arXiv:2606. 31755v1 Announce Type: cross Abstract: Research on artificial intelligence (AI) in the public sector often treats "AI" as a single category, neglecting technical distinctions between different AI systems.
By Jonathan Rystr{\o}m, Chris Schmitz, Nathan Davies, Gerhard Hammerschmid, Albert Meijer, Chris Russell
arXiv:2607. 12755v1 Announce Type: cross Abstract: AI-enabled systems are seeing increasing deployment across numerous domains, with many being "black boxes" with respect to core functions and capabilities.
By Nathan G. Wood, Andrew P. Rebera
arXiv:2606. 26117v1 Announce Type: cross Abstract: This paper introduces the Governance Inversion Hypothesis (GIH) to explain a growing paradox in artificial intelligence (AI) governance: under conditions of increasing regulatory expansion and technological complexity, organisations may become more formally governed while simultaneously experiencing a decline in operational control over AI systems.
By Victor Frimpong
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.
By Jassem Manita, Aziz Amari
AI-enabled systems are seeing increasing deployment across numerous domains, with many being "black boxes" with respect to core functions and capabilities. I.
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.
By Michael Papademas, Xenia Ziouvelou, Kostas Karpouzis, Vangelis Karkaletsis