The DOI matches its Crossref record.
International Efforts Aimed at Promoting AI Transparency and/or Accountability
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“International efforts to promote transparency and accountability increasingly shape procurement rules, audit expectations, and regulatory templates across sectors, including health and social care (García, Rivera & Iserte 2025).”
From Toward Trustworthy Artificial Intelligence in Law and Public Administration: Transparency, Accountability and Decision Support (2026) · cites this paper as García, Rivera & Iserte 2025
In the citing paper
“The references supplied by the user clearly foreground transparency, auditing, and international accountability norms as a mature research frontier rather than a supplementary concern (García, Rivera & Iserte 2025; Luna 2025).”
From Toward Trustworthy Artificial Intelligence in Law and Public Administration: Transparency, Accountability and Decision Support (2026) · cites this paper as García, Rivera & Iserte 2025
Citations
Cites
The publisher hasn’t deposited this paper’s reference list.
Research works printed but not linked: 1
- Cox, Robert W. Multilateralism and World Order. In: Cox, R. W.; Sassen, T. S. (eds.). Approaches to World Order. Cambridge: Cambridge University Press, 1996.
Cited by
Pasupuleti, M. K. (2026) · International Journal of Academic and Industrial Research Innovations(IJAIRI) · doi:10.62311/nesx/rp-1-28-30032026
Metadata
- Authors
- García, J. J. S., Rivera, N. E. G., & Iserte, J. M.
- Corresponding author
- Iserte, Jonathan Mendoza
- Venue
- Data Science, Machine Intelligence, and Law
- Publisher
- Springer Nature Switzerland
- Published
- 2025
- Pages
- 303-314
- ISSN
- 2730-5899 (ISSN-L)
- 2730-5902
- OpenAlex
- W7117976481
- Cited by
- 0
- References
- 0
- FWCI
- 0.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
- Locations
- Data science, machine intelligence, and law (publishedVersion)
- Topics
- Social Sciences › Law › Digitalization, Law, and Regulation
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Law › Artificial Intelligence in Law
- Keywords
- AI regulation, AI transparency, AI accountability, responsible AI governance, ethical AI, international cooperation on AI, Organization of American States, multi-stakeholder collaboration, trustworthy AI
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: International Efforts Aimed at Promoting AI Transparency and/or Accountability. https://app.cochat.ai/papers/10.1007/978-3-032-02762-7_20
- The paper
- García, J. J. S., Rivera, N. E. G., & Iserte, J. M. (2025). International Efforts Aimed at Promoting AI Transparency and/or Accountability. Data Science, Machine Intelligence, and Law. https://doi.org/10.1007/978-3-032-02762-7_20
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
