Abstract

The landscape of research management is undergoing a seismic transformation driven by Artificial Intelligence (AI) and data science. This talk explores their profound impact on traditional research principles and practices, unveiling a wave of challenges and unprecedented opportunities.

As AI technologies and data science continue to advance, they provide growing challenges for research management. From recruitment strategies in a fiercely competitive market to infrastructural changes introducing powerful computing capabilities, and even to the very core of research - access and discovery, AI is upending established norms.

I’ll start with a brief introduction into the state of adoption of AI and data science, with an emphasis on generative AI. Then, I’ll introduce a range of initiatives that illustrate challenges in planning and operations, specifically:

ELLIS - the European Laboratory for Learning and Intelligent Systems - a pan-European AI network of excellence which focuses on fundamental science, technical innovation and societal impact.

Helmholtz AI - one of the Helmholtz Association (Germany’s largest research organisation) several AI and data science platforms established in 2019 to address upcoming challenges in AI research, infrastructure and education.

By examining such initiatives and sharing (hard and easy) lessons learned, I aim to transmit insights into navigating this transformative era effectively. Embracing AI's potential and providing easy access to expertise while addressing its inherent challenges including competition from industry is paramount in harnessing the full power of AI for research excellence.