“Augmenting human intelligence with artificial intelligence”
Assoc.Prof.Dr. Andreas HOLZINGER
PhD, MSc, MPh, BEng, CEng, DipEd, MBCS, MAE
XAI-Lab, Alberta Machine Intelligence Insitute (amii)
University of Alberta, Edmonton, Canada
Institute for Medical Informatics, Statistics & Documentation
Medical University Graz and
Institute of Interactive Systems & Data Science
Graz University of Technology
- My research and teaching is on data driven artificial intelligence (AI) and machine learning (ML) promoting a synergistic approach of Human-Centered AI (HCAI) to augment human intelligence with machine intelligence.
- My current focus is on explainable AI and interpretable machine learning, where my background and pioneer work on interactive machine learning (iML) with a human-in-the-loop and my experience in the application area health is very beneficial.
- My goal is to enable a human expert to understand the underlying explanatory factors – the causality – of why an AI-decision has been made, paving the way for ethical responsible AI and transparent verifiable machine learning.
Due to raising ethical, social and legal issues governed by the European Union, future AI supported systems must be made transparent, re-traceable, thus human interpretable. Andreas’ aim is to explain why a machine decision has been reached, paving the way towards explainable AI and Causability, ultimately fostering ethical responsible machine learning, fairness, trust and acceptance for future robust AI. This is relevant for the application in medicine and important for adoption of human-centered AI in industry.
Andreas obtained a Ph.D. in Cognitive Science from Graz University in 1998 and his Habilitation (second Ph.D.) in Computer Science from Graz University of Technology in 2003. Andreas was Visiting Professor for Machine Learning & Knowledge Extraction in Verona, RWTH Aachen, University College London and Middlesex University London. Since 2016 Andreas is Visiting Professor for Machine Learning in Health Informatics at the Faculty of Informatics at Vienna University of Technology. Currently, Andreas is Visiting Professor for explainable AI, Alberta Machine Intelligence Institute, University of Alberta, Canada.
Andreas is lead of the Holzinger Group (HCAI-Lab), Institute for Medical Informatics/Statistics at the Medical University Graz, and Associate Professor (Univ.-Doz., UG 93) of Applied Computer Science at the Faculty of Computer Science and Biomedical Engineering at Graz University of Technology. He serves as consultant for the Canadian, US, UK, Swiss, French, Italian and Dutch governments, for the German Excellence Initiative, and as national expert in the European Commission. His is in the advisory board of the Artificial Intelligence Strategy AI made in Germany of the German Federal Government and in the advisory board of the Artificial Intelligence Mission Austria 2030.
Since 2003 Andreas has participated in leading positions in 30+ R&D multi-national projects, budget 6+ MEUR, 300+ publications, 12k+ citations, H-Index = 52.
Human-Centered AI needs a concerted effort of various experts working jointly together. Andreas founded the Expert Network HCI-KDD to foster a synergistic combination of methodologies of two areas that offer ideal conditions toward unraveling problems in understanding intelligence, enabling context-aware AI systems: Human-Computer Interaction (HCI) & Knowledge Discovery/Data Mining (KDD), with the goal of augmenting human intelligence with artificial intelligence.
Andreas is Associate Editor of Springer/Nature Knowledge and Information Systems (KAIS), Section Editor for Machine Learning of Springer/Nature BMC Medical Informatics and Decision Making (MIDM), and founding Editor-in-Chief of the cross-disciplinary journal Machine Learning & Knowledge Extraction (MAKE). He is organizer of the IFIP Cross-Domain Conference “Machine Learning & Knowledge Extraction (CD-MAKE)” and Austrian representative in the IFIP TC 12 Artificial Intelligence and member of IFIP WG 12.9 Computational Intelligence, the ACM, IEEE, GI, the Austrian Computer Science and the Association for the Advancement of Artificial Intelligence (AAAI).
This page is valid as of 28.10.2019 – 17:00 MDT (UTC-6)