How can geologic decision making under uncertainty be improved?

Cristina G. Wilson (Corresponding Author), Clare E Bond, Thomas F. Shipley

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
5 Downloads (Pure)


In the geosciences, recent attention has been paid to the influence of uncertainty on expert decision making. When making decisions under conditions of uncertainty, people tend to employ heuristics (rules of thumb) based on experience, relying on their prior knowledge and beliefs to intuitively guide choice. Over 50 years of decision making research in cognitive psychology demonstrates that heuristics can lead to less-than-optimal decisions, collectively referred to as biases. For example, the availability bias occurs when people make judgments based on what is most dominant or accessible in memory; a geoscientist who has spent the past several months studying strike-slip faults will have this terrain most readily available in her mind when interpreting new seismic data. Given the important social and commercial implications of many geoscience decisions, there is a need to develop effective interventions for removing or mitigating decision bias. In this paper, we outline the key insights from decision making research about how to reduce bias and review the literature on debiasing strategies. First, we define an optimal decision, since improving decision making requires having a standard to work towards. Next, we discuss the cognitive mechanisms underlying decision biases and describe three biases that have been shown to influence geoscientists decision making (availability bias, framing bias, anchoring bias). Finally, we review existing debiasing strategies that have applicability in the geosciences, with special attention given to those strategies that make use of information technology and artificial intelligence (AI). We present two case studies illustrating different applications of intelligent systems for the debiasing of geoscientific decision making, where debiased decision making is an emergent property of the coordinated and integrated processing of human-AI collaborative teams.

“Evidently, if the investigator is to succeed in the discovery of veritable explanations of phenomena, he must be fertile in the invention of hypotheses and ingenious in the application of tests. The practical questions for the teacher are, whether it is possible by training to improve the guessing faculty, and if so, how it is to be done. To answer these, we must give attention to the nature of the scientific guess considered as a mental process. Like other mental processes, the framing of hypotheses is usually unconscious, but by attention it can be brought into consciousness and analyzed.”
– G.K. Gilbert (1886)
Original languageEnglish
Pages (from-to)1469-1488
Number of pages19
JournalSolid earth
Issue number5
Publication statusPublished - 3 Sep 2019


  • uncertainty
  • decision bias
  • digital nudge


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