AI Capability Evaluation (ACE) Standard (AI认证考试)
Wiki Article
AI Capability Evaluation (ACE) Standard is a globally attuned, modular framework and examination designed to assess, credential, and uplift individual readiness for the AI era. Developed in 2025 by a multidisciplinary team of students from the Cornell University Chief AI Officer Program, alongside leading AI engineers and practitioners from Asia-Pacific innovation hubs—including Australia, Singapore, Hong Kong, and Macau—the ACE System reflects both academic rigor and regional relevance. The initiative also draws on the expertise of Ivy League alumni, UK- and US-trained panel experts, and several founding members of the United Nations University Global AI Network, ensuring alignment with multilateral development goals and ethical AI governance.
AI 能力评估（ACE）标准是一套契合全球趋势的模块化框架与AI认证考试体系，旨在评估、认证并提升个人在人工智能时代的应对能力。体系于 2025 年由康奈尔大学首席人工智能官（Chief AI Officer）项目的跨学科学生团队，联合来自澳大利亚、新加坡、香港和澳门等亚太创新中心的顶尖 AI 工程师及从业者共同开发。ACE 体系不仅体现了严谨的学术水准，也兼顾了区域发展的实际需求。此外，该计划还汇聚了常春藤盟校校友、英美资深专家小组以及联合国大学全球 AI 网络（United Nations University Global AI Network）多位创始成员的专业智慧，确保其与多边发展目标及合乎伦理的 AI 治理保持一致。
Examination Structure (The 4 Papers)
The ACE Standard evaluates capabilities across four core dimensions—AI Literacy, Technical Fluency, Strategic Readiness, and Collaborative Intelligence—through four specific exam papers:
Paper 1: AI Essentials
Focuses on the fundamentals of Artificial Intelligence. Topics include machine learning (supervised/unsupervised), deep AI Exam learning, neural networks, and Transformer models like BERT and GPT.
AI Essentials（AI 基础） 提供了对人工智能的全面介绍，涵盖基础的机器学习概念，包括监督学习和无监督学习，随后深入探讨深度学习、神经网络以及 BERT 和 GPT 等 Transformer 模型。课程结束后，学员将能够应用关键算法，构建并评估模型，理解现代 AI 系统的架构。学习成果包括解决实际问题的实用技能，以及向不同受众有效传达机器学习解决方案的能力。
Paper 2: Generative AI
A deep dive into modern Generative AI. It covers practical applications such as prompt engineering, "vibe coding," agentic AI, and the MCP framework, aiming to teach students how to build sophisticated AI solutions.
本课程深入探讨现代生成式人工智能（Generative AI），涵盖提示工程（Prompt Engineering）、"Vibe Coding"（氛围编码/直觉编码）、以及代理式 AI（Agentic AI）和 MCP 框架等高级概念。课程重点在于构建复杂 AI 解决方案的实际动手应用。课程结束后，学员将能够设计高效的提示词，利用 AI 进行软件开发，应用代理原则实现任务自动化，并使用 MCP 框架整合模型、代码和提示词。毕业生将精通 AI 辅助编程，并对部署生成式 AI 系统所需的伦理治理有深刻的认识。
Paper 3: AI Applications
Explores how AI transforms key business functions. It covers use cases in marketing, sales, finance, operations, and HR, teaching learners to identify strategic opportunities and design AI-driven business solutions.
人工智能应用课程探讨了人工智能如何变革关键的业务职能。课程涵盖了市场营销、销售、财务、运营和人力资源等领域的实际用例，从个性化和预测性分析到机器人流程自动化（RPA）和欺诈检测。课程结束后，学员将能够识别战略性 AI 机遇，评估其潜在影响，并理解实施过程中的挑战。本课程使学习者具备设计针对现实业务问题的有效 AI 驱动解决方案的技能，确保他们能够将技术能力转化为可衡量的商业价值。
Paper 4: AI Ethics & Governance
Examines the moral and societal implications of AI. It covers regulatory frameworks (such as the EU AI Act), bias, privacy, and transparency, preparing students to lead ethical decision-making.
人工智能伦理与治理课程对人工智能的道德和社会影响进行了批判性审视。课程涵盖了基础伦理原则、欧盟《人工智能法案》（EU AI Act）等监管框架，以及偏见、隐私和透明度等实际挑战。课程结束后，学员将能够分析人工智能系统的风险，应用治理模型，并主导合乎伦理的决策制定。主要成果包括能够设计和倡导负责任的人工智能，确保在实际应用中实现公平性、问责制和合规性。
Scoring System
Candidates are graded on a 10-Point Scale, where each paper contributes to the overall band:
Bands 1–4: Limited readiness.
Bands 5–6: Operational competence.
Bands 7–8: Advanced capability.
Bands 9–10: Leadership and global impact.
Organization
The standard is managed by ExtranAI, a Singapore-based AI Group, and its educational arm, the Global AI Academy. The Academy aims to build a world-class ecosystem for AI literacy and leadership that is anchored in Asia but serves the global community.
该标准由总部位于新加坡的人工智能集团 ExtranAI 及其教育机构全球人工智能学院 (Global AI Academy) 管理。该学院致力于构建一个植根于亚洲、服务于全球的世界级人工智能素养和领导力生态系统。