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U.S. State AI Task Force Survey Report from CPSAI

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U.S. State AI Task Force Survey Report - Table of Contents

I. Executive Summary

This report provides a comprehensive overview of how state governments across the U.S. are approaching the integration of AI into government services through the establishment of dedicated task forces. It analyzes the common structures, goals, and outputs of these task forces, categorizes them into four distinct types, and provides a detailed survey of each state's individual approach.

II. Introduction

As AI technologies rapidly advance, it is crucial to examine how governments are preparing for their impact. This report delves into the emerging trend of state-level AI task forces, highlighting their role in shaping responsible and effective AI adoption within the public sector.

III. The AI Task Force Model: Core Characteristics

  • A. Genesis of an AI Task Force: This section explores the typical methods by which AI task forces are established, highlighting the roles of executive orders and state legislation in their formation.
  • B. Composition of AI Task Forces: This section examines the typical membership of AI task forces, including the representation of government officials, agency leaders, and non-governmental stakeholders.
  • C. Structural Organization: This section outlines the common structural elements of AI task forces, focusing on the prevalence of working groups and subcommittees dedicated to specific areas of inquiry.
  • D. Operational Procedures: This section details the typical day-to-day activities of AI task forces, emphasizing their reliance on expert consultations, working group collaborations, and public meetings.
  • E. Expected Outputs and Deliverables: This section outlines the common outputs expected from AI task forces, including reports, policy recommendations, draft legislation, and ethical guidelines.
  • F. Typical Tenure and Duration: This section examines the typical lifespans of AI task forces, differentiating between those established as permanent advisory bodies and those with limited terms.
  • G. Priorities, Goals, and Objectives: This section provides a general overview of the common priorities and goals driving the work of AI task forces, laying the groundwork for a more in-depth analysis of different task force types.

    • IV. Typologies of AI Task Forces: Four Distinct Approaches

    • A. Type 1: Legislative Advising: This section focuses on the most prevalent type of AI task force, characterized by its role as a policy consultant to legislative bodies and the governor's office.
    • 1. Case Study: Washington State AI Task Force: This subsection provides a detailed examination of the Washington State AI Task Force as a prime example of a broadly scoped legislative advisory body.
      • B. Type 2: Oversight & Systems Management: This section explores AI task forces that prioritize the development, implementation, and enforcement of standardized procedures for AI use within government agencies.
        • C. Type 3: Project-Based: This section examines AI task forces primarily focused on identifying and developing specific, high-value use cases for AI within government services or the private sector.
          • 2. Case Study: Massachusetts Artificial Intelligence Strategic Task Force: This subsection explores the Massachusetts Artificial Intelligence Strategic Task Force, emphasizing its role in identifying and promoting AI applications for both the public and private sectors.
          • 3. Case Study: Wisconsin Task Force on Workforce and Artificial Intelligence: This subsection examines the Wisconsin Task Force on Workforce and Artificial Intelligence, highlighting its unique focus on analyzing and mitigating the potential labor market impacts of AI.
          • D. Type 4: Judicial: This section focuses on AI task forces specifically established within state court systems to regulate and oversee the responsible use of AI in judicial proceedings.
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            Currently ConsideringBy Justin Brown