Artificial Intelligence and Law

572 papers and 6.8k indexed citations i.

About

The 572 papers published in Artificial Intelligence and Law in the last decades have received a total of 6.8k indexed citations. Papers published in Artificial Intelligence and Law usually cover Artificial Intelligence (395 papers), Political Science and International Relations (265 papers) and Law (98 papers) specifically the topics of Artificial Intelligence in Law (260 papers), Multi-Agent Systems and Negotiation (214 papers) and Logic, Reasoning, and Knowledge (129 papers). The most active scholars publishing in Artificial Intelligence and Law are Giovanni Sartor, Henry Prakken, Trevor Bench‐Capon, Bart Verheij, Munindar P. Singh, Jaap Hage, Frank Dignum, Kevin D. Ashley, Thomas F. Gordon and Marie‐Francine Moens.

In The Last Decade

Fields of papers published in Artificial Intelligence and Law

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Artificial Intelligence and Law. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Artificial Intelligence and Law.

Countries where authors publish in Artificial Intelligence and Law

Since Specialization
Citations

This map shows the geographic impact of research published in Artificial Intelligence and Law. 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 papers published in Artificial Intelligence and Law with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Artificial Intelligence and Law more than expected).

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.

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2025