Sciences and Complexity:
Why other scientific fields are not and should not be like physics.

Noppadon Kamolvilassatian

September 6, 2001

In "The Structure of Scientific Revolutions", Thomas Kuhn argues that science is based on some set of assumptions that most, if not all, scientists in the field agreed upon. These shared assumptions allow scientific progress to be made and theories to be refined continuously into greater details. The process continues as long as the current set of beliefs, or "paradigm", serve its purpose: allowing scientific work to explain realities better. Once in a while, however, major anomalies that cannot be explained by the current paradigm appear and become significant enough that they cannot be ignored. The scientific with such events is now in flux. There are efforts to invent new fundamentals that hopefully will take care of anomalies and other know facts of the world. The process is then similar to that of natural selection, that is, the most convincing set of beliefs is gradually accepted and becomes the new fundamental. With the new fundamental, the scientific refinement of theories start again...


Orlikowski and Iacono (2001) studied research papers in the MIS field over the past decade and found different views of technology by different researchers in the field. Each of these views serve as the fundamental set of assumptions for research in that particular direction and, in effect, set the tone for the results expected from such research.

An interesting observation is that several of differing views coexists quite well in the same time period in MIS. One way to explain the phenomenon according to Kuhn is that MIS research has not settled with its fundamentals yet. In other words, the field may still be in flux. In my view, however, such coexistence of different world views is natural, and beneficial, for MIS. The concept that there are few dominant sets of fundamentals for a scientific field applies very well to physics, for example, but not necessarily to other scientific fields. Physicists successfully explain the physical aspects of the world using concise mathematical expressions formed under few sets of assumptions. Such explanations, in contrast, may not be possible, or desirable, in fields dealing with complex objects or phenomena, such as social sciences, computer sciences, and MIS.

To take an extreme example, social sciences try to explain behaviors of people and organizations in societies comprising of billions of people interacting with one another and environment. In such complex systems, it is futile, and misleading, to try to find a single and concise set of assumptions that form the basis of theories that can explain everything. This is why social sciences do not have only few dominant fundamentals, as those in physics.

MIS and computer sciences lie along the spectrum between physics and social sciences. The systems these fields try to explain, information systems and computer systems, are more complex than fundamental physical laws, but less complex than human societies. As a result, these fields may not be adequately governed by few sets of assumptions at their fundamentals. Yet, a small and coherent set of assumptions is necessary to do rigorous scientific investigation, and should be applied for research work. What we need is multiple such sets of assumptions to provide additional, complementary aspects of explanations for the system we examine.

For example, the views taken by researchers in MIS field help us understand different facets of information systems, whether as tools (tool view), through proxies (proxy view), on their computational aspects (computational view), or as part of or whole systems (ensemble view). Each of these views is grounded on different assumptions and therefore yield results of qualitatively different characteristics.

Orlikowski and Iacono criticize MIS research in which the technology is essentially absent (nominal view). In addition, they strongly propose that IT artifact, by itself, should be a central phenomenon to focus on. They gave several convincing premises why this is the case. These premises help form new fundamentals for future research in this direction. IT artifacts as a new sub-field of MIS research will be formed if these fundamentals are distinct enough from fundamentals held by other views and theories generated from these fundamentals produce tangible and useful results with qualitatively different characteristics.

It is important to recognize that we may not be able to find general, universally applicable rules that describe systems investigated by other scientific fields as we have found for physics. Those systems are fundamentally complicated enough that no simple sets of rules would suffice in explaining them in whole. We thus need to find several sets of rules to explain various aspects of the systems, while each set of rules is simple enough that our limited intellect can thoroughly comprehend.

References

1) Kuhn, T. S., "The Structure of Scientific Revolutions".

2) Orlikowski, W.J. and C.S. Iacono, "Desperately seeking the 'IT' in IT research- a call to theorizing the IT artifact", Information Systems Research, 2001, 12(2).