Applied Data Science and Artificial Intelligence

This transversal professorship serves as a driver of innovation by collaborating closely with academy staff and external experts. These efforts aim to inspire both students and staff to modernise and enrich their teaching and learning methods. From these activities, four key values linked to the professorship have been frequently highlighted and should be embedded in the programme:

Understanding AI includes addressing its potential societal and individual impacts, which often evoke emotional responses. It is essential to conduct evidence-based, factual research to analyse and understand these impacts effectively.

Many individuals and groups lack engagement with AI, its applications, and its capabilities. Terms like ’AI’, ’autonomous’, ’smart’, and ’large language models’ are inconsistently adopted, leading to confusion. Therefore, factual education and clear dissemination of information are necessary to build a deeper understanding of AI.

Applied Research and Development

Research efforts must focus on practical and applied initiatives to address BUas domain-specific challenges. The programme aims to bridge gaps by offering tailored support for each domain, progressing from initial awareness to advanced AI applications.

Open communication is critical to linking different domains, fostering internal and external collaboration, and connecting education with industry. Multiple initiatives will facilitate this, ensuring interdisciplinary cooperation and knowledge sharing.