Increasing knowledge-intensity and complexity :nanotechnology and the future of public participation and policy making

Abstract

In recent years, both policy-makers and politicians have been confronted with increasing obstacles towards the interpretation, usage, prediction and application of data, information and of knowledge. This has often resulted in surprises, for instance, as predicted outcomes of introduced policy changes, either did not take effect or simply took on other forms that were not desired. Added to that, new developments and advances in a number of key technological areas have led to the emergence of new knowledge-intensive and technologically-complex disciplines, such as Nanotechnology, Genetic Engineering or Synthetic Biology. The complexity that is inherent in any of these new disciplines poses new challenges to both policy-making and public participation. This thesis focuses on the question of whether increasing complexity and knowledge-intensity that follow current and future technological developments will lead to a decrease in both the public’s interests and ability to participate in the public debate. In addition, this thesis will investigate how policy recommendations are affected when the dependency on expertise, which is due to the inherent knowledge-intensity of these new disciplines, is on the rise. Nanotechnology has been chosen as an example case of one of these new knowledge-intensive and technologically-complex disciplines. By developing and employing a knowledge framework that is based on a practical approach to distinguishing various types of knowledge; public and expert opinions as well as policy recommendations will be analysed in order to determine whether a new approach for involving the public and for the future of policy recommendation is required. Furthermore, by applying this knowledge framework to three selected theories of policy process, special emphasis is placed on the applicability of different types of knowledge and information in policy contexts. An additional aim is to assess the use of terms, such as information and knowledge, in the policy sciences. Using these different types of knowledge, for instance, by making a deliberate distinction between knowledge by acquaintance and knowledge by description, or between tacit knowledge and explicit knowledge, allows identifying what can be known by whom, and thus will shed new light on both policy recommendations and on what can be expected from the public’s involvement in the future. This thesis will suggest that when dealing with knowledge-intensive and technologically-complex disciplines, the importance of acknowledging different types of knowledge is a prerequisite for improving the quality of policy-making, policy recommendations as well as public engagement. Also, a case will be made against a generic use of the terms knowledge and information in policy literature. As much as policy information does not equal any generic type of information, lacking specificity with regards to information and knowledge in the theories of policy may invalidate or at least challenge some claims made policy scientists, as expected outcomes that apply to one particular type of information may not automatically apply to another.