This essay gives an overview and describes prospects for generating new scientific knowledge from disparate datasets, as viewed by four active practitioners from around the globe (Illinois, Arizona, Slovenia and Australia). Although artificial intelligence (AI) and machine learning (ML) are central techniques employed in the field, the key concepts in this essay are undiscovered public knowledge (UPK) and literature-based discovery (LBD). These comprise a variety of situations, including some not yet tackled via ML.
|Title of host publication||Artificial Intelligence in Science|
|Subtitle of host publication||Challenges, Opportunities and the Future of Research|
|Place of Publication||Paris|
|Number of pages||8|
|Publication status||Published - 26 Jun 2023|