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

• Published in: Innovation (New York, NY) NY), 2024-09, Vol.5 (5), p.100658, Article 100658
• Main Authors: Kagan, Brett J., Mahlis, Michael, Bhat, Anjali, Bongard, Josh, Cole, Victor M., Corlett, Phillip, Gyngell, Christopher, Hartung, Thomas, Jupp, Bianca, Levin, Michael, Lysaght, Tamra, Opie, Nicholas, Razi, Adeel, Smirnova, Lena, Tennant, Ian, Wade, Peter Thestrup, Wang, Ge
• Format: Article
• Language: English
• ISSN: 2666-6758; 2666-6758
• DOI: 10.1016/j.xinn.2024.100658

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.