In January 2022, our Austrian Research Fund (FWF) selected our project “Explainable AI” as project of the week, providing a bit of insight into the broad field of Human-Centered AI. Here is the original article in SciLog the official science magazine of the Austrian Science Fund (FWF):
https://scilog.fwf.ac.at/en/environment-and-technology/15317/human-centred-artificial-intelligence
and here you find selected recent publications:
- Bastian Pfeifer, Afan Secic, Anna Saranti & Andreas Holzinger (2022). GNN-SubNet: disease subnetwork detection with explainable Graph Neural Networks. bioRxiv, 1–8, doi:10.1101/2022.01.12.475995
- Andreas Holzinger, Anna Saranti, Christoph Molnar, Prezemyslaw Biececk & Wojciech Samek (2022). Explainable AI Methods – A Brief Overview. XXAI – Lecture Notes in Artificial Intelligence LNAI 13200. Cham: Springer, pp. 13-38, doi:10.1007/978-3-031-04083-2_2
- Andreas Holzinger (2021). The Next Frontier: AI We Can Really Trust. In: Kamp, Michael (ed.) Proceedings of the ECML PKDD 2021, CCIS 1524. Cham: Springer Nature, pp. 1–14, [paper]
- Andreas Holzinger, Bernd Malle, Anna Saranti & Bastian Pfeifer (2021). Towards Multi-Modal Causability with Graph Neural Networks enabling Information Fusion for explainable AI. Information Fusion, 71, (7), 28-37, doi:10.1016/j.inffus.2021.01.008
- Andreas Holzinger, Andre Carrington & Heimo Mueller (2020). Measuring the Quality of Explanations: The System Causability Scale (SCS). Comparing Human and Machine Explanations. KI – Künstliche Intelligenz (German Journal of Artificial intelligence), Special Issue on Interactive Machine Learning, Edited by Kristian Kersting, TU Darmstadt, 34, (2), 193-198, doi:10.1007/s13218-020-00636-z
Here is the link to the TEDx talk which shows in a short way the thematic content of this FWF project:
https://www.youtube.com/watch?v=UuiV0icAlRs