Advancing Human Understanding with Deep Learning Go AI Engines
Attila Egri-Nagy, Antti Törmänen · 2022
Humans mainly learned from other human beings for thousands of years. Recent advancements in artificial intelligence (AI) seem to have changed this setup. Due to deep learning, we now have access to automatically generated high-quality statistical knowledge beyond human expert intuition in many fields. However, the representation is not human-friendly: an opaque mass of pure associations instead of narrative, causal explanations. Here, we investigate the epistemological problem of using AI data for human understanding and suggest an active approach based on the scientific method. Following tradition in AI, we focus on a game. Go is a well-defined problem domain that is complex enough that our approach may provide solutions in other fields of knowledge, too, where AI technology outperforms humans.