PUB - Publikationen an der Universität Bielefeld

This paper presents the development of a human-centred AI system for the classification of laundry according to washing categories such as color and type. The system aims to provide a solution that is both accurate and easy to use for individuals with varying levels of technical expertise. The development process involved a human-centred approach, including user research and testing, to ensure that the system meets the needs and expectations of its users. The system uses a combination of computer vision techniques and machine learning algorithms to analyze images of dirty laundry and provide recommendations for the appropriate washing category. In addition to the development of the system itself, this paper also focuses on the explanation of the AI. The aim is to increase transparency and promote understanding of how the system makes its decisions. This is achieved through the use of visualizations and explanations that make the inner workings of the AI more accessible to users. The results of testing demonstrate that the system is effective in accurately classifying dirty laundry. The explanation of the AI has yet to receive more feedback, whether users report that it increased their trust in the system and find it easy to use. The development of a human-centered AI system for laundry classification has the potential to improve the efficiency and accuracy of laundry sorting while also promoting understanding and trust in AI systems.