Journal of the National Research University Higher School of Economics

Policymakers responsible for improving the skill base needed for future economic development must assess the implications of radical technological change in the future.  The example selected here is in nanoscience and nanotechnology. The objective of this paper is to demonstrate the importance of using more than one scenario of long term development when assessing such a complex issue as technology development and the demand for skills. Scenario forecasting is appropriately based on assessing plausible alternatives combined with horizon-scanning and determination of “weak signals”.  This procedure will provide early warning about how far the key elements of various scenarios  become manifest and those with maximum influence on emerging trends.

This procedural approach for forecasting future skills needs in a particular technology is to estimate short-term and medium-term prospects for its development from concrete scenarios. Nanotechnology, the paper shows, due to its relative infancy, its composition of numerous lines of knowledge development, and the many contested claims about the scope and speed of its evolution, poses particular challenges.

The paper assesses how confident we can be about skill and employment projections related to nanoindustries – and industrial applications of nanotechnology, i.e. in medicine; chemistry and the environment; energy; information and communication; heavy industry; and consumer goods. It proposes ways in which to provide more policy-relevant intelligence. Future skills forecasts, it argues, can be shaped using familiar ideas from innovation research - about technological paradigms and trajectories, and about diffusion and industry life-cycles. Requirements for skills will vary depending on how revolutionary nanotechnologies will be.  Will innovation essentially extend existing nanoengineering techniques or embody more radical visions of molecular engineering and “bottom up” nanotechnologies? Responses to these questions can be derived from expert-based alternative scenarios.