Knowledge Revolution

This article contains wording that promotes the subject in a subjective manner without imparting real information. Please remove or replace such wording and instead of making proclamations about a subject's importance, use facts and attribution to demonstrate that importance. (October 2009) (Learn how and when to remove this template message)

The knowledge revolution refers to a global-scale paradigm shift that many^[who?] compare to the agricultural and industrial revolutions. The revolution is about a fundamental socioeconomic change from adding value by producing things which is, ultimately limited, to adding value by creating and using knowledge which can grow indefinitely.

Theories

Overviews of the knowledge revolution were provided by Marilyn Ferguson,^[1] who refers to the ascendance of an irreversible shift in the global state of mind; a fundamentally new world view that encompasses insights from ancient times through current breakthrough science. Sakaiya^[2] indicates that three major disrupters of the established order – population shifts, resource supply, and technological developments are producing phenomena never before encountered in the industrial society. Brown^[3] states that the revolution will not flow from the mobilization of new machines; rather, it will require a fundamental revamp of the human context in which machines are used. Finally, Johnson ^[4] observes that when such paradigm shifts occur only once every few centuries, one has to be a visionary to see beyond the limits of current forms.

From a perspective of understanding this global societal sea change, Savage^[5] states that the shift is one of attitudes, values, and norms. It will only come through a struggle of thought because many of the changes are counterintuitive from a traditional point of view and they are difficult to conceptualize with industrial era vocabulary. He also notes that it will not be a simple or cumulative process, in that new principles will have to be learned and some old principles will have to be unlearned. Brown (1999) indicates that creating new frameworks for the evolving world will require challenging the assumptions that support our traditional intellectual constructs.

In terms of what will shift, Gilder^[6] states that the basic tenet of the knowledge revolution will be the “overthrow of matter.” Wealth, in the form of physical assets will diminish, while wealth, in the form of knowledge assets will increase. The power of mind will usurp the brute force of things. Similarly, Jeremy Rifkin^[7] indicates that whereas the industrial age emphasized the exchange of goods and services, the coming age will emphasize the exchange of concepts.

From an organizational perspective, Amidon^[8] indicates that the knowledge movement is reshaping how organizations are created, evolve, mature, and evolve or die. It is reshaping how business is done, how economies develop, and how societies prosper. Ruggles and Holtshouse^[9] note that the movement is characterized by a dispersion of power and by managers who lead by empowering knowledge workers to contribute and make decisions.

From a societal perspective, John Seely Brown^[10] asks a number of key questions, including who will control the keys to the digital domain? Who will be the trusted intermediary in the marketplace? How transparent will their mediation be? What standards will be used for accountability? Thomas A. Stewart^[11] points out that just as the industrial revolution did not end agriculture because people have to eat, this revolution will not end industry because we still need physical products.

The digital revolution is revolutionizing the future agriculture. Thus, future agriculture, more importantly, the agricultural systems modelling could benefit from the advancements in ICT with big data, crowdsourcing, remote sensing, and high computational abilities, catching up with the relative slow developments^{[citation needed]} over the last two decades. Tools to enable visualization of agricultural source data, model outputs and synthesized data products are needed to enhance the discovery and understanding of information for the entire spectrum of future agriculture users, including data collectors, model developers, model users, integrative research, application developers and end users. To make sense of large amounts of unfamiliar or complex data, humans need overviews, summaries, and the capability to look for patterns and discover emergent phenomena, empirical models, and theories related to the data.

See also

References

• Bar Ilan, Ziv. 2011. From Economy of Commodities to Economy of Ideas. Wiley-Blackwell, DMI Review p.44

0.00 (0 votes)