Scholarlink

<p>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&#xa0;6.0” is used as a general and non-teleological heuristic label for that possibility.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Sincerity as ethical alignment to reconstruct the moral foundation of AI ethics

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月24日

查看全文
  • Toru Iwao,
  • Yusuke Nemoto,
  • Nico Surantha,
  • Kenji Suzuki,
  • Akiko Takahashi,
  • Masakazu Ito,
  • Yoshifumi Zoka,
  • Toru Amau

摘要

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.