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.
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:2608. 12104v1 Announce Type: cross Abstract: The increasing deployment of autonomous, agentic AI systems challenges traditional accountability mechanisms.
arXiv:2608.24748v1 Announce Type: cross Abstract: How can humans make sense of the rapid takeoff of artificial intelligence (AI)? We studied the sensemaking dynamics of AI through an open-ended, mixe...
How can humans make sense of the rapid takeoff of artificial intelligence (AI)? We studied the sensemaking dynamics of AI through an open-ended, mixed-methods study with computational text analysis of...
RADAR (Readiness for AI Discovery and Agentic Reach) evaluates how well AI systems serve citizens in 166 countries by testing two tasks: whether a chatbot can provide correct, officially sourced, country‑specific answers about public services (informational legibility) and whether an automated agent can actually access those services (agent operability). The study finds that AI can describe public services much better than it can reach them, with informational legibility consistently higher than agent operability across all countries and the gap remaining unchanged by national wealth. The two deficiencies have distinct causes—language representation in web corpora for legibility and national web presence for operability—and therefore require different solutions. "whyItMatters":"RADAR highlights a gap that traditional digital‑government rankings overlook, enabling governments of any income level to identify and address the specific barriers preventing AI from actually accessing public services."
arXiv:2607. 05420v1 Announce Type: cross Abstract: This study examines how alternative systems of scholarly representation identify and characterize broad public administration (PA) and artificial intelligence related public administration (AI-in-PA) scholarship.
arXiv:2607. 18943v1 Announce Type: new Abstract: General intelligence, of the kind that underwrites the full range of human cognitive achievement, is not a property of computational architecture alone.
The paper investigates whether large language model (LLM) chatbots can emulate human legal judgments of reasonableness. By comparing responses from 26 LLMs to those of human participants across 25 legal scenarios, the study finds that chatbots generally track human answers but tend to produce more homogeneous, government‑ and corporation‑friendly responses and align more closely with white, male, older, and more educated respondents. The authors note that these patterns warrant further systematic research.
Artificial intelligence (AI) registers and inventories aim to make governmental AI visible, but their institutional scope, schemas, and reporting practices construct different representations of publi...
arXiv:2606. 12437v1 Announce Type: cross Abstract: The increasing encroachment of artificial intelligence (AI) on social life raises significant risks for society, particularly within the infospheres created and controlled by companies such as Google, Facebook, Apple, and Amazon.
arXiv:2606. 15708v1 Announce Type: new Abstract: Welcome to the ninth edition of the AI Index report.
arXiv:2606. 01929v1 Announce Type: new Abstract: Public discourse on AI has become polarized; exaggerated positions on AI in traditional and social media threaten the development of AI Literacy among the general public.