Truly collaborative scientific field data collection between human scientists and autonomous robot systems requires a shared understanding of the search objectives and tradeoffs faced when making decisions. Therefore, critical to developing intelligent robots to aid human experts is an understanding of how scientists make such decisions and how they adapt their data collection strategies when presented with new information
- NSF-PAR ID:
- 10223578
- Date Published:
- Journal Name:
- Cognitive Research: Principles and Implications
- Volume:
- 6
- Issue:
- 1
- ISSN:
- 2365-7464
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
in situ . In this study, we examined the dynamic data collection decisions of 108 expert geoscience researchers using a simulated field scenario. Human data collection behaviors suggested two distinct objectives: an information-based objective to maximize information coverage and a discrepancy-based objective to maximize hypothesis verification. We developed a highly simplified quantitative decision model that allows the robot to predict potential human data collection locations based on the two observed human data collection objectives. Predictions from the simple model revealed a transition from information-based to discrepancy-based objective as the level of information increased. The findings will allow robotic teammates to connect experts’ dynamic science objectives with the adaptation of their sampling behaviors and, in the long term, enable the development of more cognitively compatible robotic field assistants. -
more » « less
Abstract Understanding and communicating uncertainty is a key skill needed in the practice of science. However, there has been little research on the instruction of uncertainty in undergraduate science education. Our team designed a module within an online geoscience field course which focused on explicit instruction around uncertainty and provided students with an uncertainty rating scale to record and communicate their uncertainty with a common language. Students then explored a complex, real-world geological problem about which expert scientists had previously made competing claims through geologic maps. Provided with data, expert uncertainty ratings, and the previous claims, students made new geologic maps of their own and presented arguments about their claims in written form. We analyzed these reports along with assessments of uncertainty. Most students explicitly requested geologists’ uncertainty judgments in a post-course assessment when asked why scientists might differ in their conclusions and/or utilized the rating scale unprompted in their written arguments. Through the examination of both pre- and post-course assessments of uncertainty and students’ course-based assessments, we argue that explicit instruction around uncertainty can be introduced during undergraduate coursework and could facilitate geoscience novices developing into practicing geoscientists.
-
Abstract. 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; geoscientists who have spent the past several months studying strike-slip faults will have this terrain most readily available in their 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 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, wherein debiased decision-making is an emergent property of the coordinated and integrated processing of human–AI collaborative teams.more » « less
-
more » « less
Abstract. 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, a geologist who confidently interprets ambiguous data as representative of a familiar category form their research (e.g., strike slip faults for expert in extensional domains) is exhibiting the availability bias, which occurs when people make judgments based on what is most dominant or accessible in memory. 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 summarize 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.
-
null (Ed.)The earth sciences, all sciences, are doing more and more of their activities online. Although moving online was previously a well-established trend, the COVID-19 crisis has accelerated this, as faculty, teachers, and students came to understand all too well during 2020. Ordinary activities, such as field trips, field camps, and even professional meetings like GSA 2020 Connects Online, have moved mostly online (Tikoff et al., 2020). We have had to devise new ways of teaching that are entirely outside of our experience. Rather than wistfully wishing for a return to times past, the current situation is an opportunity to explore change and depart from our old ways of doing things, striving to make our science and our geology richer to each other. Returning to and reliving the past is what we do in our geology, but it should not be what we do as geologists and scientists. At the same time, it is becoming more critical for earth scientists, and all scientists, to better engage the public and stakeholders in their work, their data, and their insights and conclusions. We have been facing not only a pandemic of disease but also a pandemic of climate change accompanied by the malady of denying science. Because the subject of geology is our shared planet and environment, geoscientists can present much of their work in a way that is relevant to the public. We have an advantage in that the public can see what we do, look directly at what we study, and appreciate where samples come from for our analyses. The basis of our science surrounds us. The online world further opens our science, whether in geologic maps, pictures of thin sections of rocks, or a numerical age for a sample, to general observation. This new openness and connectedness can give us the power of remote participation and accessmore » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1186/s41235-021-00296-z
