FLOWERS

The Flowers AI & CogSci lab aims to study the fundamental mechanisms that can enable open-ended learning and development in humans and machines, i.e. how individuals, or groups of individuals, can continuously discover and learn novel skills of increasing complexity. We also aim to leverage this fundamental understanding for human-centered real-world applications in education and in assisted scientific discovery.

In particular, we focus on studying mechanisms enabling Autotelic and Aligned Intelligence in humans and machines. A first key ingredient of open-ended learning is curiosity-driven autotelic learning, which is the ability of individuals to set and pursue their own goals (from the greek ‘telos’/goal, and ‘auto’/self), a form of intrinsic motivation pushing organisms to continuously seek new knowledge and skills. self-organizing their own learning curriculum, using meta-cognition and leading to creative exploration. 

To enable abstraction, collective intelligence, and alignment of autotelic systems on human cultures (values, preferences), we also aim to study how language and social interaction, both as a communication system and as a cognitive tool, can guide autotelic exploration. Symmetrically, using multi-scale models, we aim to study how curiosity-driven autotelic exploration could self-organize at the group level. We also aim to study what are the ecosystemic and evolutionary origins of autotelic systems.