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Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth / Ajay Agrawal, John McHale, Alex Oettl.
- Format:
- Book
- Author/Creator:
- Agrawal, Ajay.
- 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.
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