Scientific Theories and Artificial Intelligence

Artificial Intelligence presents an important paradigm shift for science. Science is traditionally founded on theories and models, most often formalized with mathematical formulas handcrafted by theoretical scientists and refined through experiments. Machine learning, an important branch of modern Artificial Intelligence, focuses on learning from data. This leads to a fundamentally different approach to model-building: we step back and focus on the design of algorithms capable of building models from data, but the models themselves are not designed by humans. This is even more true with deep learning, which requires little engineering by hand and is responsible for many of Artificial Intelligence's spectacular successes. In contrast to logic systems, knowledge from a deep learning model is difficult to understand, reuse, and may involve up to a billion parameters.