Persistent Forecasting of Disruptive Technologies—Report 2 (2010) / Chapter Skim
Currently Skimming:
3 Analysis and Final Thoughts
3 Analysis and Final Thoughts
Pages 48-64
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 48... ...
-- Vaclav Havel Having outlined several frameworks that could be used to develop an operational version of an advanced forecasting system, the Committee on Forecasting Future Disruptive Technologies discussed further the challenges in building a next-generation forecasting system and what methods and actions would help ensure such a system's success. To that end, this chapter discusses the following: whether a next-generation persistent disruptive technol ogy forecasting system can be built using existing technologies and methods, the features and characteristics of a next-generation forecasting system, and laying the foundation for subsequent steps.
|
From page 49... ...
The illustrative models developed at the workshop indicate that the design and building of a 1.0 version persistent forecasting system for disruptive technologies are possible using existing technologies and forecasting methods and can be achieved within a reasonable time frame using a modest level of human and financial resources. FEATuRES OF A NEXT-gENERATION SySTEM Six Functions of the version Independent of the forecasting model used, a version 1.0 system for forecasting disruptive technologies should provide stakeholders and decision makers with a current forecast of potential futures and the potential disruptive technologies and impacts that would be the drivers of those futures as the current forecast applies to the stake holders' and decision makers' domain of interest.
|
From page 50... ...
The use of Narrative to Initiate Analysis In its first report, the committee used a traditional model of forecasting to postulate a process: �When forecasting a disruptive technology, forecasters should use reasoned analysis and seek expert advice to understand what are the required foundational technologies and tools to engineer a new innovation. Estimating the timing of disruptive technologies requires an understanding of the sequence and an estimation of the timing of the emergence of foundational technologies and enabling tools�� (NRC, 2010, p.
|
From page 51... ...
A disruptive technology forecasting system focuses on technological wildcards: innovations that have a low or unknown probability of development but, if developed, would have enormous impact.
|
From page 52... ...
From that narrative idea, analysts or participants generate hypoth eses, map and define potential scenarios of enabling technologies that could bring that future to pass, analyze scenarios and technologies, and then iterate narratives and hypotheses with additional data. Nothing is thrown away.
|
From page 53... ...
. A narrative incorporating a strong use case would be a valuable tool in convincing stakeholders of the possibility of the extreme scenarios that a disruptive forecasting system is designed to help foresee.
|
From page 54... ...
To be successful, those setting up the persistent forecasting system would have to work hard to balance Western bias against a wider worldview. This is explored in more detail in Chapter 4 of the first report (NRC, 2010)
|
From page 55... ...
CHARACTERISTICS OF A NEXT-gENERATION FORECASTINg SySTEM While all of the models outlined in Chapter 2 had the essential elements discussed previously in this chapter, the desired characteristics for the next-generation forecasting system will need to be defined both for the 1.0 system and for future spirals of development of the persistent forecasting system. Suggested characteristics include mechanisms for continual learning, success metrics for participation, and success metrics for outputs.
|
From page 56... ...
They would be valuable for opening possibilities in people's thinking, anticipating disruptive scenarios, and providing a useful framework for tracking the development of disruptive technologies. Observation.
|
From page 57... ...
; • It receives positive feedback from potential customers; • It generates value (might be intellectual, literary, as well as for future planning) ; • It has information incorporated into other organizations' analyses, reverse citation; • It trains future policy leaders in the effective use of technology forecasts; • It causes new policies to be generated; • It survives: the system continues; • It improves the ability of decision makers to continuously ask the right questions; and • It reduces surprise.
|
From page 58... ...
The team should be given seed-level funding to establish an organizational structure and business plan and build a working 1.0 version of a disruptive technology forecasting system. The organization should have to attract additional funds from domestic and foreign corporate, nonprofit, or government sources.
|
From page 59... ...
Would staff of the open system simply maintain the system and allow the work product to be solely open-sourcederived, or would the staff �add value�� by doing analysis and generating internal narratives, hypotheses, needs, technology, and uses that run parallel to the crowdsourcing process? The participants of the workshop believe that the advantage of this crowdsourcing, persistent approach is the use of an iterative process in which new ideas and forecasts are generated through crowdsourcing and live data-gathering activities, followed by concept refinement performed by experts.
|
From page 60... ...
or join a discussion thread that contributes posts, which are flagged as technologies, uses, progression, or synthesis. This input is used to help flesh out the signals, signposts, enabling technologies, or whatever else is needed for a scenario to be realized and to identify potential intended or unintended �off label�� uses and outcomes.
|
From page 61... ...
The forecasting team should also develop midcourse evaluations and make midcourse corrections based on the ability of 1.0 to achieve these goals. CONCLuSION Forming a successful forecasting system for disruptive technologies is a task with several inherent challenges that are both a direct result of the new explosion of information exchange brought about by the ubiquity of the Internet and suggested solutions to the challenges posed by it.
|
From page 63... ...
Appendixes
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.