This year's ENBIS Spring Meeting offered two inspiring days around the topic of "Trustworthy Industrial Data Science".
This year, the Faculty of Computer Science at Fachhochschule Dortmund hosted the Spring Meeting of the European Network for Business and Industrial Statistics (ENBIS), which focused on "Trustworthy Industrial Data Science". The trustworthiness of statistical models, machine learning and artificial intelligence is crucial for their introduction and progress in Business Studies and industry.
Under the local leadership of Prof. Dr. Sonja Kuhnt (Fachhochschule Dortmund) and Prof. Dr. Markus Pauly (TU Dortmund), researchers and industry representatives from various countries came together. The aim of the conference was to exchange innovative statistical methods, machine learning models and adaptive and intelligent methods in applied data science.
Trustworthy artificial intelligence deals with the development of methods and proofs that ensure the "correct" behaviour of artificial intelligence algorithms in order to promote their acceptance by users and organizations. The event was characterized by lively discussions and forward-looking ideas for improving data quality, robustness, fairness and explainability. From empirical studies on trustworthy data analysis to the fairness of predictive models and practical applications, a broad spectrum was covered.
A particular highlight of the event were the plenary sessions with renowned speakers such as Nicolas Brunel (ENSIIE, France), Jean Michel Loubes (Université Toulouse Paul Sabatier, France) and Muhammad Bilal Zafar (Ruhr University Bochum, Germany). Their presentations provided valuable insights into the design of trustworthy and legally compliant AI systems.