Libby Kinsey
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Safety Research top 1%
- Ethics and Social Impacts of AI
Papers in
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- Adversarial Robustness in Machine Learning 4
- Explainable Artificial Intelligence (XAI) 1
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- Ethics and Social Impacts of AI 4
- Co-authors
- Anat Elhalal (4 shared papers)Jessica Morley (4 shared papers)Luciano Floridi (4 shared papers)Marta Ziosi (1 shared paper)Michael Firman (1 shared paper)Kate E. Jones (1 shared paper)Kate E. Barlow (1 shared paper)Rory Gibb (1 shared paper)
- Journals
- PLoS Computational Biology (1 paper)Science and Engineering Ethics (1 paper)AI & Society (1 paper)SSRN Electronic Journal (2 papers)
- Partner nations
- United KingdomItalyUnited States
In The Last Decade
Libby Kinsey
5 papers receiving 711 citations
Libby Kinsey's Hit Papers
Peers
Comparison fields: 5 of 106
- Health Informatics 171
- Safety Research 386
- Developmental Biology 86
- Ecological Modeling 34
- Cognitive Neuroscience 120
Countries citing papers authored by Libby Kinsey
This map shows the geographic impact of Libby Kinsey's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Libby Kinsey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Libby Kinsey more than expected).
Fields of papers citing papers by Libby Kinsey
This network shows the impact of papers produced by Libby Kinsey. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Libby Kinsey. The network helps show where Libby Kinsey may publish in the future.
Co-authors
The 17 scholars most cited alongside Libby Kinsey, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices Hit paper breakdown → | 2019 | 422 |
| 2 | 2018 | 149 | |
| 3 | 2021 | 107 | |
| 4 | 2019 | 44 | |
| 5 | 2021 | 18 |
About Libby Kinsey
Libby Kinsey is a scholar working on Artificial Intelligence, Safety Research, Cognitive Neuroscience, Ecology, Evolution, Behavior and Systematics and Developmental Biology, having authored 5 papers that have together received 740 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Ethics and Social Impacts of AI (4 papers), Neuroethics, Human Enhancement, Biomedical Innovations (2 papers), Artificial Intelligence in Healthcare and Education (1 paper), Marine animal studies overview (1 paper), Bat Biology and Ecology Studies (1 paper), Explainable Artificial Intelligence (XAI) (1 paper) and Animal Vocal Communication and Behavior (1 paper). The work is most often cited by research in Health Informatics (171 citations), Safety Research (386 citations), Developmental Biology (86 citations), Ecological Modeling (34 citations) and Cognitive Neuroscience (120 citations). Libby Kinsey has collaborated with scholars based in United Kingdom, Italy and United States. Frequent co-authors include Anat Elhalal, Jessica Morley, Luciano Floridi, Marta Ziosi, Michael Firman, Kate E. Jones, Kate E. Barlow, Rory Gibb, Ella Browning and Stuart E. Newson. Their work appears in journals such as PLoS Computational Biology, Science and Engineering Ethics, AI & Society and SSRN Electronic Journal.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.