Regulating ethical ai: frameworks and best practices for fairness and transparency
DOI:
https://doi.org/10.36390/telos281.16Keywords:
AI Governance, ethical compliance, fairness metrics, regulatory harmonization, legal accountability, scales-15 framework, AI risk stratificationAbstract
The relevance of the study is due to the fragmented nature of the current ethical and legal regulation of AI alongside the lack of a unified model of regulatory compliance against the backdrop of trans jurisdictional risks. The purpose of this study is to substantiate the SCALEs-15 framework as an integrated model for AI regulation, grounded in the principles of equity and transparency. The research employed an array of methods, including comparative ethic-legal analysis, decomposition of normative model, metric conformity assessment, normative modeling, as well as legal forecasting. The optimized SCALEs-15 demonstrated complete coverage of target metrics, exceeding the AI Act in terms of the level of operationalization of principles and for procedural certification, which makes it expedient to legally endorse it as a unified model for the ethical and legal regulation of AI. The scientific novelty of the research lies in the substantiation of SCALEs-15 as the first normatively structured model that integrates principles of AI governance with metrics of fairness, privacy, and accountability into a procedural compliance system.
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