Evolutionary Engineering -- Designing Systems that Self-Consciously Evolve --- The Defining Skill of Human Ecologists

Journal of Policy Studies, Policy Studies Association of Japan, No. 2, September 1996

40 Pages Posted: 2 Apr 2013

See all articles by Richard Greene

Richard Greene

Beijing DeTao Masters Academy; Keio University - Graduate School of System Design and Management

Date Written: September 1, 1996

Abstract

Defining a Field -- Human Ecology (Again) --- This is a survey article on the new field "human ecology" (re-found after an initial founding in the 1910s), as it applies to policy studies. Few people will agree with the way this paper defines that field. This paper is not designed to produce agreement. Rather, this paper hopes to stimulate better definitions of the field by others. Professors of new fields (and of, even pseudo-new ones) have a special obligation to define their contents, methods, and boundaries, if, for no other reason, than students of such new fields deserve guidance on what they should be learning and what, upon graduating, they will be capable of doing.

Research Questions --- This article addresses the following research questions: 1) what does a human ecologist know that differs from what graduates of other fields know; 2) what types of problems does a human ecologist solve better than graduates of other fields; 3) what makes a human ecologist different than an ecologist; 4) how does one best educate human ecologists? Though in passing this article deals with material on the origins of human ecology as a field and the way it is taught at various higher education institutions, the primary thrust of this article is answering the research questions, not repeating institutional or intellectual history. Students of human ecology related fields, their parents and employers, and researchers will find this article's answers to these question useful.

Updating Knowledge Substrates of the Field --- In part that is because complexity theory constructs from the Santa Fe Institute, are used to update total quality systems models from Japan which are used to update Jay Forrester old MIT system dynamics models which are used to update, early 20th century ecosystem dynamics images from followers of Darwin.

Defining of Evolutionary Engineering --- This article presents Evolutionary Engineering, the creation and modification of systems that self-consciously evolve, as the skill that all human ecologists have, because it is the skill that defines them. The steps of that process -- Evolutionary Engineering -- show how 18 different bodies of knowledge are used by human ecologists when they create, improve, influence, or design systems that reflexively evolve. This article examines problems with non-linear systems caused by the segmented, linear, direct command nature of existing bodies of knowledge and professions, and how human ecology overcomes those segmentations, linearities, and command processes. Difficulties in designing systems that evolve, living systems, human systems, and difficulties inherent in design itself are used to specify roles for Evolutionary Engineers.

The Most Powerful System Science -- Quality Totalizatrion by Japan --- Four attempts at creating a systems science that ended up lacking influence are compared with one successful form of systems science that gained world-wide popularity -- the total quality movement. The relationship between personal change capability and capacity to change the systems and lives of others is explored as a limit to Evolutionary Engineering.

Theory of Surprise --- A Theory of Surprise is presented, built from ways that linear models that we humans use to simplify our world, get upset by various non-linear phenomena in our world. The study, measurement improvement, and self-emergent design of policy processes is examined as a major field of application of Evolutionary Engineering.

Policy Failure Cases Analyzed --- Cases of policy failure are explained with reference to particular steps in the Evolutionary Engineering. Cases of policy failure are explained with reference to particular steps in the Evolutionary Engineering process that were omitted by the policy formation process and policy implementation illustrated using examples of Evolutionary Engineering versus other ways of creating coalitions (student governments on campus used as an example), and Evolutionary Engineering versus other ways of leading meetings (methods for personal leadership) used as an example).

Keywords: human ecology, evolutionary engineering, global quality, quality totalizations, quality globalizations, managing by events, social automata process, natural selection dynamics in non-biologic social substrates

Suggested Citation

Greene, Richard, Evolutionary Engineering -- Designing Systems that Self-Consciously Evolve --- The Defining Skill of Human Ecologists (September 1, 1996). Journal of Policy Studies, Policy Studies Association of Japan, No. 2, September 1996, Available at SSRN: https://ssrn.com/abstract=2242931

Richard Greene (Contact Author)

Beijing DeTao Masters Academy ( email )

1 Nanjin Road ShaheZhen
Changping District
Beijing, 102206
China

HOME PAGE: http://www.detaoma.com/Master_Forum/Richard_Tabor_Greene

Keio University - Graduate School of System Design and Management ( email )

1-1 KyoSeiKan Building 6 floor C6N16
Hiyoshi, Honcho, Kohoku-Ku
Yokohama, Kanagawa 223-0001
Japan

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