Requires the Commissioner of Internal Revenue to use AI, including neural machine learning, to calculate tax gap projections, reducing the burden on taxpayers. Limits National Research Program audits to fiscal year 2022 levels while leveraging commercial data analysis tools.
All other risk subdomains had no coverage in this document.
Risk Coverage Summary
This document has minimal coverage of AI risk domains, with only brief implicit references to AI system security (2.2) and lack of robustness (7.3) through its mandate to use AI for tax gap projections. The document does not substantively address the risks or harms associated with these domains, focusing instead on operational requirements.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.
All other sectors had no coverage in this document.
Sectors Summary
This document governs AI use within Public Administration (specifically the Internal Revenue Service), mandating the use of AI for tax gap projections. It does not regulate AI use across multiple economic sectors but rather governs the operations of a specific government agency.
Hard Law
Legislative Status Summary
This is a binding legislative act from the United States Congress with mandatory obligations on the Commissioner of Internal Revenue, using mandatory language ('shall') and establishing specific legal requirements with deadlines.
Proposer
Target
Enforcer
Monitor
Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems
AI Lifecycle Summary
The document primarily addresses the Deploy and Operate and Monitor stages of the AI lifecycle, as it mandates the use of AI systems for tax gap projections and implies ongoing operational use. There is minimal implicit coverage of Build and Use Model through the requirement to use neural machine learning.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document explicitly mentions artificial intelligence and neural machine learning as technologies to be used for tax gap projections. It does not define or distinguish between AI models and AI systems, nor does it reference frontier AI, general purpose AI, foundation models, or compute thresholds. The focus is on practical deployment of AI tools rather than technical categorization.
Document data from AGORA, CSET Emerging Technology Observatory.