SORS: in our own image: what can the science of the human mind reveal about GenAI

A grand ambition of machine learning is to create generative artificial intelligence capable of assisting us in our tasks. Although much progress has been made, GenAI agents still struggle to align themselves with some of the goals and thinking patterns of the human users. The mainstream solution has been to painstakingly try out different variants of the training process and scale up data and compute. But there is another way: The development of efficient, human-compatible GenAI agents can be streamlined by tapping into the methodological and theoretical advances from cognitive neuroscience. In my talk, I outline a research program applying what is known about the human mind to address current issues in machine learning. In particular, there is a solid base of scientific facts about learning and memory which can be used to inform architectural choices. I argue that GenAI already follows some principles of human cognition and that making it even more human-like will increase its ability to cooperate with humans and solve human-made tasks.