At LUCI Lab, logic is primarily a research mindset. We are inspired by, and seek to contribute to, the most pressing questions arising in science and technology.
We are witnessing the coming of age of data-intensive and AI-driven science. It is redefining the very meaning of scientific knowledge, how it is produced, and how it is transferred to society. At LUCI Lab, we ask what should follow from this kind of knowledge while it is still in the making.
Data-driven scientific knowledge is at the heart of the interaction between humans and AI systems. So we develop logics which aim to play a key role in hybrid- and human-centred AI. In this context we ask what it takes for data-driven hypotheses to yield valid scientific inferences — and under what conditions we should trust machine learning algorithms to produce valid outputs.
This project follows in the tradition of George Boole, who set a radically new goal for logic: the identification of a general method to solve mechanically all reasoning problems, including those with uncertain premisses.