Frank Dignum: TAIGA: Transdisciplinary AI for the Good of Al

Abstract

Machine learning is an important part of AI and it’s application very successful at the moment. However, it’s use is limited to situations where problems can be characterized as classification problems and the classification is learned from massive amounts of data. Most of today’s challenges in society (like climate change, pandemics, migration, etc.) are not of that nature. I will argue that for AI to play a role in tackling these challenges it needs a transdisciplinary approach. Input from all disciplines are needed in order to include all aspects of these challenges. In this approach the human should be central instead of the data about the human. I will illustrate the ideas with some real world applications.

Biography

Frank Dignum  got his PhD at the VU in Amsterdam in 1989. Since 2019 he is Wallenberg chair in socially aware AI at Umeå University in Sweden. He also has an affiliation to Utrecht University and he is an honorary principal research fellow of the University of Melbourne. Since 2014 he is a EurAI fellow. He is well known for his work on norms and his theory of social agents is employed in social simulations to support policy making and e-coaching. He has given invited lectures and seminars all over the world. He published 22 books and more than 300 papers