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 e...

Full description

Saved in:
Bibliographic Details
Published in:Risk analysis 2024-06, Vol.44 (6), p.1498-1513
Main Authors: Bostrom, Ann, Demuth, Julie L., Wirz, Christopher D., Cains, Mariana G., Schumacher, Andrea, Madlambayan, Deianna, Bansal, Akansha Singh, Bearth, Angela, Chase, Randy, Crosman, Katherine M., Ebert‐Uphoff, Imme, Gagne, David John, Guikema, Seth, Hoffman, Robert, Johnson, Branden B., Kumler‐Bonfanti, Christina, Lee, John D., Lowe, Anna, McGovern, Amy, Przybylo, Vanessa, Radford, Jacob T., Roth, Emilie, Sutter, Carly, Tissot, Philippe, Roebber, Paul, Stewart, Jebb Q., White, Miranda, Williams, John K.
Format: Article
Language:English
Subjects:
Artificial intelligence
artificial intelligence (AI)
Credibility
Development strategies
Environmental science
Measurement
R&D
Research & development
Risk assessment
Risk communication
Trust
Trustworthiness
Uncertainty
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0272-4332
1539-6924
DOI:10.1111/risa.14245