RADAR: Readiness for AI Discovery and Agentic Reach
Read the original on arXiv Machine Learning →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."
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