Scheduled: June 8th 22h00- (JST = UTC +0900)
Registration required: Please register to participate in the panel (required, if you are not the HSI official participant). It is free:
Prof. Zachary D. Tudor, CISSP, CISM, Associate Laboratory Director, National and Homeland Security Idaho National Laboratory
Prof. Milos Manic, Director, VCU Cybersecurity Center
Prof. Jacek Ruminski, Head of AI Bay, Head of Biomedical Engineering Department, Gdansk University of Technology
Prof. Hideyuki Sawada, Department of Applied Physics, School of Advanced Science and Engineering, Waseda University
Prof. Pitoyo Hartono, Department of Electrical and Electronics Engineering, School of Engineering, Chukyo University
Abstract: While AI-based systems frequently provide state-of-the-art performances, there is still hesitance towards acceptance of such AI systems. The main reason is – lack of trust.
With pervasive and ubiquitous AI around us, how do we know whether the AI is making the right decision at the right time? Is AI making the right decision for the right reasons? How do we build trust in AI? The stakes are high – from everyday situations to critical infrastructures such as energy, financial sector, transportation, or health. At the heart of the problem is exactly human-system interaction, the interaction between users (or operators) and AI driven devices and systems.
Hence the topic of Trustworthy AI in HSI becomes a very timely and necessary topic to address. With ongoing rapid technological advancements, the society should strive to be in position to manage, educate, and regulate AI in timely fashion. The problem is highly challenging – highly interdisciplinary, with guidelines and frameworks for improving user trust in AI systems still under development.
This international panel will address related issues and concepts, reflecting on initiatives in USA and EU. The panel will attempt to address issues including but not limited to transparency and explainability of AI, human-centered values and fairness, fairness and bias of AI, robustness, security, and safety of AI, AI system lifecycle, as well as AI related education and workforce development.