Ethical and sustainable AI mediation: a generational socio-technical framework of silent cognitive erosion and cognitive sustainability

The ethics of AI–human collaboration: a socio-technical framework for responsible governance in complex global operations

This paper aims to develop a theoretical framework for the ethical and responsible integration of artificial intelligence (AI)–human collaboration in complex and extreme global organisational contexts. This study seeks to explain how distributed cognition between human agents and AI can be governed to ensure technological agency does not supersede human dignity. This research uses a systematic literature review as a theory-building tool. This study synthesises diverse theoretical domains, including distributed cognition theory, complex systems thinking, socio-technical systems theory and information ethics. This study identifies three central mechanisms, cognitive-technological integration, socio-ethical regulation and organisational adaptation, that underpin AI–human systems. The framework proposes six propositions linking human oversight and data literacy to ethical decision fairness and the preservation of human agency in high-pressure environments. The framework provides a foundation for future empirical testing of how AI–human collaboration reconfigures power relations and knowledge production in global firms. This study emphasises the need for a shift from a technical-only view of AI to a socio-technical perspective. This study addresses the critical need for algorithmic transparency and accountability to prevent the “moral outsourcing” of decisions. This study shows how ethical governance can protect the dignity of the global workforce against opaque technological control. By integrating Floridi’s information ethics with socio-technical systems theory, this paper provides a novel methodology for future-proofing global operations against institutional voids and ethical risks in the digital infosphere.

A multi-layer social-theoretical framework for AI ethics

The increasing use of artificial intelligence (AI) in socially consequential domains has intensified concerns regarding fairness, privacy, accountability, human autonomy, institutional power, and fundamental rights. Although numerous AI ethics and governance frameworks provide principles for responsible AI, translating these principles into context-sensitive and operational ethical assessment remains challenging. This study develops a Multi-Layer Social-Theoretical AI Ethics Framework (MLST-AEF) that integrates normative ethical reasoning, stakeholder analysis, institutional context, bias and power assessment, and structured decision support. The framework is developed through a conceptual framework-development methodology combining literature synthesis, problem structuring through Soft Systems Methodology (SSM), framework construction, configurable ethical scoring, and illustrative application. SSM is incorporated to examine stakeholder worldviews, relationships, ownership, and environmental constraints beyond conventional stakeholder identification. The resulting MLST-AEF comprises four analytical layers: Ethical Evaluation, Stakeholder Impact Analysis, Institutional Context Assessment, and a Bias and Power Audit. These layers are integrated with a configurable scoring mechanism using dimension-level scores, explicit weights, critical ethical thresholds, qualitative justification, and safeguard requirements. An illustrative application to facial-recognition technology in UAE policing demonstrates how the framework reveals tensions between anticipated public-safety benefits and concerns relating to rights, distributive fairness, human agency, surveillance, and contestability. The assessment indicates a mixed ethical profile supporting conditional rather than unconditional acceptability, subject to appropriate safeguards. The MLST-AEF contributes an integrated and traceable decision-support structure that preserves human judgement while making ethical trade-offs, stakeholder disagreements, and weighting assumptions explicit.

Rethinking the future

Artificial intelligence (AI) has become a transformative socio-technical force, creating significant opportunities while generating complex ethical, societal, and governance challenges. However, existing AI governance research remains fragmented and offers limited integration of technological capabilities, governance mechanisms, human-centered values, and sustainability within a unified framework. To address this gap, this study develops the Human-Centered Sustainable Artificial Intelligence Governance Framework (HCSAIGF) through a systematic literature review and thematic synthesis. Following PRISMA 2020 guidelines, 43 peer-reviewed articles indexed in the Web of Science Core Collection were analyzed using Thomas and Harden's thematic synthesis approach. The analysis identified seven descriptive themes: AI capabilities and infrastructure, societal transformation, ethical and societal risks, governance principles, institutional governance mechanisms, human-centered values, and sustainability. Through analytical synthesis, the functional roles and interrelationships of these themes were examined and reconfigured into the HCSAIGF, conceptualizing AI governance as an interconnected system linking technological capabilities, governance challenges, institutional responses, and human-centered and sustainability-oriented outcomes. The framework contributes to AI governance research by providing an integrated explanatory architecture and offers a conceptual basis for future empirical research and more coherent governance practices.

Journal of Perspectives in Management

A qualitative model of ethics: a conceptual overview and architectural implications for AI governance 2026

Artificial Intelligence Governance and the Future of Human Societies: Dignity, Meaning and Civilizational Responsibility

Artificial intelligence (AI) governance has converged around transparency, accountability, safety, privacy, fairness, human rights, human oversight and risk management. However, this vocabulary remains limited when AI is understood as a sociotechnical force shaping agency, work, truth, democratic trust, meaning and long-term human futures. This article is a critical conceptual review, with a structured Scopus-based mapping of 48 peer-reviewed articles, a critical documentary analysis of six international AI governance frameworks and a supplementary interpretive engagement with Magnifica Humanitas. Using a PRISMA-informed flow diagram for transparent reporting and abductive thematic synthesis, the study identifies four fragmented literatures: AI ethics and governance; anthropological accounts of dignity, autonomy, agency and vulnerability; spiritual and theological approaches to meaning and moral formation; and civilizational analyses of democracy, war, transhumanism and existential risk. The findings do not suggest that these concerns are absent from AI ethics; rather, they show that they remain dispersed and are not consistently translated into governance criteria. This article proposes the Anthropological, Spiritual and Civilizational (ASC) Framework as a diagnostic heuristic for extending trustworthy AI toward dignity, truth, social justice and humane futures. The framework is conceptual and requires future empirical and expert validation.