WELCOME

Abstract

Unintended outcomes can become hard-coded into data-driven technologies when decision making is automated with AI, despite our intentions. Any AI holds risks of augmenting, and perpetuating blind spots into their models. These blind spots are not just a risk for unfairness, they can affect the performance of your models, or leave your systems exposed to regulatory implications. The more you understand the inner structure of your AI systems and algorithms, the better equipped you are to leverage these insights to your advantage.

This talk unpacks the workings of the design and decision making that goes into algorithmic systems, how to identify and analyze the mechanisms in AI and how to ensure those are aligned with your goals. We will dive into the limitations and possibilities of leveraging data driven technologies, learn to identify opportunities for responsible AI; and to assess an automated decision making system on its risk for unintended consequences.

Lin-Lin Chen is dean of the Faculty of Industrial Design, and chair of Design Innovation Strategy at the Eindhoven University of Technology in the Netherlands. She is Editor-in-Chief of International Journal of Design. She was professor in the Department of Design at the National Taiwan University of Science and Technology (NTUST) from 1998 to 2022, dean of the college of design at NTUST from 2004 to 2010, president of the Chinese Institute of Design from 2007 to 2008, and convener for the arts (and design) area committee of Taiwan’s National Science Council from 2009 to 2011. She founded the International Journal of Design (SCI, SSCI, AHCI) in 2007, was president of the International Association of Societies of Design Research (IASDR) from 2017 to 2019, and has been a fellow of the Design Research Society since 2006. Her research focuses on human-AI interaction, aesthetics, interdisciplinary collaboration, and design innovation strategy.

Dr. Leon Kester is a Senior Research Scientist at TNO Netherlands who did his PhD in physics. He is a transdisciplinary scientist in Responsible AI working on the safety, security, meta-ethics and governance of high risk AI systems and XR technologies. His transdisciplinary research integrates perspectives from i.a. human centered AI, systems engineering, cybernetics, cognitive science, moral psychology, law, moral programming and philosophy of science. In recent years, he has published many papers as well as book chapters (most of them with Dr. Nadisha-Marie Aliman, an independent post-doctoral scientist) on the aforementioned topics. In the EU standardization committee CEN/CENELEC JTC21 he is an editor of the European Norm for Risk Management and introduced “Augmented AI system goal specification” for advanced high-risk AI applications.