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.