2025-06-29-世界银行-设计人工智能的战略方法_政策制定者手册（英）_99页_3mb

报告摘要

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Summary of "Devising a Strategic Approach to Artificial Intelligence: A Handbook for Policy Makers"

Objective:
This handbook provides a comprehensive, adaptable framework for policymakers to develop strategic national approaches to artificial intelligence (AI), focusing on responsible deployment for public good, economic growth, and inclusive development, particularly in low- and middle-income countries (LMICs).

Key Focus:

AI Potential: AI can drive economic development and address social challenges by enhancing service delivery and reducing poverty, while mitigating risks like data privacy and algorithmic bias.
Four Cs Framework: Essential prerequisites for AI readiness include Connectivity (broadband and energy), Computing (HPC and data centers), Context (digitized, local data), and Competencies (AI literacy and skills).
Strategy Components: Covers vision, governance, innovation, and sectoral integration to ensure ethical AI adoption and alignment with global frameworks.

Development Process:
The handbook outlines an iterative and modular framework with seven modules:

Get Set Up: Define leadership and form a task force with expertise in AI and other domains.
Map the Landscape: Assess AI foundations (infrastructure, data, computing) and enablers (skills, policies).
Set the Direction: Establish strategic objectives, pillars (e.g., education, research, governance), and mission/vision statements.
Define the Focus: Identify priority sectors and use cases for AI integration aligned with national goals.
Shape Actions: Conduct policy gap analyses and define SMART actions to address gaps.
Prepare for Implementation: Institutionalize Leadership, assign responsibilities, build capacity, and develop M&E frameworks.
Adopt, Launch, and Adjust: Ensure continuous stakeholder engagement, monitor progress, and update strategies periodically.

Additional Guidance:

Leverage global AI principles (e.g., G7 Hiroshima Process, UNESCO Ethics) for harmonized governance.
Address risks such as the AI divide and ensure equitable benefits through inclusive stakeholder engagement.
Utilize annexes for practical tools, such as ToRs for task forces, policy templates, and M&E examples.

This approach supports tailored AI strategies that balance local context with global advancements.

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