Interest

Study of complex systems has become recognized as a basic scientific endeavor whose inquiry has relevance to the management of complex organizations in a complex world (Herz 2001). More specific attention has been gained in information technology (Horn 2001), biotechnology (Strausberg and Austin 1999; NSF n.d.; NIGMC n.d.; NSF 2001), healthcare industries, and the military.

Information technology companies building computer hardware and software have begun to recognize the inherently interactive and distributed nature of the systems they are designing. A significant example is the IBM "Autonomic Computing" initiative (Horn 2001), which is inspired by the biological paradigm of the autonomic nervous system and is conceptually based upon modeling robustness through biologically inspired system design. In a different perspective, Apple Computer has demonstrated the relevance of human factors, ranging from hardware design to ease-of-use and facilitation of creativity, as essential aspects of the role of computers in computer-human systems.

The major advances in biotechnology, including the genome project and other high-throughput data acquisition methods, have led to a dramatic growth in the importance of modeling and representation tools to capture large bodies of information and relate them to system descriptions and properties. Many private companies at the forefront of biotechnology are developing bioinformatics tools that strive to relate information to functional descriptions also described as "functional genomics" (Srausberg and Austin 1999). This is one facet of a broader recognition of the importance of capturing the multiscale properties of biological systems as reflected in NSF's biocomplexity initiative (NSF n.d.) and the complex biological systems programs at NIH (NIGMS 2002), as well as in joint programs.

For several years, the interest in complex systems as a conceptual and quantitative management tool has led consulting companies to work on practical implementations of strategy and more specific modeling efforts (Ernst and Young 2000, Gleick 1987). One of the areas of particular interest has been in the healthcare management community, where rapid organizational change has led to a keen interest in complex systems insights.

In the military and intelligence communities, there has been increasing realization of the relevance of networked distributed control and information systems. All branches of the military and the joint chiefs of staff have adopted vision statements that focus on complex systems concepts and insights as guiding the development of plans for information age warfare. These concepts affect both the engineering of military sensors, effectors, and information networks, and the underlying nature of military force command and control.

More broadly, the public's attention has been widely attracted to the description of complex systems research and insights. Indeed, many popular descriptions of complex systems research existed before the first textbook was written (Gleick 1987; Lewin 1992; Waldrop 1992; Gell-Mann 1994; Casti 1994; Goodwin 1994; Kauffman 1995; Holland 1995; Coveney and Highfield 1995; Bak 1996). The excitement of scientists as well as the public reflects the potential impact on our ability to understand questions that affect everyday life, perspectives on the world around us, fundamental philosophical disputes, and issues of public concern such as major societal challenges, the dynamics of social networks, global computer networks (the WWW), biomedical concerns, psychology, and ecology.

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