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Scientific Paper · source-verified
A Call for Transdisciplinary Trust in the AI Era
Krueger et al. · 2025-07-18
Trust is a cornerstone and enabler of human civilization, determining the very nature of how people interact with each other. The swift integration of artificial intelligence (AI) into daily life poses grand societal challenges and necessitates a reevaluation of trust. Our bibliometric literature review calls for scientists and stakeholders to cross traditional academic boundaries to address emerging and evolving societal challenges arising from AI. We propose a transdisciplinary research framework to understand and bolster trust in AI and address grand challenges in domains as diverse and urgent as misinformation, discrimination, and warfare.
Source identity and required public metadata were editorially reviewed on 2026-09-15.
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Krueger et al.. 2025-07-18. A Call for Transdisciplinary Trust in the AI Era. https://www.nature.com/articles/s41599-025-05481-9 (AI & Environment Resource Hub; record paper-356; collection snapshot 2026-09-15).
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Included in the original Scientific Paper collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
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- Krueger et al.
- Publisher
- Humanities and Social Science Communications
- Publication date
- 2025-07-18
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- day
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- Unknown
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- unknown
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- unknown
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- Last verified
- 2026-09-15T00:00:00.000Z
- Snapshot import
- 2026-09-06
- Legacy domain
- Cross-Cutting Sustainability
- Legacy subdomain
- The Need for Transdisciplinary Research in AI
- journal
- Humanities and Social Science Communications
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Selected fields checked: · 2026-09-06. Editorial review confirmed this record against its current source page/file; limited or generic machine-readable metadata prevented automatic corroboration. Verification source ↗
Source sheet: Scientific Paper · Row 360 · Original ID: paper-356.
A paper listing is not a quality assessment. Peer review and findings require source-level confirmation. Source link reachable · checked 2026-09-15. Source identity and required metadata verified. The import date is not the original date added.
Suggest a correction for this record →Related through shared environmental topics
Ordered by the number of shared provisional topic labels. This indicates a browsing connection, not agreement between sources.
Shared topics: Cross-cutting sustainability; Governance and society; Research tools and geospatial methods; Biodiversity and ecosystems
Shared topics: Cross-cutting sustainability; Governance and society; Research tools and geospatial methods; Biodiversity and ecosystems
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EarthMap
Earth Map is an innovative, free and open-source tool developed by the Food and Agriculture Organization of the United Nations (FAO) in the framework of the FAO - Google partnership. It was created to support countries, research institutes, farmers and members of the general public with internet access to monitor their land in an easy, integrated and multi-temporal manner. It allows everyone to visualize, process and analyze satellite imagery and global datasets on climate, vegetation, fires, biodiversity, geo-social and other topics. Users need no prior knowledge of remote sensing or Geographical Information Systems (GIS).
Shared topics: Cross-cutting sustainability; Governance and society; Research tools and geospatial methods
Podcast · 2026-08-05
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Shared topics: Cross-cutting sustainability; Governance and society; Biodiversity and ecosystems
Scientific Paper · 2025-10-06
A Critical Re-framing of the AI(s) and Sustainability Regulation Debate through the Lens of Law and Technology
The abstract argues that policy debates about “sustainable AI” are stuck in an overly simplistic binary, AI as both an environmental threat and a tool for ecological transition, which leads to shallow regulatory approaches focused mostly on energy reporting. Drawing on law-and-technology scholarship, the authors show how technological determinism, exceptionalism, and regulatory solutionism distort the debate, and they propose reframing regulation around the socio-economic drivers and power dynamics of AI development rather than the technology itself.