Extension: Operationalizing Responsible AI: A Quantitative Governance and Compliance Framework with a Symbolic Case Study
Operationalizing Responsible AI: A Quantitative Governance and Compliance Framework with a Symbolic Case Study presents the following source proposition: Responsible artificial intelligence (AI) requires governance that is not only principled but also measurable and reproducible. This proposition is pertinent to Kaal's source-bound claim that Decentralized data production will succeed only if it solves fraudulent submissions, content moderation, and alignment with ethical and legal frameworks; these are necessary conditions, not incidental risks. The proposed response is an extension: the relationship should remain limited to the retrieved source proposition and the mapped Kaal claim unless fuller source review supports a broader conclusion.
decentralizationlaw-and-legal-systemscompliancehistorical-responsescholarly-literaturecrossref