人工智能系统的合规性
Compliance of AI Systems
AI总结：
本文研究人工智能系统在欧盟AI法案下的合规性挑战，提出数据集合规性作为确保AI可信度的核心，并探讨边缘设备部署中的技术难题。
摘要：
随着人工智能系统在各领域日益深入的整合，需要坚实的概念来确保其符合未来的立法要求。本文系统地探讨了人工智能系统与相关立法的合规性，重点分析了欧盟AI法案和数据集的合规性。分析凸显了边缘设备在部署AI应用时面临的诸多挑战，这些设备由于去中心化和计算资源有限，难以实现复杂的合规机制。通过分析AI实现，本文识别了挑战并提出了开发、部署和运行AI时的首批最佳实践。数据集的合规性被强调为确保AI系统的可信度、透明性和可解释性的基石，必须与如AI法案等监管框架中的伦理标准保持一致。获得的见解应有助于持续讨论嵌入式AI系统的负责任开发和部署。
英文摘要：
The increasing integration of artificial intelligence (AI) systems in various fields requires solid concepts to ensure compliance with upcoming legislation. This paper systematically examines the compliance of AI systems with relevant legislation, focusing on the EU's AI Act and the compliance of data sets. The analysis highlighted many challenges associated with edge devices, which are increasingly being used to deploy AI applications closer and closer to the data sources. Such devices often face unique issues due to their decentralized nature and limited computing resources for implementing sophisticated compliance mechanisms. By analyzing AI implementations, the paper identifies challenges and proposes the first best practices for legal compliance when developing, deploying, and running AI. The importance of data set compliance is highlighted as a cornerstone for ensuring the trustworthiness, transparency, and explainability of AI systems, which must be aligned with ethical standards set forth in regulatory frameworks such as the AI Act. The insights gained should contribute to the ongoing discourse on the responsible development and deployment of embedded AI systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
