In my PhD, I develop and assess Explainable AI (XAI) tools tailored for internal telecom end-users. It focuses on delivering meaningful explanations informed by interaction design principles, cognitive biases, and human decision-making theories. The research explores customizing XAI for telecom use-cases to support internal decision-making, while considering user preferences captured through elicitation studies. As part of this PhD study, a prescriptive framework will integrate cognitive biases, interaction design principles, and human decision-making theory to effectively communicate AI explanations to end-users. User studies will be conducted to evaluate the effectiveness of the prototypes following from the framework
JADS also participates in several (international) projects, which contribute to grand societal challenges like health, food security, smart transport and secure societies. Together with companies, government, NGO’s and other knowledge institutions, JADS works on solutions by using data.