Curiosity is not the sole motivation for scientific research. The 

 practical need for and the utility of scientific knowledge are often 

 prime reasons for seeking such understanding. This is illustrated by 

 astronomy, one of the oldest of the sciences, which was studied in 

 earlier days for the purpose of improving navigation as well as for 

 insights into the composition and organization of the universe. This 

 dual motivation of curiosity and utility is found in all scientific fields. 

 Thus, in addition to satisfying man's curiosity, science has proven to 

 have great impact on everyday life — from changing the physical 

 conditions of existence to the length of life itself. This potential 

 utilitarian "bonus," which can be gained when scientific knowledge is 

 applied to practical ends, is so sizeable in general that a motive for basic 

 research is often the potential applications that may flow from it. This 

 flow, however, extends in the other direction as well — applications 

 raise questions requiring further research. In fact, the reciprocal 

 relationship between knowledge and utility, between insight and 

 application, focuses and invigorates each. 



In spite of the advances made in scientific knowledge — and in part 

 because of the unanswered questions such advances reveal — science 

 still faces many challenges. Some of the more specific of these are 

 noted elsewhere in the report. But perhaps the most general and 

 fundamental challenge now facing science is that of achieving better 

 understanding of highly complex phenomena that involve a large 

 number of interacting components, i.e., systems of "organized 

 complexity." The behavior of the global atmosphere, the organization 

 and functioning of the human brain, and the dynamics of a social 

 institution or a larger social system are examples of such phenomena 

 which are little understood at present. (New insights from further 

 research, however, may reveal that such phenomena are less complex 

 than they now appear.) 



Historically, science has advanced primarily through the study of 

 less complex aspects of nature, by isolating individual components and 

 seeking to understand their characteristics through observation, 

 analysis, and experiment. The understanding of such relatively simple 

 phenomena provides the basis for almost all modern technology. 

 Problems of organized complexity, on the other hand, require a broad, 

 integrative approach, combining the methods and insights from many 

 individual scientific disciplines and, perhaps, even radically new 

 concepts and methodologies that transcend individual disciplines. 

 Large-scale modeling and simulation are needed to synthesize the 

 diverse knowledge regarding these complex areas, to uncover the 

 underlying dynamics of the problems, and to project the future course 

 of their development. An indispensable tool in these efforts is the 

 enormous data-handling capacity of computers. 



Until the level of understanding of such complicated phenomena 

 is significantly improved, science will fall short of meeting the 

 challenges in this area. 



