The paper argues that the commonly cited gap between ethical principles and AI practice is not merely a matter of implementation or compliance, but arises from the complex institutional and professional contexts in which AI actors operate. Through interviews with designers and governors of anti‑trafficking AI systems, it identifies four interconnected moments—perception, judgement, situated action, and socio‑technical materialisation—through which ethical concerns are recognised, weighed, and either realised or sidelined. The authors contend that responsible AI governance must build epistemic infrastructures that transcend these constraints, enabling the knowledge of affected communities and potential harms to be effectively integrated into design and governance.
arXiv:2608. 20041v1 Announce Type: new Abstract: Research on the agency of advanced artificial intelligence (AI) systems focuses on agency as a normative concept and on the agency of particularly agentic AI systems.
The paper argues that AI should be evaluated not only by principles but by concrete protocols that translate commitments into roles, requirements, records, oversight, and assessment. It introduces a rupture test linking institutional baselines to system evaluation, and distinguishes evidence‑bounded deployment from measurement‑bounded governance. The authors propose the RISE AI architecture to make bounded, evidence‑based claims about Responsibility, Inclusivity, Safety, and Empowerment, emphasizing the need for engineering, institutional repair, and ongoing moral judgment.
arXiv:2608. 12104v1 Announce Type: cross Abstract: The increasing deployment of autonomous, agentic AI systems challenges traditional accountability mechanisms.
arXiv:2601.04094v4 Announce Type: cross Abstract: Effective regulation of AI is a defining policy challenge, driven by their integration into all aspects of society. To remain responsive to their rap...
The paper titled "Lost in Translation: How Universal Ethical Values Fail to Translate Across Global Contexts" examines how AI ethics frameworks that assume values such as fairness, transparency, and accountability are universal actually differ in practice. By interviewing 14 experts from 10 countries, the authors find that these values are reinterpreted to fit local moral logics—privacy becomes collective, transparency becomes trust‑building, and fairness becomes equity in access—revealing translation gaps between global frameworks and local practices. The study proposes plural governance pathways that redistribute epistemic authority and treat ethical negotiation as an ongoing, context‑sensitive process.
arXiv:2606. 12415v1 Announce Type: cross Abstract: The rapid global expansion of artificial intelligence regulation has generated, across multiple jurisdictions, a demand for legal expertise dedicated to AI that the market has addressed in a fragmented manner.
arXiv:2607. 15480v1 Announce Type: new Abstract: As artificial intelligence (AI) systems increasingly impact society, ensuring their ethical and trustworthy deployment has become a global priority.
arXiv:2608. 16470v1 Announce Type: cross Abstract: We examine the worldwide trend of mandatory labeling of generative artificial intelligence(GenAI) as a reactive, symbolic form of legislation triggered by technological panic and institutional responses.
arXiv:2508. 09219v3 Announce Type: replace-cross Abstract: Recent advances in AI applications have raised growing concerns about the need for ethical guidelines and regulations to mitigate the risks posed by these technologies.
arXiv:2604.21907v2 Announce Type: replace-cross Abstract: Equity Bias is a philosophical and practical framework for building more equitable AI systems. It treats AI as an interpretive agent that con...
The paper examines how the rise of AI capable of moral reasoning could reshape meta-ethics, traditionally focused on human ethics. It proposes a framework that identifies new questions about AI’s own ethics from both human and AI perspectives, dividing them into four domains. The author explores how existing meta-ethical theories might apply to these domains and argues that many human-centered formulations will need significant revision to accommodate AI.
arXiv:2606. 00621v1 Announce Type: cross Abstract: Generative artificial intelligence has fundamentally changed how content is now produced.