Emanuelle Burton
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Safety Research top 5%
- Ethics and Social Impacts of AI
Papers in
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- Ethics and Social Impacts of AI 12
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- Neuroethics, Human Enhancement, Biomedical Innovations 3
- Psychology of Moral and Emotional Judgment 2
- Co-authors
- Judy Goldsmith (10 shared papers)Nicholas Mattei (6 shared papers)Benjamin Kuipers (1 shared paper)Sven Koenig (1 shared paper)Toby Walsh (1 shared paper)Soohyun Nam Liao (1 shared paper)Michael D. Toland (1 shared paper)David Dueber (1 shared paper)
- Journals
- Communications of the ACM (1 paper)AI Magazine (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)National Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesAustralia
In The Last Decade
Emanuelle Burton
12 papers receiving 228 citations
Peers
Comparison fields: 5 of 67
- Health Informatics 29
- Safety Research 116
- Computer Science Applications 41
- Information Systems and Management 38
- Business and International Management 5
Countries citing papers authored by Emanuelle Burton
This map shows the geographic impact of Emanuelle Burton'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 Emanuelle Burton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emanuelle Burton more than expected).
Fields of papers citing papers by Emanuelle Burton
This network shows the impact of papers produced by Emanuelle Burton. 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 Emanuelle Burton. The network helps show where Emanuelle Burton may publish in the future.
Co-authors
The 14 scholars most cited alongside Emanuelle Burton, 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 | 2017 | 95 | |
| 2 | 2018 | 75 | |
| 3 | 2017 | 29 | |
| 4 | 2021 | 15 | |
| 5 | Teaching AI Ethics Using Science Fiction | 2015 | 14 |
| 6 | 2020 | 6 | |
| 7 | 2019 | 3 | |
| 8 | Using "The Machine Stops" for Teaching Ethics in Artificial Intelligence and Computer Science | 2016 | 3 |
| 9 | 2022 | 1 | |
| 10 | 2022 | 1 | |
| 11 | 2022 | 1 | |
| 12 | 2022 | 1 | |
| 13 | 2024 | 0 |
About Emanuelle Burton
Emanuelle Burton is a scholar working on Safety Research, Cognitive Neuroscience, Artificial Intelligence, Computer Science Applications and Information Systems, having authored 13 papers that have together received 244 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (12 papers), Teaching and Learning Programming (4 papers), Neuroethics, Human Enhancement, Biomedical Innovations (3 papers), Ethics in Business and Education (3 papers), Digital Education and Society (2 papers), Psychology of Moral and Emotional Judgment (2 papers), Adversarial Robustness in Machine Learning (2 papers) and Law, AI, and Intellectual Property (2 papers). The work is most often cited by research in Health Informatics (29 citations), Safety Research (116 citations), Computer Science Applications (41 citations), Information Systems and Management (38 citations) and Business and International Management (5 citations). Emanuelle Burton has collaborated with scholars based in United States and Australia. Frequent co-authors include Judy Goldsmith, Nicholas Mattei, Benjamin Kuipers, Sven Koenig, Toby Walsh, Soohyun Nam Liao, Michael D. Toland, David Dueber, Rebecca Bates and Michael Goldweber. Their work appears in journals such as Communications of the ACM, AI Magazine, Proceedings of the AAAI Conference on Artificial Intelligence and National Conference on Artificial Intelligence.
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.