11th edition AI lunch meeting (TU/e internal)

Chris Snijders
Predictive models are getting better and smarter, but often still have to relay their findings to humans. Given that models can be complex and might still make mistakes, a human's trust in the model's output is neither automatic nor straightforward. Our research focuses on ways in which we can better understand and improve the connection between model output and human receiver.

Jack van Wijk
Predictive analytics concerns the use of algorithms for decision making and decision support. Typically, these algorithms are based on machine learning, leading to complex models that are often hard to understand. Our research focuses on developing new methods to provide more insight using interactive visualization, such that users are enabled to understand and judge the results. After an overview of the background, a number of examples from different domains are shown.

Vincent Müller
Artificial intelligence and robotics are technologies that seem to be of major importance for the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, and what risks they have in the long term. In this talk I will discuss the difference between viewing AI systems as objects, i.e. tools used by humans, vs. AI systems as autonomous subjects.