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Unveiling Ethical AI: An In-Depth Bibliometric and Visual Exploration
Qihui Yuan
Unveiling Ethical AI: An In-Depth Bibliometric and Visual Exploration
This study meticulously delineates the research progression, focal points, developmental path and emergent evolutionary trajectories of computational intelligence within the domain of ethics. A comprehensive quantitative report, embodying bibliometric principles, was prepared using the Web of Science Core Collection database. The methodology involved conducting an extensive search for original articles and reviews related to “ethical artificial intelligence” Relevant data from these sources were extracted and integrated into CiteSpace and Vosviewer for bibliometric and knowledge mapping analysis. The R package was used as an auxiliary tool in this process, facilitating the creation of co-occurrence networks and providing necessary information on authors, countries/regions, institutions, documents, references and keywords. This investigation includes an aggregate of 327 articles. The research on ethical AI originated in 2001 and experienced a marked escalation from 2015 onwards. Luciano Floridi has made the most significant contribution with regard to the volume of scholarly outputs. The USA emerged as the region with the most prolific output and the University of Oxford stands as the institution contributing the greatest amount of articles. The periodical registering the most prolific scholarly contributions is “Science and Engineering Ethics”. Keyword analysis reveals that, in addition to topic-specific keywords such as “artificial intelligence”, “big data” and “artificial neural network”, there are also keywords that align with ethical theory research, such as “ethic issue” and “medical ethics”, as well as those congruent with technical application research, including “technology”, “model” and “design”. These keywords substantially shape the principal directions of future research in this domain. The study of ethics in the field of AI is undergoing significant growth and holds immense potential. It is imperative to foster international and interdisciplinary collaboration among nations and institutions in order to advance further. As AI theories and technologies continue to mature, research addressing the ethical dimensions of AI, its technical applications, or the integration of both, will undoubtedly become key areas of sustained development and innovation in the future.
Bibliometric analysis,
Artificial intelligence,
Ethical issue,
Citespace,
VOSviewer
Unveiling Ethical AI: An In-Depth Bibliometric and Visual Exploration
This study meticulously delineates the research progression, focal points, developmental path and emergent evolutionary trajectories of computational intelligence within the domain of ethics. A comprehensive quantitative report, embodying bibliometric principles, was prepared using the Web of Science Core Collection database. The methodology involved conducting an extensive search for original articles and reviews related to “ethical artificial intelligence” Relevant data from these sources were extracted and integrated into CiteSpace and Vosviewer for bibliometric and knowledge mapping analysis. The R package was used as an auxiliary tool in this process, facilitating the creation of co-occurrence networks and providing necessary information on authors, countries/regions, institutions, documents, references and keywords. This investigation includes an aggregate of 327 articles. The research on ethical AI originated in 2001 and experienced a marked escalation from 2015 onwards. Luciano Floridi has made the most significant contribution with regard to the volume of scholarly outputs. The USA emerged as the region with the most prolific output and the University of Oxford stands as the institution contributing the greatest amount of articles. The periodical registering the most prolific scholarly contributions is “Science and Engineering Ethics”. Keyword analysis reveals that, in addition to topic-specific keywords such as “artificial intelligence”, “big data” and “artificial neural network”, there are also keywords that align with ethical theory research, such as “ethic issue” and “medical ethics”, as well as those congruent with technical application research, including “technology”, “model” and “design”. These keywords substantially shape the principal directions of future research in this domain. The study of ethics in the field of AI is undergoing significant growth and holds immense potential. It is imperative to foster international and interdisciplinary collaboration among nations and institutions in order to advance further. As AI theories and technologies continue to mature, research addressing the ethical dimensions of AI, its technical applications, or the integration of both, will undoubtedly become key areas of sustained development and innovation in the future.
Bibliometric analysis,
Artificial intelligence,
Ethical issue,
Citespace,
VOSviewer