Dr. Victor Tang

(Keynote Speaker)

Massachusetts Institute of Technology, USA

Brief Bio: Victor Tang was research scientist and consultant to MIT. Formerly VP IBM-China, senior executive IBM-corporate strategy, and systems development. Founder and Secretary General of China & IBM Technology Cooperation Committee for three years. IBM’s Technology Executive for the International Olympic Committee and the 1998 Winter Olympic Games. Earned eight IBM Outstanding-Contribution Awards. Has advised the United Nations, and the Chinese government, etc. Has taught and lectured in Asia, South America and Europe. Has many research papers and authored four technology-management and technical textbooks. Book published by the Oxford University Press has been translated into Russian, Korean, and Chinese. His fourth book, Executive Decision Synthesis, is published by Springer, Heidelberg.  Victor speaks English, Chinese, Spanish, and French. Has BS Electrical Engineering and MS Mathematics from Purdue, Master’s Business Policy from Columbia, and PhD from MIT.

Title of Speech: Data, Information, Knowledge & Intelligence: A Strategic Framework for China

Abstract: This article is about the hierarchy of data, information, knowledge, and judgment. We present our definition for each and discuss their parallel hierarchies of: cognitive categories, expertise levels, uncertainty classifications, and creative types. We frame our discussion from a strategic managerial perspective and address the implications to decisions, innovation, and creativity. We use Chinese and other familiar examples to illustrate the various parallel hierarchies. Our approach has a macro and managerial bias. Some mathematics and science are necessary and cannot be avoided. Our examples are used to facilitate inferences, conclusions, and insights on innovation, creativity and strategic management. Surge in complexity and complicatedness are visibly transforming the scale of sociotechnical systems, which have become more messy, difficult and challenging to manage. We argue two conclusions; first is our Mega-Nano Hypothesis, which asserts that new problems, at this new scale and qualitative difference, cannot be solved with conventional thinking and tired mental models. They impede the ability to innovate and inhibit creative thinking about theory. This hypothesis is consistent with historical trajectories in scientific development. Namely, when scale changes at the mega or nano scale and frame-breaking levels, a new science is required to address the new and unprecedented problems that emerge. Second is our Uncertainty Hypothesis, which asserts, that at this new scale of complexity, our conventional probabilistic-risk mental models lack explanatory power and are deficient for our decision-synthesis paradigm, which we will introduce.