Luc Steels

Luc Steels

From ICREA Barcelona

Luc Steels studied linguistics at the University of Antwerp (Belgium) and computer science at the Massachusetts Institute of Technology (USA). His main research field is Artificial Intelligence covering a wide range of intelligent abilities, including vision, robotic behavior, conceptual representations and language. His work has found applications in knowledge-based systems, autonomous robots and digital community memories for the management of a commons based on community engagement and citizen science. In 1983 he founded the Artificial Intelligence Laboratory at the University of Brussels (VUB) and became a professor of computer science. In 1990 he co-founded the computer science department at the VUB and became the first chairman (from 1990 until 1995). He founded the Sony Computer Science Laboratory in Paris in 1996 and became its first director until 2014. Currently he is ICREA research professor at the Institute for Evolutionary Biology (CSIC,UPF) in Barcelona. ICREA is the Catalan Institution for Research and Advanced Studies. Steels has participated in dozens of large-scale European projects and more than 30 PhD theses have been granted under his direction. He has produced over 200 articles and edited 15 books directly related to his research. During the past decade he has focused on theories for the origins and evolution of language using computer simulations and robotic experiments to discover and test them. More recently he is pushing the boundaries of AI in the direction of a proper handling of meaning and understanding, with applications in the management of social media, the interpretation of art works, and the study of computational creativity.

Can AI make sense of art? And what are the limits of computational creativity?

Today AI is very much in the news with achievements in many areas of science, engineering and application. But how far has AI advanced in comparison to human intelligence? Can we already speak about computational creativity? To find the scope and limitations of the current state of AI I propose to look at art as one of the highest achievements of human intelligence, a domain in which creativity is highly valued. Can we somehow emulate the experience that a human has when looking at a painting? Can we emulate the act of creating new artistic work? This requires that we not only address issues of computer vision, pattern recognition and computer graphics (in the case of visual arts) but also semantic issues related to meaning and understanding. This talk is based on a case study that I carried out the past year culminating in an exhibition starting on 3 April 2021 at the BOZAR cultural center in Brussels. The subject was a world-renowned Flemish painter Luc Tuymans, and specifically one of his painting ‘Secrets’ that was last shown in his solo exhibition at the Palazzo Grassi in Venice during 2019-2020. Based on extensive discussions with the artist and with the help of some computer vision specialists, I made an AI model in the form of a transient narrative network that is fed with input from computer vision, language processing with text from the catalog, queries to semantic resources such as knowledge graphs, thesauri and dictionaries, as well as further inferences based on computational ontologies. The conclusion of this experiment is that using AI algorithms to investigate the computational nature of art interpretation is very illuminating, not only because it helps us to look more intently and to grasp more deeply the cultural and intrinsic meanings of an art work, but also because it shows us the remarkable richness of the human mind – making all claims that superhuman artificial intelligence will soon be reached sound hollow. The experiment also throws light on the nature of creativity and what it will take for AI to become creative the way human painters are. This challenge is equally considered to be far in the future – if ever reachable.