AI for Technoscientific Discovery: A Human-Inspired Architecture

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 met...

Full description

Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: Elsevier 2024-08-01
Series:Journal of Creativity
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2713374524000037
Description
Summary: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.
ISSN:2713-3745