Quantitative analysis of technology futures. Part 2: Conceptual framework for positioning FTA techniques in policy appraisal

Quantitative techniques for exploring future developments in Science and Technology (here called Future-oriented Technology Analysis (FTA)) are increasingly important in an era of big data and growing computational power. New quantitative techniques such as social software, prediction markets, and quantitative scenarios are complementing more traditional foresight and forecasting techniques. While these techniques hold great promise, it is unclear how robust and appropriate is their use under different contexts. In order to help users think through their distinct values and limitations, in this paper we discuss quantitative FTA techniques in the light of a general analytical framework. Following Stirling \& Scoones (2009), we position FTA quantitative techniques according to their representation of (the incompleteness) of knowledge --i.e. the extent to which they portray their knowledge on probabilities and outcomes as problematic. This framework illuminates the implicit assumptions about the uncertainty, ambiguity and ignorance that distinct quantitative techniques make when exploring (in some cases "predicting'') the future. We distinguish between techniques that tend to `open up' awareness of new or unexpected futures, and others that tend to `close down' by pointing out to likely futures.Peer reviewe