Keep it complex

Managing uncertainty, ambiguity and ignorance in impact assessment by embedding evolutionary resilience, participatory modelling and adaptive management

“…In one example, a Gaussian plume model was compared against tracer data in two urban settings in the USA and found to both over-and under-predict concentrations at different receptors (Hanna and Baja, 2009). There is also evidence that complex prediction leads to a focus on smaller areas of certainty, at the expense of other issues that are no less important, but which cannot be predicted with any certainty; similarly, organisations might make simplifying assumptions that set inappropriately restricted boundaries around the issues to be investigated (Turner, 1976;Stirling, 2010). Duncan (2013) acknowledges the complexity of uncertainty and comments on the reality of IA practice whereby uncertainties are communicated by a range of actors drawing on different narratives of the potential consequences posed by uncertainties; he therefore suggests a constructivist perspective needs to be taken when dealing with uncertainty in IA, again calling into question the existing rationalist theoretical framings of impact assessment.…”

“…The "impact" Assessment, 2009, p.1). We distinguish ambiguity, uncertainty and ignorance from risk after Stirling (2010) as illustrated in Figure 1, which also suggests appropriate qualitative and quantitative methods for identifying and/or managing these types of knowledge. Stirling (2010) argues that a narrow focus on risk, which commonly informs many decisionmaking processes and often underpins IA processes in practice, inadequately considers incomplete knowledge and can therefore lead to decisions that ultimately prove to be poor.…”

“…We distinguish ambiguity, uncertainty and ignorance from risk after Stirling (2010) as illustrated in Figure 1, which also suggests appropriate qualitative and quantitative methods for identifying and/or managing these types of knowledge. Stirling (2010) argues that a narrow focus on risk, which commonly informs many decisionmaking processes and often underpins IA processes in practice, inadequately considers incomplete knowledge and can therefore lead to decisions that ultimately prove to be poor. He recommends that attention be paid to more "neglected areas of uncertainty" (Stirling, 2010(Stirling, , p.1030 including ambiguity and ignorance (and this generic meaning for uncertainty, encompassing uncertainty, ambiguity and ignorance will be used in this paper); thus the focus of this paper will be on ambiguity, uncertainty and ignorance, and not on risk.…”

“…Stirling (2010) argues that a narrow focus on risk, which commonly informs many decisionmaking processes and often underpins IA processes in practice, inadequately considers incomplete knowledge and can therefore lead to decisions that ultimately prove to be poor. He recommends that attention be paid to more "neglected areas of uncertainty" (Stirling, 2010(Stirling, , p.1030 including ambiguity and ignorance (and this generic meaning for uncertainty, encompassing uncertainty, ambiguity and ignorance will be used in this paper); thus the focus of this paper will be on ambiguity, uncertainty and ignorance, and not on risk. In IA, uncertainty is a recognised problem (de Jongh, 1988;Geneletti et al, 2003;Liu et al, 2010), although ambiguity and ignorance have received much less attention (a simple illustration is based on the number of results returned by the Scopus database at the time of writing considering the search terms "impact assessment" AND "uncertainty" (1,551), "ambiguity" (31) and "ignorance" (18) respectively), except where uncertainty is used as more of an umbrella term where ambiguity and ignorance are not distinguished.…”

Towards a Reflexive Turn in the Governance of Global Environmental Expertise. The Cases of the IPCC and the IPBES

“…Indeed, the fact of this being a "choice" at all is often exactly the point at issue. The value lies more in opening up appreciations of choice than in closing these down (Stirling 2010). These choices concern the criteria for, inter alia, evaluating scientific evidence, setting standards for knowledge validity, selecting experts, organizing review procedures, and demarcating mandates between scientific and political institutions (Jasanoff 2012).…”