Since its start, AI research has been inspired by our knowledge of human intelligence. Neuroscience concepts such as neurons and the way they are connected have loosely inspired artificial neural nets while human mental faculties studied by cognitive scientists, such as language, perception, memory, attention, reasoning, and emotion, have long been considered by AI researchers to advance AI's capabilities.

This bridge program focuses on the connection between cognitive science and AI. While neuroscience can be the source of inspiration in mimicking the structures and architectures underlying human intelligence, we believe that, given the current state of AI, cognitive science can help in understanding how to define and build AI architectures that support the combination of neuro- and symbolic AI, in a way that takes the best of each of these two approaches to AI. While data-driven AI provides flexibility and learning (analogous to System 1 human reasoning from Kahneman's taxonomy), symbolic AI provides high-level reasoning processes (analogous to System 2 human reasoning). The way the human mind combines these two modalities can be a source of inspiration to integrate the two approaches and provide AI with capabilities that it is now lacking, such as truth recognition and handling, trustworthiness, and reasoning processes.

The goal of this bridge program is therefore to create a structural and long-lasting bridge between cognitive science and AI, in order to achieve a well-defined and principled connection between neuro- and symbolic AI.

The target audience include all AI researchers, hoping that researchers in both neuro- and symbolic AI approaches will join this event and effort, as well as cognitive scientists. We hope that the audience will walk away having learned much about the other discipline, and with many ideas on how to continue the work in their own research environment but especially in collaboration with researchers from the other discipline. 

Organizing Committee