Opening new institutional spaces for grappling with uncertainty: A constructivist perspective

Abstract

In the context of an increasing reliance on predictive computer simulation models to calculate potential project impacts, it has become common practice in impact assessment (IA) to call on proponents to disclose uncertainties in assumptions and conclusions assembled in support of a development project. Understandably, it is assumed that such disclosures lead to greater scrutiny and better policy decisions. This paper questions this assumption. Drawing on constructivist theories of knowledge and an analysis of the role of narratives in managing uncertainty, I argue that the disclosure of uncertainty can obscure as much as it reveals about the impacts of a development project. It is proposed that the opening up of institutional spaces that can facilitate the negotiation and deliberation of foundational assumptions and parameters that feed into predictive models could engender greater legitimacy and credibility for IA outcomes.

Analysis of uncertainty consideration in environmental assessment: an empirical study of Canadian EA practice

“…Different types of uncertainty can be distinguished, some of which may be possible to quantify (e.g., Benetto, Dujet, and Rousseaux 2006, Peche and Rodriguez 2011, Ross, Booker, and Montoya 2013, while other types are not due to lack of knowledge about the components and structure of the environmental or socioeconomic systems affected (Duncan 2013;Bond et al 2015). For each environmental component (e.g., air, water, soils, wildlife) identified in each EIS, specific uncertainties in mitigation, contingency plans, and follow-up programs were then categorized based on: (1) what the uncertainty was generally about; (2) the nature and level of uncertainty disclosure; and (3) how the uncertainty was addressed.…”

“…There has been much written on the need to better communicate uncertainties in EA practice and the implications of non-disclosure (Duncan 2013;Wardekker et al 2008). Yet, given the hundreds of impact predictions and mitigation measures identified across the 12 EAs in our sample, our results reflect the findings of Tennøy, Kvaerner, and Gjerstad (2006) and Wiklund (2011) in that uncertainties are not fully disclosed in EA practice and EA documents often portray a degree of confidence that may not exist.…”

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

“…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. Furthermore, and more fundamentally still, the psychologist Kahneman (2013) points out that individual humans inevitably rapidly arrive at simplistic understandings of complex situations as a direct function of how our brains work with respect to favouring intuition and easy or lazy answers.…”

The precautionary principle and management of uncertainties in EIAs – analysis of waste incineration cases in Finland

“…In general, they believe in different forms of participant engagement, positive planning and mutual learning, and remind us that we should also look beyond decision-making events -IA processes should be seen more as possibilities for learning than they now are. For example, Duncan (2013) has recently suggested that IAs need institutional spaces for uncertainty disclosure and that facilitating negotiation and deliberation could engender greater legitimacy and credibility for IA outcomes.…”

“…In this way the information reduces the uncertainty surrounding the plans and its effects, and aids in risk evaluation. On the flip side, it has been noted that this reduction is often flawed in practice, leaving socio interactive aspects of uncertainties unexamined (Duncan 2008(Duncan , 2013 or, more generally, EIAs are seen to fall short in descriptions of uncertainties or their management altogether (Tennoy et al 2006).…”