没有监管就没有信任！

AI总结：

针对机器学习在关键系统中的信任问题，本文强调监管和标准对认证安全性的必要性，并探讨了AI法案下的认证挑战与方法。

摘要：

机器学习（ML）性能的爆炸式增长及其应用的潜力，强烈促使我们考虑将其用于工业系统，包括用于自主系统中的决策等关键功能。虽然人工智能社区充分意识到确保基于AI应用的可信性的必要性，但仍然在很大程度上忽视了安全问题及其必然结果——监管和标准，没有这些，就不可能认证任何安全水平，无论系统是轻微关键还是高度关键。在航空航天、核电站、铁路或汽车行业等受监管行业中，开发和认证安全关键软件和系统的过程早已被合理化和掌握。他们使用定义明确的标准、监管框架和流程，以及形式化技术来评估和证明其开发的系统和软件的质量和安全性。然而，规范的低形式化水平以及基于机器学习的组件的不确定性和不透明性，使得使用大多数传统关键系统工程方法难以对其进行验证和确认。这引发了资格标准的问题，因此也引发了适用于AI的法规问题。通过《人工智能法案》，欧盟委员会为推进和构建安全、可信且尊重欧洲伦理价值观的AI应用集成的坚实方法奠定了基础。那么问题就变成了：“我们如何迎接认证的挑战，并为可信人工智能提出方法和工具？”

英文摘要：

The explosion in the performance of Machine Learning (ML) and the potential of its applications are strongly encouraging us to consider its use in industrial systems, including for critical functions such as decision-making in autonomous systems. While the AI community is well aware of the need to ensure the trustworthiness of AI-based applications, it is still leaving too much to one side the issue of safety and its corollary, regulation and standards, without which it is not possible to certify any level of safety, whether the systems are slightly or very critical.The process of developing and qualifying safety-critical software and systems in regulated industries such as aerospace, nuclear power stations, railways or automotive industry has long been well rationalized and mastered. They use well-defined standards, regulatory frameworks and processes, as well as formal techniques to assess and demonstrate the quality and safety of the systems and software they develop. However, the low level of formalization of specifications and the uncertainties and opacity of machine learning-based components make it difficult to validate and verify them using most traditional critical systems engineering methods. This raises the question of qualification standards, and therefore of regulations adapted to AI. With the AI Act, the European Commission has laid the foundations for moving forward and building solid approaches to the integration of AI-based applications that are safe, trustworthy and respect European ethical values. The question then becomes "How can we rise to the challenge of certification and propose methods and tools for trusted artificial intelligence?"

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。