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

被引:13
|
作者
Bostrom, Ann [1 ]
Demuth, Julie L. [2 ]
Wirz, Christopher D. [2 ]
Cains, Mariana G. [2 ]
Schumacher, Andrea [2 ]
Madlambayan, Deianna [1 ]
Bansal, Akansha Singh [3 ]
Bearth, Angela [4 ]
Chase, Randy [5 ]
Crosman, Katherine M. [6 ]
Ebert-Uphoff, Imme [3 ]
Gagne, David John [7 ]
Guikema, Seth [8 ]
Hoffman, Robert [9 ]
Johnson, Branden B. [10 ]
Kumler-Bonfanti, Christina [11 ]
Lee, John D. [12 ]
Lowe, Anna [13 ]
McGovern, Amy [5 ,14 ]
Przybylo, Vanessa [15 ]
Radford, Jacob T. [3 ]
Roth, Emilie [16 ]
Sutter, Carly [15 ]
Tissot, Philippe [17 ]
Roebber, Paul [18 ]
Stewart, Jebb Q. [19 ]
White, Miranda [17 ]
Williams, John K. [20 ]
机构
[1] Univ Washington, Evans Sch Publ Policy & Governance, Seattle, WA 98195 USA
[2] Natl Ctr Atmospher Res NCAR, Mesoscale & Microscale Meteorol Lab, Boulder, CO 80305 USA
[3] Colorado State Univ, Cooperat Inst Res Atmosphere, Ft Collins, CO USA
[4] Swiss Fed Inst Technol, Inst Environm Decis, Consumer Behav, Zurich, Switzerland
[5] Univ Oklahoma, Sch Meteorol, Norman, OK USA
[6] Norwegian Univ Sci & Technol, Fac Engn, Dept Marine Technol, Trondheim, Norway
[7] Natl Ctr Atmospher Res, Computat & Informat Syst Lab, Boulder, CO USA
[8] Univ Michigan, Ind & Operat Engn, Ann Arbor, MI USA
[9] Inst Human & Machine Cognit, Pensacola, FL USA
[10] Decis Res, Eugene, OR USA
[11] Univ Colorado Boulder, Cooperat Inst Res Environm Sci, Boulder, CO USA
[12] Univ Wisconsin Madison, Ind & Syst Engn, Madison, WI USA
[13] North Carolina State Univ, Marine Earth & Atmospher Sci, Raleigh, NC USA
[14] Univ Oklahoma, Sch Comp Sci, Norman, OK USA
[15] SUNY Univ, Dept Atmospher & Environm Sci, Albany, NY USA
[16] Roth Cognit Engn, Brookline, MA USA
[17] Texas A&M Univ Corpus Christi, Conrad Blucher Inst Surveying & Sci, Corpus Christi, TX USA
[18] Univ Wisconsin Milwaukee, Sch Freshwater Sci, Milwaukee, WI USA
[19] NOAA, Global Syst Lab, Ocean & Atmospher Res, Boulder, CO USA
[20] Weather Co, IBM Business, Andover, MA USA
基金
美国国家科学基金会;
关键词
artificial intelligence (AI); environmental science; risk communication; trust; trustworthiness; SEVERE WEATHER; BLACK-BOX; PART; RISK; UNCERTAINTY; AUTOMATION; PREDICTION; MODEL; DIMENSIONALITY; COMMUNICATION;
D O I
10.1111/risa.14245
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页码:1498 / 1513
页数:16
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