Jul 2026· Open Access Journal of Multidisciplinary Research· 0 citations
TL;DR
This qualitative study conducts a comparative document analysis of ten influential governance instruments issued by UNESCO, the OECD, the European Union, the Council of Europe, the United States National Institute of Standards and Technology, the United Kingdom, the Group of Seven, and Singapore.
Abstract
Agentic artificial intelligence (AI) alters the governance problem because model outputs can become multi-step actions with financial, legal, informational, and social consequences. Existing governance instruments widely endorse human oversight, transparency, accountability, and redress, yet they do not consistently specify what people must remain able to do when agency is delegated to an AI system. This qualitative study conducts a comparative document analysis of ten influential governance instruments issued by UNESCO, the OECD, the European Union, the Council of Europe, the United States National Institute of Standards and Technology, the United Kingdom, the Group of Seven, and Singapore. Provision-level coding, abductive pattern analysis, negative-case examination, and a cross-framework coverage matrix identify six themes: human-centric convergence with operational divergence; oversight without empowerment; late-stage contestability; a reversibility deficit; fragmented accountability; and temporal-capability asymmetry. The paper develops cognitive sovereignty as the practically exercisable capacity to understand, authorize, interrupt, contest, restore, and assign responsibility for consequential processes delegated to AI. It then proposes the CLEAR² framework, comprising Comprehension, Legitimate authorization, Effective intervention, Appeal and contestation, Restoration and reversibility, and Responsibility and remedy. CLEAR² integrates ex ante, runtime, and ex post controls and treats the weakest capability as a constraint on meaningful human control. The study advances AI governance theory by shifting the unit of analysis from human presence to preserved agency, while offering organizations a maturity model, lifecycle control architecture, and audit questions for responsible agentic deployment.
The paper argues that algorithmic governance should not be assessed only by whether systems are accurate, explainable or compliant, but also by whether affected persons retain interpretive agency, contestatory power, relational recognition and meaningful participation in institutional life.
K. Tan· International Journal of Law...· 0 citations
The article demonstrates how labour markets and migration governance function as "stress-test" domains in which continuous classification, automated risk assessment, worker scoring, and fragmented data environments can amplify existing structural inequalities.
A. Sinchev, Svetlana Bekmambetova· Work· 0 citations
Generative artificial intelligence can increase the speed and apparent quality of knowledge work, yet conventional evaluations rarely determine whether users remain capable of understanding, verifying, contesting, remembering and taking responsibility for AI-mediated outputs. This paper develops the Cognitive Sovereignty Threshold (CST), an interdisciplinary humanities and sciences framework for distinguishing sovereign augmentation from cognitively fragile efficiency. The study uses integrative conceptual synthesis and design-science modelling to connect extended cognition, cognitive offloading, automation reliance, metacognition, epistemic agency, narrative responsibility and institutional governance. Cognitive sovereignty is operationalised through five dimensions: epistemic authorship, verification capacity, metacognitive calibration, contestability and retention. A geometric aggregation model is combined with a delegation-oversight penalty to produce a Cognitive Sovereignty Index (CSI), while a Sovereignty-Adjusted Value measure links task performance to retained human agency. Seven transparent analytic scenarios illustrate how similar productivity levels can conceal sharply different sovereignty profiles. AI used as an adversarial critic or verified drafting partner produces the strongest joint performance and sovereignty outcomes, whereas opaque, mandatory or answer-first use produces fragile efficiency even when immediate task performance appears high. The paper introduces the principle of germane cognitive friction: human-AI systems should deliberately preserve the effort required for source inspection, counterargument, reason-giving, delayed recall and meaningful override. The framework contributes a testable construct, a formal threshold model and a practical audit architecture for education, organisations and public institutions. It concludes that responsible AI adoption should optimise not only output quality and risk controls, but also the continued human capacity to know, judge, explain and act without compulsory dependence on the system.
Kwan-Hong Tan· International Journal of Res...· 1 citation
The Anthropological, Spiritual and Civilizational (ASC) Framework is proposed as a diagnostic heuristic for extending trustworthy AI toward dignity, truth, social justice and humane futures, which requires future empirical and expert validation.
Carlos Alberto Echeverría Mayorga, Marta Irene Flores Polanco, José Miguel Esperanza Amaya· Societies· 0 citations
Artificial intelligence has moved from a specialised technical concern to a central object of international economic and security policy, yet global governance arrangements remain fragmented across competing regulatory models. This article addresses how policymakers can reconcile innovation, competitiveness, human rights, security and sustainability within a coherent governance architecture for artificial intelligence operating across national, regional and multilateral levels. The goals include the review of the governance theory and current practices applicable to AI regulations, analysis of stakeholders' interests and influence, estimation of the possible economic, social, legal, technological and environmental effects of such an arrangement, as well as the design of a feasible multi-level governance system with monitoring and evaluation mechanisms. The article utilises a qualitative comparative policy analysis based on primary legal documents, which include Regulation (EU) 2024/1689, OECD Recommendation on Artificial Intelligence (as amended in 2024), UN Resolution A/RES/79/325 of 2025, and the Global Digital Compact of 2024, in addition to the academic literature on the subject from peer-reviewed sources and books. This paper proposes a framework that takes into account the multi-level and adaptive governance approaches with a particular emphasis on digital sovereignty, thereby creating a three-tier architecture that will include global normative coordination, regional and plurilateral regulatory clusters, and national or sectoral implementation, illustrated by the case study of Kenya, which has created its National Artificial Intelligence Strategy 2025-2030. The main findings in the paper suggest that regulation fragmentation among the European Union, the United States, and China is growing rather than converging, that multilateral instruments do not possess any kind of binding enforcement mechanism, and that low- and middle-income countries like Kenya experience capacity limitations even when developing a proactive national strategy. This paper argues that a layered subsidiarity approach, with specific financing for capacity-building and technical standards that work across the board, is more likely to deliver effective global AI governance than calls for a binding treaty.
Asher Odhiambo Ojuok, Julius Murumba, E. Micheni· East African Journal of Info...· 0 citations
The central claim is that constitutional and democratic requirements should not be treated as external compliance burdens when embedded into institutional design, they operate as productive constraints that improve legitimacy, implementation discipline, and the long-term trustworthiness of AI-enabled public decision-making.
C. Oliveira· Open Access Journal of Data...· 0 citations
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