Idea Engines: A Unified Theory of Innovation and Obsolescence From Markets and Genetic Evolution to Science

19 Pages Posted: 29 Apr 2022 Last revised: 8 Dec 2022

See all articles by Edward Lee

Edward Lee

Complexity Science Hub Vienna

Chris Kempes

Santa Fe Institute

Geoffrey West

Santa Fe Institute

Date Written: March 29, 2022

Abstract

Innovation and obsolescence describe dynamics of ever-churning and adapting social and biological systems, concepts that encompass field-specific formulations. We formalize the connection with a reduced model of the dynamics of the "space of the possible" (e.g. technologies, mutations, theories) to which agents (e.g. firms, organisms, scientists) couple as they grow, die, and replicate. We predict three regimes: the space is finite, ever growing, or a Schumpeterian dystopia in which obsolescence drives the system to collapse. We reveal a critical boundary at which the space of the possible fluctuates dramatically in size, displaying recurrent periods of minimal and of veritable diversity. When the space is finite, corresponding to physically realizable systems, we find surprising structure. This structure predicts a taxonomy for the density of agents near and away from the innovative frontier that we compare with distributions of firm productivity, covid diversity, and citation rates for scientific publications. Remarkably, our minimal model derived from first principles aligns with empirical examples, implying a follow-the-leader dynamic in firm cost efficiency and biological evolution, whereas scientific progress reflects consensus that waits on old ideas to go obsolete. Our theory introduces a fresh and empirically testable framework for unifying innovation and obsolescence across fields.

Keywords: innovation, obsolescence, idea lattice, firms, evolution, citations

Suggested Citation

Lee, Edward and Kempes, Chris and West, Geoffrey, Idea Engines: A Unified Theory of Innovation and Obsolescence From Markets and Genetic Evolution to Science (March 29, 2022). Available at SSRN: https://ssrn.com/abstract=4069545 or http://dx.doi.org/10.2139/ssrn.4069545

Edward Lee (Contact Author)

Complexity Science Hub Vienna ( email )

Josefstädter Straße 39
Vienna
Austria

HOME PAGE: http://https://eddielee.co

Chris Kempes

Santa Fe Institute ( email )

1399 Hyde Park Road
Santa Fe, NM 87501
United States

Geoffrey West

Santa Fe Institute ( email )

1399 Hyde Park Road
Santa Fe, NM 87501
United States

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