Recent progress in artificial intelligence has elevated what used to be a highly specialised research area to a topic of public discourse and debate. In this presentation I will discuss why beyond the hype, there are good reasons to be excited, but also concerned about AI. Specifically, I will explain how and why AI will have transformative impact on all sciences and engineering disciplines. Based on my own research on the robustness of neural networks, I will discuss some of the fundamental strengths, weaknesses and limitations of current AI systems. Finally, I will share some thoughts on the most serious risks of deploying these systems quickly and broadly, as well as on what needs to be done in order to manage these risks and to realise the benefits AI can bring.
Holger H. Hoos holds an Alexander von Humboldt professorship in AI at RWTH Aachen University (Germany), as well as a professorship in machine learning at Universiteit Leiden (the Netherlands) and an adjunct professorship in computer science at the University of British Columbia (Canada). He is a Fellow of the Association of Computing Machinery (ACM), the Association for the Advancement of Artificial Intelligence (AAAI) and the European AI Association (EurAI), past president of the Canadian Association for Artificial Intelligence, former editor-in-chief of the Journal of Artificial Intelligence Research (JAIR) and chair of the board of CLAIRE, an organisation that seeks to strengthen European excellence in AI research and innovation (claire-ai.org).
Holger H. Hoos is known for his work on machine learning and optimisation methods for the automated design of high-performance algorithms and on stochastic local search, he has developed – and vigorously pursues – the paradigm of programming by optimisation (PbO); he is also one of the originators of the concept of automated machine learning (AutoML). He has a penchant for work at the boundaries between computing science and other disciplines, and much of his work is inspired by real-world applications.