The GW Center for the Study of Globalization
2033 K Street, NW, Suite 230 • Washington, DC 20052 • Phone: (202) 994-5206 • Fax: (202) 994-5284
Email: gwcsg@gwu.edu • http://gstudynet.org/
Professor Rycroft started by comparing the different types of learning and their sources; as networks evolve in complexity so does technology. In fact, the three revolutions in science lately, which are biotech, IT, and nanotech, are very complex technologies and learning intensive; and the advancement of those fields is interconnected. For example, the Human Genome project was achieved using very strong computational power. Professor Rycroft stressed that for networks to learn, they have to rely on the different types of learning, however the focus has always been on a few of those types and sources like R&D and the need for different types of learning is constantly growing as knowledge displaces other factors of production.
Professor Rycroft noted that the factors that are creating globalization are also factors in creating localization. While knowledge and technological advances are pushing globalization forward, they are also concentrating the high-tech industries in local regions. He then moved to the different states of knowledge, which are the known, the unknown, the complex and the unknowable. He identified the role of each learning types in moving the state of knowledge toward the known. For example the R&D budget moves knowledge from unknown to known but it doesn't help in moving knowledge from other states. Therefore, the need of the network of knowledge that would move from unknowable to other states is even more obvious. However, moving from the known state-of-knowledge to the complex state require use of metaphors. In fact, many enduring network-generated and learning-based competitive advantages of technological innovation are now described in terms of capital metaphors. The choice of capital is due to the similarity of its accumulation to the accumulation of knowledge. Human capital, as well as social capital, provides metaphors needed to explain complex state of knowledge. Professor Rycroft distinguished different types of capital that are related to different state of knowledge as well as different type of learning and different type of network. Besides the intellectual capital which is carried by individuals and which state of knowledge is in the known and unknown, Professor Rycroft named other types, human capital and social capital.
Human Capital, or the know-how, is not written, is carried by groups and teams and is at the complex state of knowledge. One example is system integration. "It is sitting in the walls of the organization" was an expression used to point to the idea that such knowledge was not written but it was inside the company. On the other hand, the social capital, or the know-where, is carried by organizations and is at the unknowable state of knowledge. Some examples of the social capital or the know-where are alliances and interactions. For example, Intel embedded a chemistry company in their production process.
Finally, Professor Rycroft addressed the policy implications of complex system. He noted that public policies aimed at facilitating complex innovation would need to be as learning-based and flexible as the innovation process itself. One example of this flexibility is the latest statement of the department of justice that it will not enforce the anti-trust laws which constitutes a major change from the past when this law was a pillar of the American system. In addition, because the innovation of complex technologies is characterized by many unknowns and some things are likely to be unknowable, the formulation of successful complex innovation policy is also an unknowable exercise. He later stressed that complexity is not a panacea, it is a challenge and an incentive to thought, complexity should also not be confused with completeness but seen as emphasizing the incompleteness of knowledge. Moreover, a focus on complexity doesn't dismiss the individual, but rather places the individual in a broader context as a member of social organizations.
Finally, Professor Rycroft acknowledged that policy-makers' task is difficult, but he believed that complex policies in the future might have much greater payoff than today's initiatives; because, in complex systems, small events often have large consequences. Therefore, small well-crafted policy intervention can generate large positive impacts.
When asked if complexity theory was taken advantage of in policy making, Professor Rycroft explained that complexity theory is a variation of systems theories. He reminded the audience that when policy makers tried to apply system theory to policy making, it worked well in defense but not in other places that dealt with human needs and behavior because it couldn't explain it enough. After the 60's misadventure, similar attempt was done using the chaos theory. These days, complex theory is a third step; however, it is done in a much more cautious way. Another question was on how to measure the impact of intervention in complex systems, Professor Rycroft gave an example related to environment policy where the measurement is done through monitoring which was necessary although very costly.
The GW Center for the Study of Globalization
2033 K Street, NW, Suite 230 • Washington, DC 20052 • Phone: (202) 994-5206 • Fax: (202) 994-5284
Email: gwcsg@gwu.edu • http://gstudynet.org/