Skip to main navigation Skip to search Skip to main content

AI for Technoscientific Discovery: A Human-Inspired Architecture

  • J. Y. Tsao
  • , R. G. Abbott
  • , D. C. Crowder
  • , S. Desai
  • , R. P.M. Dingreville
  • , J. E. Fowler
  • , A. Garland
  • , P. P. Iyer
  • , J. Murdock
  • , S. T. Steinmetz
  • , K. A. Yarritu
  • , C. M. Johnson
  • , D. J. Stracuzzi

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

We present a high-level architecture for how artificial intelligences might advance and accumulate scientific and technological knowledge, inspired by emerging perspectives on how human intelligences advance and accumulate such knowledge. Agents advance knowledge by exercising a technoscientific method—an interacting combination of scientific and engineering methods. The technoscientific method maximizes a quantity we call “useful learning” via more-creative implausible utility (including the “aha!” moments of discovery), as well as via less-creative plausible utility. Society accumulates the knowledge advanced by agents so that other agents can incorporate and build on to make further advances. The proposed architecture is challenging but potentially complete: its execution might in principle enable artificial intelligences to advance and accumulate an equivalent of the full range of human scientific and technological knowledge.
Original languageEnglish
JournalJournal of Creativity
Volume34
Issue number2
DOIs
StatePublished - Aug 1 2024
Externally publishedYes

Fingerprint

Dive into the research topics of 'AI for Technoscientific Discovery: A Human-Inspired Architecture'. Together they form a unique fingerprint.

Cite this