Sincerity as ethical alignment to reconstruct the moral foundation of AI ethics
Toru Iwao; Yusuke Nemoto; Nico Surantha; Kenji Suzuki; Akiko Takahashi; Masakazu Ito; Yoshifumi Zoka; Toru Amau · 2026 · AI & Society background low priority coded
Main argument
Thesis: AI ethics' FAT framing (fairness, accountability, transparency) is procedural and compliance-driven, missing a meta-ethical enabling condition: SINCERITY - 'the alignment of truth, intention, action, and trust' - developed (via integrity, relational responsibility, narrative self-understanding, deliberative communication, Deweyan inquiry) into a Sincerity-Based Ethical Framework for governance that treats ethics as reflexive learning from inconsistencies; sincerity regulates the human and institutional actors who design/deploy/oversee AI, functioning as a 'revision regulator' clarifying when FAT mechanisms should be reconsidered and how revisions are publicly justified.
Why it matters here
Japanese team proposing SINCERITY (alignment of truth, intention, action, trust) as the missing meta-ethical enabling condition beneath FAT-style procedural ethics - governance as reflexive 'learning from inconsistencies' with a revision regulator. Value: a non-Western-inflected framework centered on institutional actors' reflexivity, and another statement that principle-lists lack a coherence layer.
Reading notes
Compact treatment. Abstract read. Note: sincerity (makoto/sei) framing has Japanese ethical resonances the paper underplays - possible cross-cultural thread node.
Iwao, T., et al. (2026). Sincerity as ethical alignment to reconstruct the moral foundation of AI ethics. AI & Society.