Litcius/Paper detail

Toward a nomenclature consensus for diverse intelligent systems: Call for collaboration

Brett J. Kagan, Michael Mahlis, Anjali Bhat, Josh Bongard, Victor Cole, Phillip Corlett, Christopher Gyngell, Thomas Härtung, Bianca Jupp, Michael Levin, Tamra Lysaght, Nicholas L. Opie, Adeel Razi, Lena Smirnova, Ian Tennant, P. Wade, Ge Wang

2024The Innovation10 citationsDOIOpen Access PDF

Abstract

Disagreements about language use are common both between and within fields. Where interests require multidisciplinary collaboration or the field of research has the potential to impact society at large, it becomes critical to minimize these disagreements where possible. The development of diverse intelligent systems, regardless of the substrate (e.g., silicon vs. biology), is a case where both conditions are met. Significant advancements have occurred in the development of technology progressing toward these diverse intelligence systems. Whether progress is silicon based, such as the use of large language models, or through synthetic biology methods, such as the development of organoids, a clear need for a community-based approach to seeking consensus on nomenclature is now vital. Here, we welcome collaboration from the wider scientific community, proposing a pathway forward to achieving this intention, highlighting key terms and fields of relevance, and suggesting potential consensus-making methods to be applied.

Topics & Concepts

Relevance (law)Multidisciplinary approachField (mathematics)NomenclatureComputer scienceData scienceEngineering ethicsKnowledge managementManagement sciencePolitical scienceTaxonomy (biology)SociologyEngineeringBiologyEcologySocial scienceLawMathematicsPure mathematicsMachine Learning in Materials ScienceSemantic Web and OntologiesScientific Computing and Data Management
Toward a nomenclature consensus for diverse intelligent systems: Call for collaboration | Litcius