Human + Machine : Reimagining Work in the Age of AI

217 indexed citations
published 2021

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doi.org/w67668964 →

Countries where authors are citing Human + Machine : Reimagining Work in the Age of AI

Specialization
Citations

This map shows the geographic impact of Human + Machine : Reimagining Work in the Age of AI. 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 Human + Machine : Reimagining Work in the Age of AI with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Human + Machine : Reimagining Work in the Age of AI more than expected).

Fields of papers citing Human + Machine : Reimagining Work in the Age of AI

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Human + Machine : Reimagining Work in the Age of AI. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Human + Machine : Reimagining Work in the Age of AI.

About Human + Machine : Reimagining Work in the Age of AI

This paper, published in 2021, received 217 indexed citations . Written by Paul R. Daugherty. It is primarily cited by scholars working on Sociology and Political Science (58 citations), Artificial Intelligence (51 citations) and Safety Research (40 citations).

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.

This paper is also available at doi.org/w67668964.

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