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

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

Research output: Contribution to journalArticleOtherpeer-review

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.

Original languageEnglish
Article number100658
Number of pages3
JournalThe Innovation
Volume5
Issue number5
DOIs
Publication statusPublished - 9 Sept 2024

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