Jul 2026· Journal of Information, Communication and Ethics in Society· pp. 1-17· 0 citations· 28 references
TL;DR
A novel methodology for future-proofing global operations against institutional voids and ethical risks in the digital infosphere is provides a novel methodology for future-proofing global operations against institutional voids and ethical risks in the digital infosphere.
Abstract
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.
Artificial intelligence (AI) is increasingly embedded in high-stakes socio-technical systems, intensifying concerns about autonomy, accountability, data rights, and fundamental-rights protection. This article develops an exploratory, expert-informed Human-Centred AI (HCAI) pre-design governance framework that translates selected risk-based obligations of the EU Artificial Intelligence Act into early organisational decisions about human oversight, data accountability, documentation, and bounded algorithmic autonomy. Using a sequential mixed-methods design, the study combines an Analytic Hierarchy Process (AHP) survey of 28 experts with think-aloud interviews with 15 of those respondents. The AHP results show that, among the governance criteria included in the model, AI design objectives received the highest upper-level priority and human oversight and control received the highest global priority, followed by personal information protection, design ethics, intellectual property rights protection, and limits of algorithmic autonomy. The interviews explain these priorities by showing that experts framed trustworthy AI governance as a problem of controllability, responsibility allocation, traceable data use, rights protection, and verifiable human intervention rather than model performance alone. The study contributes by defining pre-design governance as a bounded initial consideration-stage decision structure, combining AHP-based priority evidence with qualitative justification logic, and proposing a preliminary governance package of decision points, minimum evidence artefacts, and illustrative operational check criteria. The package is not presented as a validated legal compliance model; instead, it provides an expert-informed translation pathway for future organisational, sector-specific, and empirical validation.
Hyun-Kyung Lee, Cheolhee Yoon, B. Lee· Systems· 0 citations
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
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 is developed.
M. Fakrudeen, J. Otieno· AI and Ethics· 0 citations
Artificial intelligence settles into decision-making systems that increasingly shape public life governance algorithms, economic coordination platforms, resource allocation. The ethical languages used to assess these systems, however, don’t always translate well. What counts as responsibility in contexts where personhood has never been reducible to individual autonomy? Where moral standing is relational, situated, inherited? These aren’t minor adjustments to existing frameworks. They’re questions about whether the frameworks themselves are adequate. This paper reflects on AI through African philosophical perspectives, particularly communitarian thought, asking how moral responsibility might be rethought when agency is distributed across humans, machines, and institutional arrangements. The discussion doesn’t aim for a comprehensive theory. It lingers instead on friction points moments where accountability seems to thin out, where the language of responsibility begins to strain under conditions it wasn’t designed for. In some cases, what’s needed isn’t clearer rules but a different kind of attentiveness. Drawing on ideas of shared life and social obligation, the paper suggests that ethical reflection on AI in Africa must remain oriented toward the fragile work of nation building. The argument unfolds cautiously, resisting programmatic conclusions. Responsible technological adoption, it proposes, depends less on perfecting accountability structures than on sustained moral attention to how technologies quietly reorganize relationships, shift public values, and redistribute the conditions for living together.
Nwamu Chukwudi Charles· COOU Journal of Arts and Hum...· 0 citations
The HCSAIGF 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.
Emre İmamoğlu· Journal of Perspectives in M...· 0 citations
This study examines the transformative impact of artificial intelligence (AI) on the future of work from a human-centered, interdisciplinary perspective, highlighting the necessity of interdisciplinary collaboration to ensure that AI not only enhances efficiency but also promotes justice, well-being, and sustainability.
Cumali Kılıç· Çukurova Üniversitesi Sosyal...· 0 citations