The brain sciences have been an inspiration for computer scientists for a long time, as they tried to mimic cognitive skills of humans within machines. In the age of rapidly developing AI, brain scientists in turn are getting more interested in computer science and AI due to analyzing data from the neurosciences with means of AI but also to understand the human-AI-interaction better. In the realm of the latter it is aimed to understand how AI can best be developed and used to foster productivity and well-being in humans without a result such as humans showing signs of overreliance on AI (both in the emotional and cognitive domain). Further, within the study of human-AI-interaction personalization processes of the user interface will be needed to be better understood overcoming the idea that “one size fits all” AI design will suit all users in the same way. Finally, it will be important to unravel how brains respond to AI systems in contrast to human-human-interactions. This kind of research might inform AI designers to create trustworthy and ethical AI. In sum, the study of human-AI-interaction represents a timely endeavor worth of in-depth study in the brain sciences and curriculum for students.

CILO-1: To understand the complexities when forecasting the impact of AI (“AI is the new electricity”) by taking into account the problems of AI definitions. CILO-2: To apply neuroscience techniques to improve AI product developments (chances and limitations). CILO-3: To be able to explain in what areas artificial intelligence is superior to human intelligence and in what areas human intelligence outperforms artificial intelligence. CILO-4: To be able to explain psychological and neuroscientific aspects of human-AI-interaction (concepts such as uncanny valley / AI pessimism aversion, algorithm aversion can be outlined and applied to product development or design intervention). CILO-5: To reflect on ethical issues around the development and roll out of AI products.