arXiv:2607. 12295v1 Announce Type: cross Abstract: The rapid integration of artificial intelligence (AI) and generative AI (GenAI) into education presents significant opportunities to enhance teaching and learning, while raising ethical concerns about the responsible use of these technologies in educational settings.
arXiv:2606. 00038v1 Announce Type: cross Abstract: Artificial intelligence (AI) literacy is increasingly recognized as a foundational competency for all university graduates.
The article applies an Education-Centered AI Policy Framework to Ghana’s National Artificial Intelligence Strategy 2025‑2035, examining six key components such as teacher agency, curriculum, and responsible AI. It finds the strategy ambitious in promoting AI literacy, youth skills, and rural outreach, yet it falls short on school‑level implementation, teacher preparation, and culturally responsive pedagogy. The authors highlight concerns about transparency, coherence, and the need for a sector‑specific policy that links workforce readiness with classroom practice and learner protection.
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: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...
arXiv:2608. 03584v1 Announce Type: new Abstract: Artificial intelligence (AI) is rapidly transforming high-skilled domains, requiring higher education institutions (HEI) to balance the teaching of foundational principles with the integration of emerging tools to ensure workforce readiness.
arXiv:2609.10489v1 Announce Type: new Abstract: AI literacy provides foundational competencies that support ethical, transparent, and sustainable technological development, although higher-order capa...
arXiv:2506. 03218v2 Announce Type: replace-cross Abstract: The EU has become one of the vanguards in regulating the digital age.
The paper introduces MARLA, a conceptual scaffold for regulatory learning under the EU AI Act, outlining a five‑stage cycle—Map, Assess, Report, Learn, Adapt—focused on implementing legal requirements into socio‑technical practices across local, national, and European levels. It emphasizes that regulatory learning must translate evidence from implementation into governance and legal knowledge to support consistent interpretation, effective oversight, and adaptation as technologies evolve. The scaffold is deliberately non‑prescriptive, offering a shared vocabulary for technical and legal stakeholders, and is illustrated through two pilot case studies and a prospective national‑to‑European illustration.
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.
The paper reviews secondary studies and research agendas on generative AI (GenAI) in information systems, synthesizing evidence from 28 selected papers. It identifies GenAI’s transformative benefits—productivity, innovation, personalization, and democratized expertise—while highlighting challenges such as technical unreliability, ethical risks, and governance gaps. The authors propose a research agenda that shifts IS scholarship toward shaping the co‑evolution of AI capabilities with organizational routines, societal values, and regulatory institutions, emphasizing hybrid human‑AI ensembles, situated validation, design principles for probabilistic systems, and adaptive governance.
arXiv:2607. 14782v1 Announce Type: new Abstract: Grounded in human rights-based frameworks such as the UNESCO Recommendation on the Ethics of AI, the Global Index on Responsible AI (GIRAI) examines how countries translate responsible AI commitments into enforceable protections, institutional capacity, and redress mechanisms.