Abstract

This habilitation thesis explores the foundations of scientific discovery by examining the roles of language, conceptual structures, and artificial intelligence in knowledge production. It contributes to the emerging field of the philosophy of scientific discovery by addressing fundamental questions: What constitutes a scientific discovery? What structural features characterize discovery processes? How do language and naming practices shape scientific progress? And to what extent can machines participate in or even independently generate discoveries? Drawing from case studies in biology, epistemology, and AI research, this work argues that scientific discovery is a structured process encompassing three core elements: finding, acceptance, and knowledge. Special attention is given to declarative speech acts in the validation of discoveries, the role of ambiguity and naming in the evolution of scientific terminology, and the potential for artificial agents to engage in meaning-making and scientific inference. By integrating perspectives from the philosophy of science, language, and mind, this work lays the groundwork for a systematic and interdisciplinary approach to understanding scientific discovery.