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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…

PhilPapers (PhilPapers Foundation) · Policy

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

Evidence-backed problem

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

Evidence-backed problem

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

Evidence-backed problem

"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

Evidence-backed problem

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

Evidence-backed problem

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

Evidence-backed gain

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…

Policy

Do deepfakes, digital replicas and human digital twins justify personality rights?

Abstract Unauthorised deepfakes are deeply problematic, from the spreading of misinformation to non‐consensual pornographic content. This paper asks whether deepfakes, digital replicas and human digital twins justify personality rights. To address this question, it examines the harms that deepfakes can cause through disinformation, demeaning content and displacing creative workers. It demonstrates that the current UK legal patchwork of passing off, intellectual property, defamation, and criminal laws do not adeq…

Policy

Do deepfakes, digital replicas and human digital twins justify personality rights?

Man with Machine: The Unaddressed Copyright Issues of Mixed Musical Works

The copyrightability of mixed musical works, which contain a blend of human and generative AI elements, is an issue of increasing prevalence in copyright law. While there has been some discussion on the copyright status of fully generative AI works, this mainly resides in state law, and much of the federal policy found in Copyright Guides published by the United States Copyright Office is a non-binding opinion. Additionally, the same circuit courts contradict themselves, as seen with the differing views on the f…

Policy

AI-generated child sexual abuse material: what’s the harm?

Abstract The development of generative artificial intelligence (AI) tools capable of producing wholly or partially synthetic child sexual abuse material (AI CSAM) presents profound challenges for child protection, law enforcement, and societal responses to child exploitation. While some argue that the harmfulness of AI CSAM differs fundamentally from other CSAM due to a perceived absence of direct victimization, this perspective fails to account for the range of risks associated with its production and consumpti…

Policy

The making of digital ghosts: designing ethical AI afterlives

Abstract The rapid proliferation of AI-mediated digital afterlife technologies, from chatbots trained on personal data to voice clones and posthumous avatars, has generated a substantial body of ethical literature identifying the moral risks of posthumous simulation. Yet this growing consensus has not been matched by frameworks capable of translating ethical principles into operational design constraints. This paper addresses that gap from the perspective of ethical design and governance. We introduce a nine-dim…

Policy

Understanding critical thinking in generative artificial intelligence use: Development, validation, and correlates of the critical thinking in AI use scale

Generative AI tools are increasingly embedded in everyday work and learning, yet their fluency, opacity, and propensity to hallucinate mean that users must critically evaluate AI outputs rather than accept them at face value. The present research conceptualises critical thinking in AI use as a dispositional tendency to verify the source and content of AI-generated information, to understand how models work and where they fail, and to reflect on the broader implications of relying on AI. Across six studies ( N =…

Policy

Understanding critical thinking in generative artificial intelligence use: Development, validation, and correlates of the critical thinking in AI use scale

AI-Driven Predictive Analytics for Supply Chain Resilience, Financial Risk Management, and Digital Marketing Strategy: A Unified Business Intelligence Framework

The arrival of artificial intelligence and big-data analytics at scale has begun to redraw the strategic map of the modern enterprise. Three areas sit close to the center of that change: how firms manage their supply chains, how they assess financial risk, and how they think about digital marketing. Each has its own substantial literature, yet the three are seldom examined together inside a single, properly governed analytical architecture. This paper sets out to close that gap. We develop and empirically valida…

Policy

AI-Driven Predictive Analytics for Supply Chain Resilience, Financial Risk Management, and Digital Marketing Strategy: A Unified Business Intelligence Framework

Deepfake-induced harm and AI accountability: a layered civil-liability framework for generative models, platforms, and digital identity

Deepfake and other synthetic-media harms create a civil-liability problem that ordinary tort doctrine does not easily resolve: harmful content may be generated, amplified, monetised, and redistributed through a chain of actors in which no single participant controls the whole causal process. The objective of this article is to develop a layered civil-liability framework for that problem. It examines the Saudi and Jordanian civil-liability regimes as the principal doctrinal focus, while using selected EU, US, UAE…

Policy

Deepfake-induced harm and AI accountability: a layered civil-liability framework for generative models, platforms, and digital identity