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

Autor: Bostrom A; Evans School of Public Policy & Governance, University of Washington, Seattle, Washington, USA., Demuth JL; Mesoscale & Microscale Meteorology Lab, National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA., Wirz CD; Mesoscale & Microscale Meteorology Lab, National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA., Cains MG; Mesoscale & Microscale Meteorology Lab, National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA., Schumacher A; Mesoscale & Microscale Meteorology Lab, National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA., Madlambayan D; Evans School of Public Policy & Governance, University of Washington, Seattle, Washington, USA., Bansal AS; Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado, USA., Bearth A; Consumer Behavior, Institute for Environmental Decisions, ETH Zürich, Zürich, Switzerland., Chase R; School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA., Crosman KM; Department of Marine Technology, Faculty of Engineering, Norwegian University of Science and Technology, Trondheim, Norway., Ebert-Uphoff I; Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado, USA., Gagne DJ 2nd; Computational & Information Systems Lab, National Center for Atmospheric Research, Boulder, Colorado, USA., Guikema S; Industrial & Operations Engineering, University of Michigan, Ann Arbor, Michigan, USA., Hoffman R; Institute for Human & Machine Cognition, Pensacola, Florida, USA., Johnson BB; Decision Research, Eugene, Oregon, USA., Kumler-Bonfanti C; Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA., Lee JD; Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA., Lowe A; Marine, Earth and Atmospheric Sciences, North Carolina State University, Raleigh, North Carolina, USA., McGovern A; School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA.; School of Computer Science, University of Oklahoma, Norman, Oklahoma, USA., Przybylo V; Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York, USA., Radford JT; Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado, USA., Roth E; Roth Cognitive Engineering, Brookline, Massachusetts, USA., Sutter C; Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York, USA., Tissot P; Conrad Blucher Institute for Surveying and Science, Texas A&M University-Corpus Christi, Corpus Christi, Texas, USA., Roebber P; School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA., Stewart JQ; Global Systems Laboratory, Oceanic and Atmospheric Research, National Oceanic and Atmospheric Administration, Boulder, Colorado, USA., White M; Conrad Blucher Institute for Surveying and Science, Texas A&M University-Corpus Christi, Corpus Christi, Texas, USA., Williams JK; The Weather Company, an IBM Business, Andover, Massachusetts, USA.
Jazyk: angličtina
Zdroj: Risk analysis : an official publication of the Society for Risk Analysis [Risk Anal] 2024 Jun; Vol. 44 (6), pp. 1498-1513. Date of Electronic Publication: 2023 Nov 08.
DOI: 10.1111/risa.14245
Abstrakt: 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.
(© 2023 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.)
Databáze: MEDLINE
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