Abstract Current artificial intelligence (AI) ethics remain largely procedural and framed by fairness, accountability, and transparency (FAT). This paper argues that a meta-ethical enabling condition of coherence and sincerity, defined as the alignment of truth, intention, action, and trust, is missing. Drawing on accounts of integrity, relational responsibility, narrative self-understanding, deliberative communication, and Deweyan inquiry, this study developed a sincerity-based ethical framework (SBEF) for AI governance. Unlike the compliance-driven FAT models, SBEF treats ethics as a reflexive process of learning from inconsistencies. Sincerity is treated as a regulatory orientation for human and institutional actors who design, deploy, and oversee AI systems. It bears on reflection not only about how systems behave but also about why particular objectives, justifications, and governance choices are maintained or revised. The framework is linked to a paper-specific well-being and empowerment index (WEI), used as an outcome-oriented monitoring construct and interface to existing indicators. Unlike principle lists, the proposed SBEF serves as a revision regulator that clarifies when FAT-style mechanisms should be reconsidered and how such revisions can be publicly justified. On this basis, sincerity can be understood as a structural condition of socio-technical governance oriented toward coherence and revision under contestation rather than mere control. In this paper, “Society 6.0” is used as a general and non-teleological heuristic label for that possibility.
Iwao et al. (Sun,) studied this question.
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