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Paul A. White

Publications and source records attributed to Paul A. White.

2 recordsLinked to original sources

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”

Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). The comment by Walker et al. (2018, https://doi.org/10.1002/2017EF000750 ) illustrates several points made by Glynn et al. (2017, https://doi.org/10.1002/2016EF000487 ) and many other articles. Namely, biases and beliefs often drive scientific reasoning, and scientists, just like other humans, are intimately attached to their values and heuristics. Scientists, just like many other people, also tend to read and interpret text in ways that best match their individual perceptions of a problem or issue: in many cases paraphrasing and changing the meaning of what they read to better match their initial ideas. Walker et al. are doing interesting and important research on uncertainty. Nonetheless, they misinterpret the work, assumptions, and conclusions brought forth by Glynn et al. (2017, https://doi.org/10.1002/2016EF000487 ).

Earth's Future

From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments

Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). Derived from these types of minds, innate biases, beliefs, heuristics, and values (BBHV) influence behaviors, often beneficially, when individuals or small groups face immediate, local, acute situations that they and their ancestors faced repeatedly in the past. BBHV, though, need to be recognized and possibly countered or used when facing new, complex issues or situations especially if they need to be managed for the benefit of a wider community, for the longer-term and the larger-scale. Taking BBHV into account, we explain and provide a cyclic science-infused adaptive framework for (1) gaining knowledge of complex systems and (2) improving their management. We explore how this process and framework could improve the governance of science and policy for different types of systems and issues, providing examples in the area of natural resources, hazards, and the environment. Lastly, we suggest that an “Open Traceable Accountable Policy” initiative that followed our suggested adaptive framework could beneficially complement recent Open Data/Model science initiatives.

Earth's Future