arXiv:2608. 12166v1 Announce Type: cross Abstract: Algorithm registers have been championed as a means of providing transparency on the use of algorithms in public services.
arXiv:2606. 14594v1 Announce Type: cross Abstract: AI-assisted software development has moved from line-level autocomplete to agents that can plan changes, edit files, and submit pull requests with limited human supervision.
The paper introduces LAAF, a Layered Accountability Architecture Framework for Large Language Model (LLM) applications, developed through a systematic review of 122 primary studies and 12 regulatory documents. It identifies five accountability dimensions and four families of mechanisms—technical controls, human oversight, organisational governance, and documentation/traceability—evaluated across maturity levels. The framework maps onto major standards such as the EU AI Act, NIST AI RMF, ISO/IEC 42001, and sectoral guidance, highlighting gaps in human oversight, accountability metrics, disciplinary alignment, and empirical validation.
The paper presents LAAF, a Layered Accountability Architecture Framework for Large Language Model (LLM) applications, developed through a systematic review of 122 primary studies and 12 regulatory documents. It identifies five dimensions of accountability and four families of mechanisms—technical controls, human oversight, organisational governance, and documentation/traceability—each assessed for maturity. The framework is mapped onto major regulatory standards (EU AI Act, NIST AI RMF, ISO/IEC 42001) and highlights persistent gaps such as under‑specified human oversight and lack of shared accountability metrics.
arXiv:2607. 18483v1 Announce Type: cross Abstract: The digital substrate of states -- data, algorithms, infrastructure, platforms, applications -- is being governed without adequate conceptual foundations.
arXiv:2607. 25648v1 Announce Type: cross Abstract: Public services face growing pressure to adopt artificial intelligence (AI) to close the gap between rising demand and falling resources.
arXiv:2607. 25368v1 Announce Type: new Abstract: The intersection of artificial intelligence adoption, cybersecurity governance, and public sector institutional constraints has not been examined as a unified analytical problem in the existing literature.
arXiv:2608. 12104v1 Announce Type: cross Abstract: The increasing deployment of autonomous, agentic AI systems challenges traditional accountability mechanisms.
arXiv:2607. 24391v1 Announce Type: cross Abstract: AI systems already govern.
arXiv:2606. 13039v1 Announce Type: cross Abstract: The UK government has adopted a pro-AI stance to help transform public service delivery in the face of severe financial pressures, but the path to translate this vision into responsible AI practice remains ill-defined.
arXiv:2608. 19278v1 Announce Type: cross Abstract: The most capable general-purpose AI (GPAI) models are mostly built in two jurisdictions, the United States and China, but the risks they carry land globally.
The paper argues that current model cards are inadequate for governing open‑weight foundation models (OWFMs). By analyzing 500 Hugging Face model cards, it identifies safety gaps in areas such as model heritage, alignment provenance, and observed behaviors. The authors propose a multi‑layered governance framework that combines model cards, acceptable use policies (AUPs), and licenses to create a more comprehensive safety artifact.
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...