Giada Pistilli
Impact in
-
- Artificial Intelligence in Healthcare and Education
-
- Archaeological Research and Protection
Papers in
-
- Ethics and Social Impacts of AI 5
- Co-authors
- Yacine Jernite (2 shared papers)Margaret A. Mitchell (2 shared papers)Carlos Muñoz Ferrandis (1 shared paper)Alex Shenfield (1 shared paper)Michael J. Muller (2 shared papers)Sasha Luccioni (1 shared paper)Daniele Quercia (2 shared papers)Jessica Vitak (2 shared papers)
- Journals
- Internet Archaeology (1 paper)European Radiology (1 paper)Ethics and Information Technology (1 paper)arXiv (Cornell University) (2 papers)Proceedings of the AAAI/ACM Conference on AI Ethics and Society (2 papers)
- Partner nations
- FranceNetherlandsUnited States
In The Last Decade
Giada Pistilli
7 papers receiving 46 citations
Peers
Comparison fields: 5 of 28
- Health Informatics 8
- Space and Planetary Science 6
- Safety Research 13
- Computer Science Applications 5
- Geology 4
Countries citing papers authored by Giada Pistilli
This map shows the geographic impact of Giada Pistilli'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 Giada Pistilli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giada Pistilli more than expected).
Fields of papers citing papers by Giada Pistilli
This network shows the impact of papers produced by Giada Pistilli. 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 Giada Pistilli. The network helps show where Giada Pistilli may publish in the future.
Co-authors
The 21 scholars most cited alongside Giada Pistilli, 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 | 14 | |
| 2 | 2024 | 12 | |
| 3 | 2024 | 9 | |
| 4 | Ce qui se cache derrière l'Intelligence Artificielle Générale (Artificial General Intelligence, AGI) : préoccupations éthiques liées aux grands modèles de langage (Large Language Models, LLMs) | 2022 | 5 |
| 5 | 2024 | 3 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 0 | |
| 10 | 2026 | 0 |
About Giada Pistilli
Giada Pistilli is a scholar working on Safety Research, Space and Planetary Science, Health Informatics, Management of Technology and Innovation and General Economics, Econometrics and Finance, having authored 10 papers that have together received 46 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (5 papers), Neuroethics, Human Enhancement, Biomedical Innovations (1 paper), Mental Health via Writing (1 paper), Blockchain Technology Applications and Security (1 paper), Chronic Disease Management Strategies (1 paper), Legal and Policy Issues (1 paper), Explainable Artificial Intelligence (XAI) (1 paper) and Image Processing and 3D Reconstruction (1 paper). The work is most often cited by research in Health Informatics (8 citations), Space and Planetary Science (6 citations), Safety Research (13 citations), Computer Science Applications (5 citations) and Geology (4 citations). Giada Pistilli has collaborated with scholars based in France, Netherlands and United States. Frequent co-authors include Yacine Jernite, Margaret A. Mitchell, Carlos Muñoz Ferrandis, Alex Shenfield, Michael J. Muller, Sasha Luccioni, Daniele Quercia, Jessica Vitak, Lauren G Wilcox and Jess Holbrook. Their work appears in journals such as Internet Archaeology, European Radiology, Ethics and Information Technology, arXiv (Cornell University) and Proceedings of the AAAI/ACM Conference on AI Ethics and Society.
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.