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人工智能内部审计提示工程演示.pdf

上传人: 学*** 编号:187772 2024-12-26 30页 1.45MB

1、ARTIFICIAL INTELLIGENCE&PROMPT ENGINEERING FOR INTERNAL AUDITAugust 2024AI Standards,Regulations,&Governance03AI and Internal Audit09Prompt Engineering Tips&Tricks15Prompt Patterns&Examples20QuestionsAgendaAgenda2AI Standards,Regulations&GovernanceAI Standards,Regulations&GovernancePoll question 1Po

2、ll question 1What is your primary concern with the use of AI at your organization?Data privacy and confidentiality.AReliability and accuracy of outputs.BPotential biases and fairness issues.CCompliance with relevant laws and regulations.D4Why is AI being regulated?Why is AI being regulated?New risks

3、 and threats for individuals fundamental rights and freedomsNeed to build trust to keep the momentum in use and adoption of AIDisruptive changes on business,economy,social life,environment,science and researchAbility to enable manipulation and advanced surveillanceSelf-learning and self-evolving nat

4、ure following the launchAI-specific Frameworks and Regulationsi.e.,EU AI Act,NIST AI Risk Management FrameworkSectorial Regulations aligned to AIi.e.,UK Consumer DutyRegulations on Data and Digital Infrastructurei.e.,DORA(Digital Operational Resilience Act),GDPR5Recognized standards for AI Governanc

5、eRecognized standards for AI GovernanceNIST AI Risk Management Framework is designed to equip organizations and individuals with approaches that increase the trustworthiness of AI systems,and to help foster the responsible design,development,deployment,and use of AI systems over time.European Union

6、AI Act focuses primarily on strengthening rules around data quality,transparency,human oversight and accountability.It also aims to address ethical questions and implementation challenges.ISO/IEC AI Framework provides guidance on managing risk associated with the development and use of AI.The docume

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本文主要讨论了人工智能(AI)在内部审计中的应用,包括AI标准、法规和治理,以及如何利用提示工程技巧来提高AI在内部审计中的效率和准确性。文章首先介绍了AI的监管背景,包括欧盟AI法案、NIST AI风险管理框架等,强调了AI系统应遵循的五大原则:透明度和可解释性、公平性和偏见缓解、问责制、隐私和数据治理、稳健性和安全性。接着,文章详细介绍了提示工程的重要性,包括定义提示、上下文、逻辑性、示例和可操作性等要素,并提供了各种提示模式,如角色模式、问题细化模式、认知验证模式、受众角色模式、翻转交互模式和模板模式。最后,文章通过实际案例展示了如何将生成式AI应用于内部审计的各个阶段,包括审计通知模板的生成、过程流程的记录和分析等。
如何利用AI提高内部审计效率? 如何设计有效的AI提示以获取准确结果? 如何确保AI在内部审计中的合规性?
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