The DOI matches its Crossref record.
Gender Diversity in AI Research
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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
“There are significant gaps in gender, race, and ethnicity [71, 72]”
From Use of artificial intelligence in critical care: opportunities and obstacles (2024) · cites this paper as [71]
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Speeding up to keep up: exploring the use of AI in the research process
Chubb, J., Cowling, P., & Reed, D. (2022) · AI & SOCIETY · doi:10.1007/s00146-021-01259-0 · Cited by 218
Use of artificial intelligence in critical care: opportunities and obstacles
Pinsky, M. R., Bedoya, A., Bihorac, A., Celi, L., Churpek, M., Economou-Zavlanos, N. J., Elbers, P., Saria, S., Liu, V., Lyons, P. G., et al. (2024) · Critical Care · doi:10.1186/s13054-024-04860-z · Cited by 160
“There are significant gaps in gender, race, and ethnicity [71, 72] Lack of diverse perspectives can negatively impact resulting products, as has plagued the AI field for years [73, 74].”
Background
Metadata
- Authors
- Stathoulopoulos, K., & Mateos-Garcia, J. C.
- Affiliations
- Nesta (GB)
- Corresponding author
- Stathoulopoulos, Konstantinos
- Venue
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Published
- 2019
- ISSN
- 1556-5068 (ISSN-L)
- OpenAlex
- W2980155061
- Cited by
- 47
- References
- 0
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 11 · 2023: 7 · 2022: 3 · 2021: 6 · 2020: 8
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- SSRN Electronic Journal (publishedVersion)
- Topics
- Social Sciences › Library and Information Sciences › scientometrics and bibliometrics research
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- gender diversity, artificial intelligence research, citation impact, research institutions, research geography, computer ethics, machine learning, diversity and inclusion, women in technology
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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