Trust and trustworthy artificial intelligence: A research agenda for AI in the environmental sciences.

Demands to manage the risks of artificial intelligence (AI) are growing. These demands and the government standards arising from them both call for trustworthy AI. In response, we adopt a convergent approach to review, evaluate, and synthesize research on the trust and trustworthiness of AI in the environmental sciences and propose a research agenda. Evidential and conceptual histories of research on trust and trustworthiness reveal persisting ambiguities and measurement shortcomings related to inconsistent attention to the contextual and social dependencies and dynamics of trust. Potentially underappreciated in the development of trustworthy AI for environmental sciences is the importance of engaging AI users and other stakeholders, which human-AI teaming perspectives on AI development similarly underscore. Co-development strategies may also help reconcile efforts to develop performance-based trustworthiness standards with dynamic and contextual notions of trust. We illustrate the importance of these themes with applied examples and show how insights from research on trust and the communication of risk and uncertainty can help advance the understanding of trust and trustworthiness of AI in the environmental sciences.

The "Inter" Within Interdisciplinary Research: Strategies for Building Integration Across Fields.

As emphasis on interdisciplinary and convergent research grows, researchers and institutions can benefit from additional insights into how to build interdisciplinary integration within the research process. This article presents signs of successful interdisciplinary research and proposes strategies that researchers can implement to help create and sustain integration across fields. Drawing on the authors' experiences, other examples from hazards research, and the literature on interdisciplinarity, the article asserts that successful interdisciplinary research incorporates full intellectual participation by each contributing field, forming a multiway partnership. Such work can frame new research questions, develop novel approaches, and generate innovative insights across and within disciplines. It can also address complex questions at the intersections of established fields, beyond what the collection of contributing fields can produce on their own. To build integration across fields, researchers can use strategies such as interweaving perspectives in the research foci, interacting regularly at the working level, and interconnecting knowledge and ideas throughout the research process. Another strategy is leadership that enables contributions from multiple fields and empowers interdisciplinary synthesis. During the research process, researcher commitment, curiosity, willingness to take risks, and flexibility are also important, along with patience and persistence as challenges arise.

Explicating Experience: Development of a Valid Scale of Past Hazard Experience for Tornadoes.

People's past experiences with a hazard theoretically influence how they approach future risks. Yet, past hazard experience has been conceptualized and measured in wide-ranging, often simplistic, ways, resulting in mixed findings about its relationship with risk perception. This study develops a scale of past hazard experiences, in the context of tornadoes, that is content and construct valid. A conceptual definition was developed, a set of items were created to measure one's most memorable and multiple tornado experiences, and the measures were evaluated through two surveys of the public who reside in tornado-prone areas. Four dimensions emerged of people's most memorable experience, reflecting their awareness of the tornado risk that day, their personalization of the risk, the intrusive impacts on them personally, and impacts experienced vicariously through others. Two dimensions emerged of people's multiple experiences, reflecting common types of communication received and negative emotional responses. These six dimensions are novel in that they capture people's experience across the timeline of a hazard as well as intangible experiences that are both direct and indirect. The six tornado experience dimensions were correlated with tornado risk perceptions measured as cognitive-affective and as perceived probability of consequences. The varied experience-risk perception results suggest that it is important to understand the nuances of these concepts and their relationships. This study provides a foundation for future work to continue explicating past hazard experience, across different risk contexts, and for understanding its effect on risk assessment and responses.

"Know What to Do If You Encounter a Flash Flood": Mental Models Analysis for Improving Flash Flood Risk Communication and Public Decision Making.

Understanding how people view flash flood risks can help improve risk communication, ultimately improving outcomes. This article analyzes data from 26 mental models interviews about flash floods with members of the public in Boulder, Colorado, to understand their perspectives on flash flood risks and mitigation. The analysis includes a comparison between public and professional perspectives by referencing a companion mental models study of Boulder-area professionals. A mental models approach can help to diagnose what people already know about flash flood risks and responses, as well as any critical gaps in their knowledge that might be addressed through improved risk communication. A few public interviewees mentioned most of the key concepts discussed by professionals as important for flash flood warning decision making. However, most interviewees exhibited some incomplete understandings and misconceptions about aspects of flash flood development and exposure, effects, or mitigation that may lead to ineffective warning decisions when a flash flood threatens. These include important misunderstandings about the rapid evolution of flash floods, the speed of water in flash floods, the locations and times that pose the greatest flash flood risk in Boulder, the value of situational awareness and environmental cues, and the most appropriate responses when a flash flood threatens. The findings point to recommendations for ways to improve risk communication, over the long term and when an event threatens, to help people quickly recognize and understand threats, obtain needed information, and make informed decisions in complex, rapidly evolving extreme weather events such as flash floods.

Factors Affecting Hurricane Evacuation Intentions.

Protective actions for hurricane threats are a function of the environmental and information context; individual and household characteristics, including cultural worldviews, past hurricane experiences, and risk perceptions; and motivations and barriers to actions. Using survey data from the Miami-Dade and Houston-Galveston areas, we regress individuals' stated evacuation intentions on these factors in two information conditions: (1) seeing a forecast that a hurricane will hit one's area, and (2) receiving an evacuation order. In both information conditions having an evacuation plan, wanting to keep one's family safe, and viewing one's home as vulnerable to wind damage predict increased evacuation intentions. Some predictors of evacuation intentions differ between locations; for example, Florida respondents with more egalitarian worldviews are more likely to evacuate under both information conditions, and Florida respondents with more individualist worldviews are less likely to evacuate under an evacuation order, but worldview was not significantly associated with evacuation intention for Texas respondents. Differences by information condition also emerge, including: (1) evacuation intentions decrease with age in the evacuation order condition but increase with age in the saw forecast condition, and (2) evacuation intention in the evacuation order condition increases among those who rely on public sources of information on hurricane threats, whereas in the saw forecast condition evacuation intention increases among those who rely on personal sources. Results reinforce the value of focusing hurricane information efforts on evacuation plans and residential vulnerability and suggest avenues for future research on how hurricane contexts shape decision making.

Flash Flood Risks and Warning Decisions: A Mental Models Study of Forecasters, Public Officials, and Media Broadcasters in Boulder, Colorado.

Timely warning communication and decision making are critical for reducing harm from flash flooding. To help understand and improve extreme weather risk communication and management, this study uses a mental models research approach to investigate the flash flood warning system and its risk decision context. Data were collected in the Boulder, Colorado area from mental models interviews with forecasters, public officials, and media broadcasters, who each make important interacting decisions in the warning system, and from a group modeling session with forecasters. Analysis of the data informed development of a decision-focused model of the flash flood warning system that integrates the professionals' perspectives. Comparative analysis of individual and group data with this model characterizes how these professionals conceptualize flash flood risks and associated uncertainty; create and disseminate flash flood warning information; and perceive how warning information is (and should be) used in their own and others' decisions. The analysis indicates that warning system functioning would benefit from professionals developing a clearer, shared understanding of flash flood risks and the warning system, across their areas of expertise and job roles. Given the challenges in risk communication and decision making for complex, rapidly evolving hazards such as flash floods, another priority is development of improved warning content to help members of the public protect themselves when needed. Also important is professional communication with members of the public about allocation of responsibilities for managing flash flood risks, as well as improved system-wide management of uncertainty in decisions.