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Persistent Forecasting of Disruptive Technologies
FIGURE 3-5 Steroid product for athletes. SOURCE: Reprinted with permission from Custom Medical Stock Photo.
Another example is the Internet, which was originally envisioned as a means for researchers to communicate with one another and to share the computational resources of powerful research computers no matter where they were.9 The Internet subsequently became a global backbone for communications and now supports a diverse array of applications for which it was never designed. One of the “applications” supported by the Internet is the delivery of cyberattacks, which have significant disruptive potential. Thus, to assess this potential for a given technology sector or application, forecasters must ask “What else?”
This chapter has overviewed the general features of disruptive technologies that must be considered, such as the attributes, categories, and timelines associated with these technologies. The timeline of a technology’s deployment does not necessarily need to be very short for the technology to be considered disruptive, and its cycle can vary, with most technologies undergoing a series of S-curves of growth and development during their lifetimes. Approaches to assessing the likelihood of a given technology disruption were also discussed, including the impact of geographic, demographic, cultural, and social factors. Signposts (metrics that can be used to anticipate the development of a disruptive technology) were emphasized.
Chapters 4 and 5 specifically address the characteristics of a forecasting system for disruptive technologies, including how bias can affect a forecast and the necessary attributes of such a system.