My Account Log in

1 option

Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth / Ajay Agrawal, John McHale, Alex Oettl.

NBER Working papers Available online

View online
Format:
Book
Author/Creator:
Agrawal, Ajay.
Contributor:
National Bureau of Economic Research.
McHale, John.
Oettl, Alex.
Series:
Working Paper Series (National Bureau of Economic Research) no. w24541.
NBER working paper series no. w24541
Language:
English
Physical Description:
1 online resource: illustrations (black and white);
Other Title:
Finding Needles in Haystacks
Place of Publication:
Cambridge, Mass. National Bureau of Economic Research 2018.
Summary:
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.
Notes:
Print version record
April 2018.

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account