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Artificial Intelligence (AI) has made impressive progress in recent years andrepresents a key technology that has a crucial impact on the economy andsociety. However, it is clear that AI and business models based on it can onlyreach their full potential if AI applications are developed according to highquality standards and are effectively protected against new AI risks. Forinstance, AI bears the risk of unfair treatment of individuals when processingpersonal data e.g., to support credit lending or staff recruitment decisions.The emergence of these new risks is closely linked to the fact that thebehavior of AI applications, particularly those based on Machine Learning (ML),is essentially learned from large volumes of data and is not predetermined byfixed programmed rules.  Thus, the issue of the trustworthiness of AI applications is crucial and isthe subject of numerous major publications by stakeholders in politics,business and society. In addition, there is mutual agreement that therequirements for trustworthy AI, which are often described in an abstract way,must now be made clear and tangible. One challenge to overcome here relates tothe fact that the specific quality criteria for an AI application dependheavily on the application context and possible measures to fulfill them inturn depend heavily on the AI technology used. Lastly, practical assessmentprocedures are needed to evaluate whether specific AI applications have beendeveloped according to adequate quality standards. This AI assessment catalogaddresses exactly this point and is intended for two target groups: Firstly, itprovides developers with a guideline for systematically making their AIapplications trustworthy. Secondly, it guides assessors and auditors on how toexamine AI applications for trustworthiness in a structured way.

Guideline for Trustworthy Artificial Intelligence -- AI Assessment Catalog