Abstract
Artificial Intelligence: Theory or Tool? A Brief Discussion Drawn From Interdisciplinary Machine Learning Research Examples.

Abstract: Artificial Intelligence (AI) is arguably the most discussed technology of our times: On the one hand, AI algorithms have led to a variety of substantial breakthroughs which have inspired the use of AI for many qualitatively different research questions. On the other hand, no other research paradigm has a comparable history in falling behind its theoretical considerations causing recurring 'AI winters'. In order to provide a balanced discussion I will present several deep learning examples with applications in behavioural neuroscience which will naturally lead to intrinsic challenges and limitations of state-of-the-art AI algorithms. These limitations are particularly apparent in interdisciplinary projects in which AI is predominantly used as a tool to 'solve' a particular problem from the respective field. An in-depth investigating of the mathematical foundation of these algorithms is therefore pivotal to bridge the gap between theory and practice and ultimately save AI from its self-induced hypes. Therefore, the overall goal of my talk is to present some hopefully inspiring AI examples while advocating for truly interdisciplinary research projects in order to reduce the divergence between AI theory and tools.