Answers to questions on uncertainty in geography: old lessons and new scenario tools

In many domains, including geography, there can be the implicit assumption that improved data-analysis and statistical modelling must lead to improved policymaking, and its perceived failure to do so can be disconcerting. Yet, this assumption overlooks the fundamental distinction between epistemological and ontological uncertainty, as discussed herein. Epistemological uncertainty describes the known and bounded inaccuracy of our knowledge about the world as now. Whereas ontological uncertainty describes the rendering completely obsolete of this present knowledge by surprises in the form of currently unknown future events, and by cascading changes to beliefs, attitudes and behaviours made by diverse actors in response to - and in anticipation of others’ responses to - new developments. This paper does the following: 1) shows that, because of ontological uncertainty, improved data-analysis and statistical modelling can never lead straightforwardly to improved policymaking, no matter how well implemented; 2) outlines how probability-based tools offer little assistance with ontological uncertainty because they are based on present perceptions of future possibilities; 3) urges geographers to reconcile with ontological uncertainty as a source of potentially transformational change, rather than viewing it as a problem to be overcome, or something to be defended against; 4) reviews a range of new, non-probabilistic scenario tools that, when used in combination, can assist in harnessing ontological uncertainty for transformational purposes by surfacing what is to be gained and by whom from enabling, blocking or altering intended policy outcomes, and by searching for future possibilities unconstrained by the present.

Derbyshire, J. (2019). Answers to questions on uncertainty in geography: Old lessons and new scenario tools. Environment and Planning A: Economy and Space, 52(4), 710–727. Copyright © 2019 The Author. DOI: https://doi.org/10.1177/0308518X19877885