History of Ideas in the Science of AI

The story of Artificial Intelligence is often told as a march of breakthroughs and inevitable progress. This book begs to differ. It looks beneath the headlines to trace AI as a living web of research threads, where ideas emerge, mutate, recombine, and sometimes fade from view. By introducing conceptual tools such as phylo-epistemic networks and a series of carefully chosen case studies — ranging from mathematical reasoning to modelling language as a complex adaptive system — this book proposes a new framework for understanding how techno-scientific research fields function. These tools reveal how the ‘pollination’ of concepts across subfields, shifts in meaning, unlikely recombinations, and seemingly abandoned approaches have continually expanded AI’s ‘adjacent possible’. By understanding the history of AI as a living epistemic ecosystem, this book also sets its eyes on the future. As today’s dominant paradigms crowd out alternatives, the field’s epistemic diversity grows fragile. By treating AI’s past not as a closed chapter but as a living resource, this book invites readers to think differently about what AI is — and what it could become.