Yapay Zekâ Yönetişiminde Temsil Krizi ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme

Zeynep İlhan

doi:10.38057/bifd.1968998

TR EN

Yapay Zekâ Yönetişiminde Temsil Krizi ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme

Abstract

Bu çalışmanın amacı, yapay zekâ (YZ), toplumsal cinsiyet, algoritmik ön yargı, temsil ve yönetişim kesişimindeki literatürün entelektüel yapısını, gelişim dinamiklerini ve güncel eğilimlerini bibliyometrik olarak incelemektir. Web of Science Core Collection veri tabanından elde edilen kayıtlar, belge türü ve dil sınırlamaları ile manuel içerik incelemesinin ardından değerlendirilmiş ve 147 yayın analiz edilmiştir. Veriler, Python 3.12.13 programlama dili ve ilgili analiz kütüphaneleri kullanılarak tanımlayıcı analiz, performans analizi, sosyal ağ analizi, kavramsal yapı analizi ve tematik evrim analizi aşamalarında incelenmiştir. Bulgular, yayın sayısının özellikle 2023 sonrasında arttığını ve 2025 yılında 41’e ulaştığını göstermektedir. İspanya yayın sayısı bakımından ilk sırada yer alırken ülkeler arası iş birliği ağında ABD ve Çin bağlantı düzeyleriyle öne çıkmaktadır. Kavramsal yönelimler, keşfedici değerlendirme kapsamında üç geniş tematik topluluk altında betimsel olarak düzenlenmiştir. Stratejik diyagramdaki göreli konumlar; toplumsal cinsiyet stereotipleri, hakkaniyet ve ayrımcılık temalarının temel ve dönüşümsel; eğitim, üretken yapay zekâ ve kapsayıcılık temalarının motor tema niteliği kazanmakta olan; kurumsal yönetişim ve toplumsal cinsiyet çeşitliliğinin ise niş bir araştırma yönelimi sergilediğini düşündürmektedir. Liderlik temasının yalnızca iki belgede bulunması, kadın liderlik ile yapay zekâ yönetişimi arasındaki ilişkinin literatürde sınırlı görünürlüğe sahip olduğuna işaret etmektedir. Bibliyometrik bulgular, doğrulayıcı kanıt niteliği taşımayan ve kavramsal modelin geliştirilmesine yön veren literatür eğilimleri olarak değerlendirilmiştir. Önerilen modelde kadın liderlik, temsil krizine yönelik çok boyutlu çözüm çerçevesinin unsurlarından biri olarak ele alınmış; etik duyarlılık, çeşitlilik yönetimi, hesap verebilirlik ve kapsayıcı karar alma aracılığıyla kapsayıcı yapay zekâ yönetişimini destekleyebilecek bir yönetişim kapasitesi olarak konumlandırılmıştır. Bu doğrultuda araştırma ve uygulamaya yönelik öneriler sunulmuştur.

Keywords

Yapay Zekâ Yönetişimi, Kadın Liderlik, Temsil Krizi, Algoritmik Ön Yargı, Bibliyometrik Analiz

The Representation Crisis and Women's Leadership in Artificial Intelligence Governance: A Conceptual Assessment Drawing on Bibliometric Findings

Abstract

The aim of this study is to bibliometrically examine the intellectual structure, development dynamics, and current trends of the literature at the intersection of artificial intelligence (AI), gender, algorithmic bias, representation, and governance. Records retrieved from the Web of Science Core Collection were evaluated after applying document type and language restrictions and conducting a manual content review, resulting in a final dataset of 147 publications. The data were analyzed using Python 3.12.13 and related analytical libraries through descriptive analysis, performance analysis, social network analysis, conceptual structure analysis, and thematic evolution analysis. The findings show that the number of publications increased particularly after 2023 and reached 41 in 2025. Spain ranked first in publication output, while the United States and China stood out in the international collaboration network in terms of their connectivity. As part of the exploratory assessment, the conceptual orientations were descriptively organized into three broad thematic communities. Their relative positions in the strategic diagram suggest that gender stereotypes, fairness, and discrimination represent basic and transversal themes; education, generative AI, and inclusion constitute a thematic orientation moving toward motor-theme status; and corporate governance and gender diversity display a niche research orientation. The presence of the leadership theme in only two publications indicates that the relationship between women’s leadership and AI governance has limited visibility in the literature. The bibliometric findings were interpreted as literature trends that inform the development of the conceptual model without constituting confirmatory evidence. In the proposed model, women’s leadership is considered one component of a multidimensional framework for addressing the representation crisis and is positioned as a governance capacity that may support inclusive AI governance through ethical sensitivity, diversity management, accountability, and inclusive decision-making. Accordingly, recommendations for future research and practice are presented.

Keywords

Artificial Intelligence Governance, Women’s Leadership, Representation Crisis, Algorithmic Bias, Bibliometric Analysis

References

Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
Brookes, B. C. (1985). "Sources of information on specific subjects" by S.C. Bradford. Journal of Information Science, 10(4), 173–175. https://doi.org/10.1177/016555158501000406
Buss, M., Andler, S., & Tiberius, V. (2025). Female leadership: An integrative review and research framework. The Leadership Quarterly, 36(1), 101858. https://doi.org/10.1016/j.leaqua.2024.101858
Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic research and technological innovation. Scientometrics, 22(1), 155–205. https://doi.org/10.1007/bf02019280
Cath, C. (2018). Governing artificial intelligence: Ethical, legal and technical opportunities and challenges. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2133). https://doi.org/10.1098/rsta.2018.0080
Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application in the fuzzy sets theory field. Journal of Informetrics, 5(1), 146–166. https://doi.org/10.1016/j.joi.2010.10.002
Collett, C., & Dillon, S. (2019). AI and gender: Four proposals for future research. Cambridge Centre for the Future of Intelligence. https://doi.org/10.17863/CAM.41459
Council of Europe Commissioner for Human Rights. (2019). Unboxing artificial intelligence: 10 steps to protect human rights. Council of Europe. https://rm.coe.int/unboxing-artificial-intelligence-10-steps-to-protect-human-rights-reco/1680946e64
D’Ignazio, C., & Klein, L. F. (2020). Data feminism. MIT Press. https://doi.org/10.7551/mitpress/11805.001.0001 Dahlerup, D. (2014). The critical mass theory in public and scholarly debates. In R. Campbell & S. Childs (Eds.), Deeds and words: Gendering politics after Joni Lovenduski (pp. 143–164). ECPR Press
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070

Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact? Scientometrics, 105(3), 1809–1831. https://doi.org/10.1007/s11192-015-1645-z
Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin's Press.
European Parliament, & Council of the European Union. (2024). Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence. Official Journal of the European Union, L, 2024/1689. https://eur-lex.europa.eu/eli/reg/2024/1689/oj
Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.8cd550d1
Glänzel, W. (2001). National characteristics in international scientific co-authorship relations. Scientometrics, 51(1), 69–115. https://doi.org/10.1023/A:1010512628145
Gross, N. (2023). What ChatGPT tells us about gender: A cautionary tale about performativity and gender biases in AI. Social Sciences, 12(8), Article 435. https://doi.org/10.3390/socsci12080435
Gupta, M., Parra, C. M., & Dennehy, D. (2022). Questioning racial and gender bias in AI-based recommendations: Do espoused national cultural values matter? Information Systems Frontiers, 24, 1465–1481. https://doi.org/10.1007/s10796-021-10156-2
Hall, P., & Ellis, D. (2023). A systematic review of socio-technical gender bias in AI algorithms. Online Information Review, 47(7), 1264–1279. https://doi.org/10.1108/OIR-08-2021-0452
Kuhn, T. S. (1962). The structure of scientific revolutions. University of Chicago Press.
Larson, G., & DeChurch, L. A. (2020). Leading teams in the digital age: Four perspectives on technology and what they mean for leading teams. The Leadership Quarterly, 31(1), 101377. https://doi.org/10.1016/j.leaqua.2019.101377
McCain, K. W. (1990). Mapping authors in intellectual space: A technical overview. Journal of the American Society for Information Science, 41(6), 433–443. https://doi.org/10.1002/(SICI)1097-4571(199009)41:6<433::AID-ASI11>3.0.CO;2-Q
Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York University Press.
O’Connor, S., & Liu, H. (2024). Gender bias perpetuation and mitigation in AI technologies: Challenges and opportunities. AI & Society, 39, 2045–2057. https://doi.org/10.1007/s00146-023-01675-4
OECD. (2024). OECD digital economy outlook 2024 (Vol. 2): Strengthening connectivity, innovation and trust. OECD Publishing. https://doi.org/10.1787/3adf705b-en
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, Article n71. https://doi.org/10.1136/bmj.n71
Perianes-Rodriguez, A., Waltman, L., & van Eck, N. J. (2016). Constructing bibliometric networks: A comparison between full and fractional counting. Journal of Informetrics, 10(4), 1178–1195. https://doi.org/10.1016/j.joi.2016.10.006
Peters, H. P. F., & van Raan, A. F. J. (1991). Structuring scientific activities by co-author analysis: An exercise on a university faculty level. Scientometrics, 20(1), 235–255. https://doi.org/10.1007/BF02018157
Prates, M. O. R., Avelar, P. H. C., & Lamb, L. C. (2020). Assessing gender bias in machine translation: A case study with Google Translate. Neural Computing and Applications, 32, 6363–6381. https://doi.org/10.1007/s00521-019-04144-6
Raman, R., Mandal, S., Das, P., Kaur, T., Sanjanasri, J. P., & Nedungadi, P. (2024). Exploring university students’ adoption of ChatGPT using the diffusion of innovation theory and sentiment analysis with gender dimension. Human Behavior and Emerging Technologies, 2024, Article 3085910. https://doi.org/10.1155/2024/3085910
Shrestha, S., & Das, S. (2022). Exploring gender biases in ML and AI academic research through systematic literature review. Frontiers in Artificial Intelligence, 5, Article 976838. https://doi.org/10.3389/frai.2022.976838
Slimi, Z., & Villarejo-Carballido, B. (2023). Navigating the ethical challenges of artificial intelligence in higher education: An analysis of seven global AI ethics policies. TEM Journal, 12(2), 590–602. https://doi.org/10.18421/TEM122-02
Sun, L., Wei, M., Sun, Y., Suh, Y. J., Shen, L., & Yang, S. (2024). Smiling women pitching down: Auditing representational and presentational gender biases in image-generative AI. Journal of Computer-Mediated Communication, 29(1), Article zmad045. https://doi.org/10.1093/jcmc/zmad045
T.C. Aile ve Sosyal Hizmetler Bakanlığı. (2024). Kadının Güçlenmesi Strateji Belgesi ve Eylem Planı (2024–2028). https://www.aile.gov.tr/media/158302/kadinin-guclenmesi-strateji-belgesi-ve-eylem-plani-2024-2028.pdf
T.C. Cumhurbaşkanlığı Dijital Dönüşüm Ofisi & T.C. Sanayi ve Teknoloji Bakanlığı. (2021). Ulusal yapay zekâ stratejisi 2021–2025. https://cbddo.gov.tr/uyzs
van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
Vlasceanu, M., & Amodio, D. M. (2022). Propagation of societal gender inequality by internet search algorithms. Proceedings of the National Academy of Sciences of the United States of America, 119(29), Article e2204529119. https://doi.org/10.1073/pnas.2204529119
White, H. D., & McCain, K. W. (1998). Visualizing a discipline: An author co-citation analysis of information science, 1972–1995. Journal of the American Society for Information Science, 49(4), 327–355. https://doi.org/10.1002/(SICI)1097-4571(19980401)49:4<327::AID-ASI4>3.0.CO;2-4
Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector—applications and challenges. International Journal of Public Administration, 42(7), 596–615. https://doi.org/10.1080/01900692.2018.1498103
Zhao, D., & Strotmann, A. (2008). Information science during the first decade of the web: An enriched author cocitation analysis. Journal of the American Society for Information Science and Technology, 59(6), 916–937. https://doi.org/10.1002/asi.20799
Zuiderwijk, A., Chen, Y. C., & Salem, F. (2021). Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda. Government Information Quarterly, 38(3), 101577. https://doi.org/10.1016/j.giq.2021.101577
Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472. https://doi.org/10.1177/1094428114562629

Details

Primary Language

Turkish

Subjects

Leadership

Journal Section

Research Article

Authors

Zeynep İlhan ^*
0000-0001-6978-5756
Türkiye

Publication Date

October 29, 2026

Submission Date

June 11, 2026

Acceptance Date

September 24, 2026

Published in Issue

Year 2026 Volume: 9 Number: 2

DOI

https://doi.org/10.38057/bifd.1968998

IZ

https://izlik.org/JA59HL69UN

APA

İlhan, Z. (2026). Yapay Zekâ Yönetişiminde Temsil Krizi ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme. Bucak İşletme Fakültesi Dergisi, 9(2), 177-196. https://doi.org/10.38057/bifd.1968998

AMA

1.İlhan Z. Yapay Zekâ Yönetişiminde Temsil Krizi ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme. Bucak İşletme Fakültesi Dergisi. 2026;9(2):177-196. doi:10.38057/bifd.1968998

Chicago

İlhan, Zeynep. 2026. “Yapay Zekâ Yönetişiminde Temsil Krizi Ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme”. Bucak İşletme Fakültesi Dergisi 9 (2): 177-96. https://doi.org/10.38057/bifd.1968998.

EndNote

İlhan Z (October 1, 2026) Yapay Zekâ Yönetişiminde Temsil Krizi ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme. Bucak İşletme Fakültesi Dergisi 9 2 177–196.

IEEE

[1]Z. İlhan, “Yapay Zekâ Yönetişiminde Temsil Krizi ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme”, Bucak İşletme Fakültesi Dergisi, vol. 9, no. 2, pp. 177–196, Oct. 2026, doi: 10.38057/bifd.1968998.

ISNAD

İlhan, Zeynep. “Yapay Zekâ Yönetişiminde Temsil Krizi Ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme”. Bucak İşletme Fakültesi Dergisi 9/2 (October 1, 2026): 177-196. https://doi.org/10.38057/bifd.1968998.

JAMA

1.İlhan Z. Yapay Zekâ Yönetişiminde Temsil Krizi ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme. Bucak İşletme Fakültesi Dergisi. 2026;9:177–196.

MLA

İlhan, Zeynep. “Yapay Zekâ Yönetişiminde Temsil Krizi Ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme”. Bucak İşletme Fakültesi Dergisi, vol. 9, no. 2, Oct. 2026, pp. 177-96, doi:10.38057/bifd.1968998.

Vancouver

1.Zeynep İlhan. Yapay Zekâ Yönetişiminde Temsil Krizi ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme. Bucak İşletme Fakültesi Dergisi. 2026 Oct. 1;9(2):177-96. doi:10.38057/bifd.1968998

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Yapay Zekâ Yönetişiminde Temsil Krizi ve Kadın Liderlik: Bibliyometrik Bulgular Işığında Kavramsal Bir Değerlendirme

Abstract

Keywords

The Representation Crisis and Women's Leadership in Artificial Intelligence Governance: A Conceptual Assessment Drawing on Bibliometric Findings

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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