How can we fight unemployment more effectively? Will automation via robots and algorithms take our jobs? And how can we find new ways to fight global warming and preserve biodiversity? These questions have in common their complexity in the sense of complex systems: By definition, they are difficult to study and impossible to predict.
In this talk, I will present a method to address these complex, yet crucial issues for our societies, using a particular form of artificial intelligence called agent-based simulation. The idea is to provide an innovative method for designing and evaluating policies (of all kinds) in a virtual world, before their implementation in the real world.
I will illustrate this approach on several examples, in particular on the 3 previous questions (work, automation, climate) which will be treated and discussed.
Please register here: #frAIday, and we will send you a link in good time before the event, open to everyone who is interested in AI!
We are interested in AI research that benefits people by taking into account ethical, legal, technical, cultural, and social aspects – AI for the Good of All. To achieve this, we collaborate with researchers and experts in all disciplines and through internationally established networks and other partners. Read more about TAIGA here.
Speaker
Jean-Daniel Kant, Associate professor, Sorbonne University - CNRS, Computer Science Lab LIP6, Paris, France