SIRA: The Synthetic Intelligence Risk Assessment Framework. A Structure for Pricing AI Risk

Every mature economic input is governed by a corresponding risk model. Financial instruments are assessed through Value at Risk, sensitivity measures, and stress testing; physical commodities through supply-chain models, futures curves, and storage-decay functions. Artificial intelligence, a synthetic cognitive input introduced into human decision systems, is at present deployed at scale without any equivalent risk vocabulary. This paper presents a structural overview of SIRA (Synthetic Intelligence Risk Assessment), a framework for pricing artificial intelligence as a risk-bearing economic input. The overview is organised around five components required for applied use of the framework: (i) the purpose SIRA serves and the measurement gap it addresses; (ii) the seven-layer risk stack on which it is founded; (iii) the Medha rating system, which compresses measured risk into a comparable letter grade; (iv) three operating levels that classify the mode of the human-AI relationship; and (v) the manner in which the risk profile varies across economic sectors. The framework's central proposition turns on two multipliers of identical magnitude: the one whose conditions remain unexamined is a liability, and the one whose conditions have been priced is an asset. The output is identical in both cases; the difference lies in whether the risks beneath it have been made explicit, and measuring that difference is the framework's purpose.