AI not only offers great potential. In some respects, it also harbors risks and suffers from certain weaknesses. This includes the fact that the internal processes of AI systems often remain opaque. In addition, AI-generated results can also be incorrect and/or discriminatory. This means that an acute awareness and appropriate strategies are needed to ensure high quality standards when working with AI. These strategies include assessing, on a case-by-case basis, whether the use of AI systems even makes sense in the specific situation, and making informed choices in selecting the technologies and applications that are best suited for the task at hand.

When it comes to input quality, it is important to WU to ensure that the data/content uploaded to AI systems meets high standards. Depending on the individual use case, the data should be free of bias and discriminatory content, and it should be taken from reliable sources. Especially when working with generative AI systems such as ChatGPT, the better the prompts (the input) and the more specific the instructions, the higher the quality of the results.

WU employees are aware of the potential shortcomings of AI-generated results and take responsibility for the content they generate with the help of AI. It is therefore crucial to remain critical with regard to quality and, if necessary, to review the results, adapt them accordingly, and use them responsibly.