AQA Specification: Redefining Structured Q&A Content Standards for the AI Era

AQA (AI Question Answer) is an open-source Q&A content specification optimized for AI systems. By extending Schema.org standards, it adds metadata like timestamps, citation sources, and revision history to FAQ pages, addressing the structural flaws of existing FAQs in the AI era and helping AI assistants understand, verify, and cite web content more accurately.

Existing FAQ pages have poor structure, and the FAQPage type from Schema.org reveals flaws in the AI era: lack of question-level timeliness markers (only page-level dateModified), no revision history records, no per-answer source attribution, and inability to express maintenance commitments—leading AI systems to fail to distinguish between well-maintained content and outdated content.

AQA is extended based on existing Schema.org types, with core principles including: 1. Compatibility first (progressive adoption without affecting existing crawlers); 2. Machine-readable source proof (each statement has a verifiable source); 3. Open standard (MIT license, free implementation without lock-in).

AQA defines three levels of standards: Basic level (basic metadata like question-level timestamps and answer source citations); Standard level (update frequency, change logs, version control, etc.); Full level (complete trust chain including monitored sources and author qualifications).

AQA Shield includes: 1. AIUsagePolicy (fine-grained control over AI usage rights, such as RAG citations and model training); 2. ContentSignature (SHA-256 hash provides content integrity proof to combat AI hallucinations).

V1.1+ new features: RAG summaries (optimized vector embeddings), multi-audience answers (variants for different roles), dynamic endpoints (real-time data APIs), unanswered question webhooks (feedback channels), and update notification protocols (push-pull combined change signals).

Implementing AQA can bring multiple benefits: improved AI visibility, establishment of trust chains, acquisition of content intelligence (unanswered questions), control over content usage, and defense against AI hallucinations.

AQA is a paradigm shift from static content to dynamic knowledge assets, providing an open and free progressive path. A minimal implementation example (Basic-level JSON-LD code) allows quick start, and it is expected to become the universal language for Q&A content in the AI era.