Lauren Kahn
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 5
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- International Relations and Foreign Policy 2
- Intelligence, Security, War Strategy 1
- Co-authors
- Michael C. Horowitz (10 shared papers)Jacquelyn Schneider (2 shared papers)Julia R. MacDonald (1 shared paper)Markus Anderljung (2 shared papers)Allan Dafoe (2 shared papers)Lucas Walsh (1 shared paper)Robert Patrick (1 shared paper)Baobao Zhang (1 shared paper)
- Journals
- PLoS ONE (2 papers)The Washington Quarterly (1 paper)International Studies Quarterly (1 paper)Journal of Conflict Resolution (1 paper)Journal of Artificial Intelligence Research (1 paper)
- Partner nations
- United StatesIrelandCanada
In The Last Decade
Lauren Kahn
11 papers receiving 203 citations
Peers
Comparison fields: 5 of 58
- Health Informatics 36
- Safety Research 72
- Information Systems and Management 20
- Computer Science Applications 11
- Artificial Intelligence 64
Countries citing papers authored by Lauren Kahn
This map shows the geographic impact of Lauren Kahn'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 Lauren Kahn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lauren Kahn more than expected).
Fields of papers citing papers by Lauren Kahn
This network shows the impact of papers produced by Lauren Kahn. 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 Lauren Kahn. The network helps show where Lauren Kahn may publish in the future.
Co-authors
The 8 scholars most cited alongside Lauren Kahn, 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 | 2023 | 59 | |
| 2 | 2021 | 58 | |
| 3 | 2021 | 46 | |
| 4 | 2024 | 16 | |
| 5 | 2020 | 14 | |
| 6 | 2021 | 6 | |
| 7 | 2022 | 4 | |
| 8 | 2022 | 4 | |
| 9 | 2022 | 3 | |
| 10 | Developing skills for life and work: accelerating social and emotional learning across South Australia | 2012 | 3 |
| 11 | 2021 | 1 | |
| 12 | 2021 | 0 |
About Lauren Kahn
Lauren Kahn is a scholar working on Safety Research, Political Science and International Relations, Health Informatics, Sociology and Political Science and Artificial Intelligence, having authored 12 papers that have together received 214 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (5 papers), Artificial Intelligence in Healthcare and Education (3 papers), Adversarial Robustness in Machine Learning (2 papers), International Relations and Foreign Policy (2 papers), Defense, Military, and Policy Studies (2 papers), Youth Education and Societal Dynamics (1 paper), Human-Automation Interaction and Safety (1 paper) and Intelligence, Security, War Strategy (1 paper). The work is most often cited by research in Health Informatics (36 citations), Safety Research (72 citations), Information Systems and Management (20 citations), Computer Science Applications (11 citations) and Artificial Intelligence (64 citations). Lauren Kahn has collaborated with scholars based in United States, Ireland and Canada. Frequent co-authors include Michael C. Horowitz, Jacquelyn Schneider, Julia R. MacDonald, Markus Anderljung, Allan Dafoe, Lucas Walsh, Robert Patrick and Baobao Zhang. Their work appears in journals such as PLoS ONE, The Washington Quarterly, International Studies Quarterly, Journal of Conflict Resolution and Journal of Artificial Intelligence Research.
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.