Data Science: User Experience Design
The rapid advancement of Generative AI is transforming business models, decision-making, and customer interactions across industries. In these disruptive scenarios, organizations must redesign user experiences (UX) that balance technological efficiency with human values such as well-being, trust, and ethics. This lecture explores how data science can serve as a foundation for UX design by integrating AI-driven information processing, optimization, and affect analytics with human judgment, empathy, and creativity. Drawing on the concept of Extended Service Capability (ESC)—an organizational ability to co-create value through human–AI collaboration—it proposes a three-layer framework: a philosophy layer defining where AI should and should not be used, an operational layer where data science and human insight jointly shape the experience, and an outcome layer placing well-being at the center of value. Insights from research on long-established Japanese firms illustrate how organizations sustain a clear identity—knowing “what we are” and “what we are not”—while adapting through innovation. The lecture argues that future competitive advantage will depend not only on data-driven optimization but also on the design of meaningful human experiences enabled by stakeholder value co-creation, presenting a framework for Human–AI Co-evolution that supports both organizational sustainability and societal well-being.
Lecture at NEMO2026
Date/Time: Thursday, July 30, 2026 at 08:30