The role of the University of Twente in the AI landscape
At the University of Twente, “Shaping AI to work” is rooted in a collaborative and inherently multidisciplinary approach. Scientists and students from diverse fields come together, drawing on a broad spectrum of expertise to develop and prepare AI methods and techniques for real-world application. This is done in co‑creation with external stakeholders who need to “Make AI work”, meaning putting it to practical use. Our foundational work concentrates on advancing focused AI, where AI technology is designed to perform a single task and excel at it. “Shaping AI to work” also involves ensuring that AI aligns with scientific and social values and that it can be used justifiably and in an accountable manner. In other words, AI is shaped to work for a better world.
Collaboration and deeply rooted domain knowledge are central to this process. The UT proactively collaborates with a wide range of stakeholders, including industry and public partners, non-profit organisations and citizens as the fundamental starting point. We believe that AI must be aligned with real-world needs and ethical standards. Therefore, these partnerships enrich the academic environment and provide practical insights, bridging the gap between research and practical application. This ensures that UT researchers understand for whom and for what purpose they are doing their work.
The multidisciplinary nature of AI research at UT is a significant strength. Teams include experts in data science, engineering, ethics, mathematics, social science, safety and security, and, of course, domain experts. This diversity gives us a holistic view of the problems at hand, allowing us to develop AI solutions that are both technically proficient and socially and environmentally conscious. UT scientists contribute to AI methods and techniques with a comprehensive understanding of their potential impacts across different sectors.
Thus, “Shaping AI to work” at the University of Twente represents a dynamic mix of collaboration, multidisciplinary innovation, and ethical responsibility. It demonstrates how academic environments can confidently and optimistically lead change by preparing AI for broad and effective application. When the time comes to “Make AI Work”, the technologies are not only ready for it, but they will also be ready to have a positive, transformative impact on society.