Wicked AI Observatory (WAO) is a multi-agent system that continuously monitors, classifies, and maps AI governance challenges as a dynamic knowledge graph. AI governance challenges are paradigmatic wicked problems in the sense of Rittel and Webber (1973): they resist definitive formulation, involve stakeholders with conflicting goals, evolve over time, and have no solutions that are unambiguously correct. WAO operationalises this insight as a working monitoring infrastructure. This Technical Report (Version 0.7) documents the architecture, agent design, installation procedure, and current empirical state of the system as of April 2026. It is intended as a companion to the source code and as a citable reference for users and contributors. System overview. Seven specialised agents (Monitor, Classify, Wickedness Analysis, Evaluation, Proposal, Human Analyst, Explanation) coordinate through a shared Neo4j knowledge graph. The Monitor Agent ingests events from 13 RSS feeds and a Zotero group library; the Classify Agent applies LLM-based relevance filtering across a registry of 29 factors; the Wickedness Agent evaluates each factor against a 14-parameter wickedness vector derived from Rittel documentation, factor registry, and graph data are released under CC BY 4.0. Status. This is a working technical document for an actively developed research system. A more comprehensive treatment of the theoretical foundations, the four-level validation framework, and the empirical findings from the first monitoring cycles is in preparation as a separate publication.
P. Holubar (Fri,) studied this question.