Artificial Intelligence (AI) and Data Science is developing at a phenomenal speed, driven by the increasing availability of “big” data, better machine learning algorithms like deep learning, and ever more computing power. Radboud AI has been set up to create a unique profile in AI research and education, summarized in our joint mission to develop the next generation of responsible AI. Radboud AI includes the Radboud Data Science Centre (RDSC) as a platform for the use of AI and other modern techniques for advanced big data analysis. In the next two years, we aim to turn Radboud AI into a virtual institute, to acquire regional, national, and EU funding, to boost AI and DS education, to set up new public-private labs, and to create new faculty positions for AI staff.
The joining of forces is an absolute necessity to attract and retain AI top talent. In a similar vein, the European initiatives ELLIS en CLAIRE mean to counterbalance the enormous investments in North-America and China and to prevent the outflow of top talent to giants like Google, Microsoft, and Amazon. Within the Netherlands, a lobby has been started towards a national AI strategy, in line with our neighbouring countries (see this overview). Radboud AI is essential both to connect to these initiatives and to educate and retain AI talent for our region.
Developing the next generation of responsible AI
Radboud AI aims to become the national hub on responsible AI, laying the foundations for the use of artificial intelligence to the benefit of society as a whole. Here we broadly interpret “responsible AI”, or “verantwoorde kunstmatige intelligentie” in Dutch, as AI to the benefit of society with qualities such as transparency, fairness, accountability, social-awareness, efficiency, and sustainability; qualities that are still lacking in most currently popular AI systems. Responsible AI requires the development of novel paradigms that are intrinsically fair, transparent, and accountable, e.g., building upon our strong line of research on causal inference.
Socially-aware AI systems need to be able to communicate with and properly understand humans. Relevant ongoing top-notch research on campus ranges from text mining and speech recognition, through social robot interaction and virtual reality, to brain-computer interfaces. Modernization of our labs will boost our joint research on human-centered AI and spin off demos for popular outreach. We will specifically focus on AI applications in health, as a natural extension of the highly successful research on deep learning for computer-aided diagnosis in radiology and pathology.
Goals for the coming years are:
- Forming a public-private virtual institute in the field of Artificial Intelligence and Data Science
- The organization of public-private labs
- Conducting knowledge-enhancing training and educational activities, e.g. a Radboud wide minor Data Science
- Tendering local, regional, national and EU funding
- The development of a talent pool
- Conducting communication and PR activities
Source: Website Radboud University, 1 January 2019.