Title: The Third Wave of Artificial Intelligence — From Blackbox Machine Learning to Explanation-based Cooperation.
Time: 20th April 2021, 16:00 CET (10:00 EST).
Abstract:
Machine learning is considered as an important technology with high potential for many application domains in industry as well as society. Impressive results of deep neural networks, for instance for image classification, promise that complex decision models can be derived from raw data without the need of feature engineering (end-to-end learning). However, there is an increasing awareness of the short-comings of data-intensive black box machine learning approaches: For many application domains it is either impossible or very expensive to provide the amount and quality of data necessary for deep learning. Furthermore, legal or ethical or simply practical considerations often make it necessary that decisions of learned models are transparent and comprehensible to human decision makers. Consequently, AI researchers and practitioners alike proclaim the need for the so-called 3rd Wave of AI to overcome the problems and restrictions of an AI which is focusing on purely data-driven approaches. In the talk, it is shown that machine learning research offers many alternative, often less data-intensive, approaches. Current topics and approaches for explainable and interactive machine learning will be introduced and illustrated with some example applications for human-AI partnerships.
Speaker’s Bio:
Ute Schmid is professor of Applied Computer Science/Cognitive Systems at the University of Bamberg. She has university diplomas in computer science as well as psychology, and a doctor degree and a habilitation in computer science from TU Berlin. She is member of the board of directors of the Bavarian Institute of Digital Transformation (bidt) and member of the Bavarian AI Council. Furthermore, Ute Schmid is head of the Fraunhofer IIS project group Explainable AI. Research interests of Ute Schmid are in the domain of comprehensible machine learning, explainable AI, and high-level learning on relational data, especially inductive programming. Research topics are generation of visual, verbal and example-based explanations, cognitive tutor systems, and cooperative and interactive learning. Ute Schmid dedicates a significant amount of her time to measures supporting women in computer science and in 2018 won the Minerva Gender Equality Award of Informatics Europe for her university. Since many years she offers and organises computer science workshops, including AI for children and is speaker of the working group AI in Schools of the SIG AI of the German Computer Science Society (GI e.V.).
The foto copyright is J. Schabel.
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