Simplify, Don't Amplify the IRS Act, Sec. 201 ("Tax Gap Projection")

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.

  • Authority: United States Congress
  • Parent authority: Federal government
  • Jurisdiction: United States
  • Collections: U.S. federal laws
  • Most recent activity: Defunct
  • Most recent activity date: 2025-01-03

Risk subdomain coverage

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.

Sector coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.

  • Public Administration (excl. National Security)

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.

Legislative Status

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.

Actors

Proposer

  • Entity Types: AI_Governance_Actor
  • Entities: United States Congress
  • Summary: The document is identified as an Act of the United States Congress, which is the legislative body that proposed and enacted this governance instrument.

Target

  • Entity Types: AI_Governance_Actor, AI_Deployer
  • Entities: Commissioner of Internal Revenue; Internal Revenue Service
  • Summary: The document explicitly targets the Commissioner of Internal Revenue, who is required to use AI systems for tax gap projections and is subject to specific constraints on audit activities. The IRS acts as both a governance actor (tax collection authority) and AI deployer (using AI for tax gap calculations).

Enforcer

  • Entity Types: AI_Governance_Actor
  • Entities: United States Congress
  • Summary: Congress serves as the enforcement body through its oversight authority, requiring annual reporting from the Commissioner and establishing binding constraints on IRS activities.

Monitor

  • Entity Types: AI_Governance_Actor
  • Entities: United States Congress
  • Summary: Congress monitors implementation through mandatory annual reporting requirements that include detailed descriptions of data used and projections, allowing Congressional oversight of the AI-based tax gap calculation system.

AI Lifecycle Stages

Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems

  • Collect and Process Data
  • Build and Use Model
  • Deploy
  • Operate and Monitor

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.

Technical Scope

Terms relating to technical scope that are mentioned or implicitly referenced in the document

  • AI Models
  • AI Systems
  • Predictive AI
  • Task-specific AI

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.

https://www.congress.gov/bill/118th-congress/house-bill/2556
https://agora.eto.tech/instrument/795
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Document data from AGORA, CSET Emerging Technology Observatory.