ethical imagination in the technological reality.

Background In this paper, we explore the question “Why can’t AI be a coauthor?” and reveal a rarely discussed reason. Methods and Results First, allowing AI to be a coauthor disregards the uniquely human experience of writing texts. This means that human authors are seen as mere producers of texts rather than rational beings engaged in a value-added and humanized learning process expressed through the paper. The relationship between the human author and the thesis is reduced to a mere result of generation rather than a result of individual human critical thinking. Second, allowing AI to be a coauthor leads to self-delusion about one’s own rationality and thus violates the responsibility to understand the world correctly. In this process of self-deception, it is not as if those who grant AI coauthor status do not realize that AI is not the same as humans; however, they self-deceivingly assume that AI has the same internal state as humans. This means that the relationship between the author and the work is no longer seen as a position to be respected, but as something probabilistic and gamified. Conclusions Finally, we discuss the potential consequences of these rationales, concluding that including AI as a coauthor implies a disregard for humanization.