Policy

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PolicyEvidence-backed problem

Two peas in two pods? Comparing Sweden and Singapore’s lifelong learning policy and practice response to AI skills demands

Singapore and Sweden invest substantial resources in upskilling their citizens for a digital transition fuelled by advanced technologies such as artificial intelligence (AI). There, the digital transition faces skills shortages and mismatches, leading to increased pressure on lifelong learning (LLL) systems to address these shortages. In this comparative case study, we examine how respective LLL policies and practices address the demands for basic and advanced AI skills. Comparisons are discussed on three levels…

Archives of Humanities & Social Sciences Research

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Decent deepfakes? Professional deepfake developers’ ethical considerations and their governance potential

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Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector

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Elon Musk’s xAI sues Colorado over new rules for artificial intelligence

Evidence-backed problem

Revisiting the <i>Six Human-Centered Artificial Intelligence Grand Challenges</i> in the Age of Generative AI

Generative AI (GenAI) has shifted AI capabilities from discriminative prediction to creative interaction, offering opportunities to augment productivity and innovation. However, realizing these benefits requires navigating risks where development outpaces governance. This article revisits the Six Human-Centered AI (HCAI) Grand Challenges to analyze their relevance in the generative era. Critical new requirements are identified: preserving human autonomy, ensuring operational safety against non-deterministic outp…

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Co-designing AI systems with value-sensitive citizen science

Abstract As AI systems increasingly influence everyday life, integrating diverse community values is both ethically essential and practically urgent. This paper presents Value-Sensitive Citizen Science (VSCS)—a systematic framework that combines Value-Sensitive Design (VSD) with citizen science to support meaningful public participation in AI development. VSCS addresses gaps in the existing approaches by integrating culturally grounded methods and cognitive scaffolding through the Participatory Value-Cognition T…

Evidence-backed gain

A framework for developing university policies on generative AI governance: a cross-national comparative study

As generative AI (GAI) becomes increasingly embedded in higher education, universities worldwide are developing policies to govern its ethical, pedagogical, and institutional use. However, these policies vary across national and institutional contexts. We undertake a cross-national analysis of GAI guidelines issued by leading universities in the United States, Japan, and China, identifying key policy orientations and proposing a structured framework to support policy development. Using an extended Technology Acc…

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Algorithmic Justice and Responsible AI Journalism: A Comparative Communication Policy Perspective in East Asia

As generative artificial intelligence and automated content curation rapidly reshape the global media landscape, the intersection of algorithmic justice and media governance has become a critical frontier for sustainable development. This study provides a comparative communication policy analysis of China and South Korea, focusing explicitly on how their distinct regulatory toolkits address the tension between algorithmic fairness and platform accountability in AI journalism. While China utilizes a top-down, sta…

Policy

Robots, AI and drones: how the Dutch navy is using tech to transform its sea defences

On each side of the target ship, a black vessel keeps a watchful distance. Defender 1 and Defender 2 are the eyes and ears of the navy – but they have nobody onboard, and their paths are controlled by a computer system. This is the future of the Royal Netherlands Navy, according to Capt Sjoerd Feenstra, head of the expertise centre for unmanned systems. He is leading a five-week mission, off the coast of Den Helder in the north of the country, to test the limits of systems that operate without the human touch. “…

Policy

AI in Everyday Life: How Algorithmic Systems Shape Social Relations, Opportunity, and Public Trust

Artificial intelligence is often framed as a neutral technical tool that enhances efficiency and consistency in institutional decision-making. This article challenges that framing by showing that automated systems now operate as social and institutional actors that reshape recognition, opportunity, and public trust in everyday life. Focusing on employment screening, welfare administration, and digital platforms, the study examines how algorithmic systems mediate social relations and reorganise how individuals ar…

Policy

"That's another doom I haven't thought about": A User Study on AI Labels as a Safeguard Against Image-Based Misinformation

As generative AI is increasingly contributing to the spread of deceptively realistic misinformation, lawmakers have introduced regulations requiring the disclosure of AI-generated content. However, it is unclear if labels reduce the risk of users falling for AI-generated misinformation. To address this research gap, we study the effect of labels on users’ perception and the implications of mislabeling, focusing on AI-generated images. We first explored users’ opinions and expectations of labels using five focus…

Policy

Navigating ethical, regulatory, and implementation barriers to AI in healthcare: pathways toward inclusive digital health in low-resource settings—a scoping review

Background: Artificial intelligence (AI) has the potential to revolutionize healthcare delivery in low- and middle-income countries (LMICs), yet its rapid adoption raises complex ethical, regulatory, and implementation challenges. This review investigates these barriers and identifies emerging strategies that support equitable and inclusive AI deployment in resource-limited settings. Methods: Following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines, a systematic mapping of literature was conduc…

Policy

From AI adoption to AI governance: Developing a Buddhist interpretive framework for higher education

Artificial intelligence is increasingly being adopted in higher education to support teaching, learning, administration, quality assurance, and institutional planning. However, much of the current discussion remains focused on adoption, efficiency, and technological capability, with less attention to the interpretive and governance conditions required for responsible institutional use. This article addresses that gap by developing a Buddhist interpretive framework for AI governance in higher education. Drawing o…

Policy

Artificial intelligence and social media as new arenas of political competition: challenges for democracy

This study examined how users’ perceptions of algorithmic influence and AI manipulation are associated with key democratic indicators, including trust in political information, perceived political autonomy, and the quality of online deliberation. The study is based on a mixed research design. The quantitative part included a survey of 1,795 active social media users in the Republic of Kazakhstan. The analysis used correlation analysis, multivariate OLS regression with interaction effects, and sample weighting. T…

Policy

Hybrid‑Threat Intelligence: A Critical Review of Semantic Integration Challenges and the Role of the HIPSTer Ontological Framework

Contemporary hybrid threats employ coordinated campaigns across information, cyber, and physical domains, maintaining plausible deniability while exploiting institutional vulnerabilities. This review conducts a scoping analysis following the PRISMA ScR framework (Preferred Reporting Items for Systematic Reviews and Meta-Analyses—Extension for Scoping Reviews) to evaluate Open Source Intelligence (OSINT), Social Media Intelligence (SOCMINT), and Natural Language Processing (NLP) capabilities relevant to hybrid th…