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Mapping gender and geographic diversity in artificial intelligence research: Editor representation in leading computer science journals.
Busch, Felix; Keller, Sarah; Rueger, Christopher; Kader, Avan; Ziegeler, Katharina; Bressem, Keno K; Adams, Lisa C.
Afiliación
  • Busch F; Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
  • Keller S; Division of Operative Intensive Care Medicine, Department of Anesthesiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
  • Rueger C; Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
  • Kader A; Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
  • Ziegeler K; Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
  • Bressem KK; Department of Radiology, Klinikum rechts der Isar, Technische Universität München (TUM), Munich, Germany.
  • Adams LC; Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
Acta Radiol Open ; 12(10): 20584601231213740, 2023 Oct.
Article en En | MEDLINE | ID: mdl-38034076
ABSTRACT

Background:

The growing role of artificial intelligence (AI) in healthcare, particularly radiology, requires its unbiased and fair development and implementation, starting with the constitution of the scientific community.

Purpose:

To examine the gender and country distribution among academic editors in leading computer science and AI journals. Material and

Methods:

This cross-sectional study analyzed the gender and country distribution among editors-in-chief, senior, and associate editors in all 75 Q1 computer science and AI journals in the Clarivate Journal Citations Report and SCImago Journal Ranking 2022. Gender was determined using an open-source algorithm (Gender Guesser™), selecting the gender with the highest calibrated probability.

Result:

Among 4,948 editorial board members, women were underrepresented in all positions (editors-in-chief/senior editors/associate editors 14%/18%/17%). The proportion of women correlated positively with the SCImago Journal Rank indicator (ρ = 0.329; p = .004). The U.S., the U.K., and China comprised 50% of editors, while Australia, Finland, Estonia, Denmark, the Netherlands, the U.K., Switzerland, and Slovenia had the highest women editor representation per million women population.

Conclusion:

Our results highlight gender and geographic disparities on leading computer science and AI journal editorial boards, with women being underrepresented in all positions and a disproportional relationship between the Global North and South.
Palabras clave

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Acta Radiol Open Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Acta Radiol Open Año: 2023 Tipo del documento: Article