Wednesday 20 May
19:45 live music
20:15 speakers
Café Loburg
Like it or not, Advanced AI Assistant are popping up everywhere. These assistants are supposed to make our lives easier by taking over tasks such as organizing meetings or summarizing meeting outcomes. But what if these AI support systems become more and more autonomous and make decisions we did not intend? Who is responsible for misconduct of such an assistant? How do we make sure that the benefits of AI outweigh the risks? This requires some careful thinking about the why, when and which tasks we want an advanced AI assistant for, and how to build-in effective control over AI-based decisions to mitigate errors.
Dr. Sietze Kai Kuilman is a researcher at Delft University of Technology, where he works at the intersection of computer science and philosophy. He obtained his PhD at TU Delft, and his PhD thesis “AI that glitters is not gold: Requirements for meaningful control of AI systems” inspired us for this Science café session. Dr Kuilman obtained an MSc in Artificial intelligence at the University of Amsterdam as well as an MA in philosophy also at the University of Amsterdam. During his studies, he focused on Philosophy of Language and Philosophy of Cognition. His current research focuses on the notion of control and its relation to sociotechnical systems. His interests are broadly speaking the history of Artificial Intelligence and the question of what algorithmically can be achieved in terms of understanding.
Prof.dr. Ioannis N. Athanasiadis is Chair of Artificial Intelligence at Wageningen University and Research. His research aims to advance artificial intelligence to address global challenges, related to food security, agriculture and ecology. He is a proponent of use-inspired fundamental research. Driven by the complexities of natural systems, Ioannis aspires to further the field of artificial intelligence and contribute towards a more sustainable and food-secure future. Together with his research team, students and stakeholders, Ioannis develops artificial intelligence systems tailored to help farmers, policymakers, and stakeholders make better-informed decisions, manage risks and improve our understanding of complex system interactions with data-driven discoveries.