Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth

Ajay Agrawal, John McHale and Alexander Oettl

No 24541, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Innovation is often predicated on discovering useful new combinations of existing knowledge in highly complex knowledge spaces. These needle-in-a-haystack type problems are pervasive in fields like genomics, drug discovery, materials science, and particle physics. We develop a combinatorial-based knowledge production function and embed it in the classic Jones growth model (1995) to explore how breakthroughs in artificial intelligence (AI) that dramatically improve prediction accuracy about which combinations have the highest potential could enhance discovery rates and consequently economic growth. This production function is a generalization (and reinterpretation) of the Romer/Jones knowledge production function. Separate parameters control the extent of individual-researcher knowledge access, the effects of fishing out/complexity, and the ease of forming research teams.

JEL-codes: O3 O33 O4 Z38 (search for similar items in EconPapers)
Date: 2018-04
New Economics Papers: this item is included in nep-big, nep-gro, nep-ict and nep-tid
Note: EFG PR
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Published as Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth , Ajay Agrawal, John McHale, Alexander Oettl. in The Economics of Artificial Intelligence: An Agenda , Agrawal, Gans, and Goldfarb. 2019

Downloads: (external link)
http://www.nber.org/papers/w24541.pdf (application/pdf)

Related works:
Chapter: Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:24541

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w24541

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().