The trustworthiness of AI applications has been the subject of recent research and is also addressed in the EU's recently adopted AI Regulation. The currently emerging foundation models in the field of text, speech and image processing offer completely new possibilities for developing AI applications. This whitepaper shows how the trustworthiness of an AI application developed with foundation models can be evaluated and ensured. For this purpose, the application-specific, risk-based approach for testing and ensuring the trustworthiness of AI applications, as developed in the 'AI Assessment Catalog - Guideline for Trustworthy Artificial Intelligence' by Fraunhofer IAIS, is transferred to the context of foundation models. Special consideration is given to the fact that specific risks of foundation models can have an impact on the AI application and must also be taken into account when checking trustworthiness. Chapter 1 of the white paper explains the fundamental relationship between foundation models and AI applications based on them in terms of trustworthiness. Chapter 2 provides an introduction to the technical construction of foundation models and Chapter 3 shows how AI applications can be developed based on them. Chapter 4 provides an overview of the resulting risks regarding trustworthiness. Chapter 5 shows which requirements for AI applications and foundation models are to be expected according to the draft of the European Union's AI Regulation and Chapter 6 finally shows the system and procedure for meeting trustworthiness requirements.

翻译：人工智能应用的可信度已成为近期研究的热点，同时也是欧盟新近通过的《人工智能法案》所关注的核心议题。当前在文本、语音及图像处理领域新兴的基础模型，为开发人工智能应用提供了全新的可能性。本白皮书阐述了如何评估并确保基于基础模型开发的人工智能应用的可信度。为此，我们借鉴了弗劳恩霍夫智能分析和信息系统研究所（Fraunhofer IAIS）在《人工智能评估目录——可信赖人工智能指南》中提出的面向特定应用、基于风险的测试与保障方法，并将其迁移至基础模型的语境中。特别需要考虑的是，基础模型的特定风险可能对人工智能应用产生影响，因此在可信度检查时必须予以纳入。白皮书第1章从可信度视角阐释了基础模型与其衍生的AI应用之间的基本关系；第2章介绍基础模型的技术构建原理；第3章展示如何基于基础模型开发AI应用；第4章概述由此产生的可信度相关风险；第5章阐明根据欧盟《人工智能法案》草案，AI应用与基础模型所需满足的要求；第6章最终展示满足可信度要求的系统与方法。