Response to Comment by Walker et al. on “From Data to Decisions: Processing Information, Biases, and Beliefs for Improved Management of Natural Resources and Environments”

Glynn, Pierre D.; Voinov, Alexey; Shapiro, Carl; White, Paul

doi:10.1002/2018ef000819

Cited by 13 publications

(11 citation statements)

References 17 publications

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“…discussion and references in Glynn et al, 2022, this issue). BBHV and other behavioral and social factors mentioned in this paper affect everyone: information generators, consumers, funders, evaluators, decision makers, and even the most objective economists and scientists (Glynn, 2014;Glynn, 2017;Glynn et al, 2017;Glynn et al, 2018). Improving incorporation of these factors in VOI studies could provide a more holistic assessment of how and to what degree information influences decisions and resulting actions.…”

Section: Introductionmentioning

confidence: 94%

Value of Information and Decision Pathways: Concepts and Case Studies

Glynn

Rhodes²,

Chiavacci³

et al. 2022

Front. Environ. Sci.

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Information used in decision making arises from the structuring of observations and data. The collection, dissemination, and use of information has monetary and non-monetary costs (e.g., competition for attention) and necessitates trade-offs. Understanding the benefits of having information (i.e., the value of information, VOI), including resulting societal outcomes, is useful to information producers/funders and decision makers. Using theory, use cases, and hypotheticals, we describe how information (e.g., geospatial information) is valued and incorporated in decisions and actions related to managing natural resources, environments, and the impacts of natural and anthropogenic hazards. We discuss the nature of information and how it relates to models (conceptual, mental, scientific), beliefs, knowledge, and economic analyses. VOI approaches and behavioral factors that potentially affect information use and value are summarized. Framing of information and VOI through data to decision pathways (DDPs) at first simplifies understanding, then illustrates the benefits of information, and the human and societal challenges encountered in valuing and using it. We present approaches to overcome these challenges. Our transdisciplinary analysis concludes with a summary of critical issues affecting DDPs and VOI, and suggestions for improving both economic analyses and the actionability and use of information.

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Section: Introductionmentioning

confidence: 94%

Value of Information and Decision Pathways: Concepts and Case Studies

Glynn

Rhodes²,

Chiavacci³

et al. 2022

Front. Environ. Sci.

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“…While scientific advice may be, in the future, increasingly based on complex models, the environmental policies benefiting from these tools should head into the direction of more transparent and collaborative processes. It may be difficult to communicate the computational details of a black box model, but it is still necessary to communicate the logic behind the results, as well as the policy process that uses the models (Röckmann et al, 2012;Glynn et al, 2018;Jordan et al, 2018). To keep the participatory processes up with the advancements of the fast-developing computation capacity and modeling technology, substantial effort should be spent on developing tools and skills to support stakeholder participation and engagement.…”

Section: Actionable Recommendationsmentioning

confidence: 99%

Black Boxes and the Role of Modeling in Environmental Policy Making

Maeda

Haapasaari

Helle

et al. 2021

Front. Environ. Sci.

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Modeling is essential for modern science, and science-based policies are directly affected by the reliability of model outputs. Artificial intelligence has improved the accuracy and capability of model simulations, but often at the expense of a rational understanding of the systems involved. The lack of transparency in black box models, artificial intelligence based ones among them, can potentially affect the trust in science driven policy making. Here, we suggest that a broader discussion is needed to address the implications of black box approaches on the reliability of scientific advice used for policy making. We argue that participatory methods can bridge the gap between increasingly complex scientific methods and the people affected by their interpretations

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“…In particular, we do not know how much disagreement on how the system under study functions can persist without making it impossible for a group to agree on a course of action. We also do not know when joint, collaborative thinking, which can be quite helpful for group dynamics, becomes group thinking (Glynn et al, 2018) and turns into an obstacle for critical thinking and effective decision making.…”

Section: 1029/2018ef000841mentioning

confidence: 99%

Twelve Questions for the Participatory Modeling Community

et al. 2018

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Participatory modeling engages the implicit and explicit knowledge of stakeholders to create formalized and shared representations of reality and has evolved into a field of study as well as a practice. Participatory modeling researchers and practitioners who focus specifically on environmental resources met at the National Socio-Environmental Synthesis Center (SESYNC) in Annapolis, Maryland, over the course of 2 years to discuss the state of the field and future directions for participatory modeling. What follows is a description of 12 overarching groups of questions that could guide future inquiry.Participatory approaches to resource management must involve those who are affected by the decisions that stem from environmental management decisions (Reed et al., 2009). Environmental resource management often requires a combination of descriptive and normative knowledges as well as local capacity for action (and inaction). Because resource users have such knowledge and capacity, local engagement is crucial in PM. However, there are imbricated layers of power between researchers and locals-often with researchers holding the balance of power due to their increased access to social goods such as money, formal education,

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Response to Comment by Walker et al. on “From Data to Decisions: Processing Information, Biases, and Beliefs for Improved Management of Natural Resources and Environments”

Cited by 13 publications

References 17 publications

Value of Information and Decision Pathways: Concepts and Case Studies

Value of Information and Decision Pathways: Concepts and Case Studies

Black Boxes and the Role of Modeling in Environmental Policy Making

Twelve Questions for the Participatory Modeling Community

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