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Ethical and social dynamics in artificial intelligence and society: A bibliometric study

Larisa I. Tararina 1 2 * , Kristina L. Gorshkova 3 , Olga M. Kolomiets 4 , Elena N. Kareva 5 , Natalia A. Zaitseva 6 , Ekaterina G. Sokolova 7 , Oksana K. Korobkova 8
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1 Department of Foreign Languages, Moscow Institute of Physics and Technology, Moscow, Russia2 Department of Foreign Languages and Culture, Russian State Social University, Moscow, Russia3 Department of Automation and Information Technology, Almetyevsk State Technological University, Petroleum High School, Almetyevsk, Russia 4 Institute of Psychological and Social Work, Sechenov First Moscow State Medical University, Moscow, Russia. 5 Institute of Digital Biodesign and Modeling of Living Systems, Sechenov First Moscow State Medical University, Moscow, Russia6 Department of Hospitality, Tourism and Sports Industry, Plekhanov Russian University of Economics, Moscow, Russia 7 Institute of Foreign Languages, Peoples’ Friendship University of Russia (RUDN University), Moscow, Russia 8 Higher School of Economics, Pacific National University, Khabarovsk, Russia* Corresponding Author
Online Journal of Communication and Media Technologies, 16(2), April 2026, e202623 , https://doi.org/10.30935/ojcmt/18475
Published: 25 April 2026
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This article belongs to the special issue "Interdisciplinary Perspectives on Communication, Education, and Ethics in the Digital Age"

ABSTRACT

The study aims to provide a comprehensive bibliometric analysis of the academic literature on artificial intelligence (AI) ethics and social dynamics. Publications between 2020 and 2025 from Web of Science and Scopus databases were examined. The study aims to reveal expose the evolution, patterns, geographic distribution, and multidisciplinary structure of the subject of AI ethics. With an increase of over 100% in both databases, particularly between 2023 and 2024, the results show that the field has displayed fast expansion recently. Though there are variations in production and influence, the USA, the UK, and China dominate the field. Journal analysis shows that the journal “AI & Society” is the most influential publication in both databases. Keyword and thematic analyses show that while “AI”, “ethics” and “machine learning” remain central, new themes such as “ChatGPT” and “generative AI” are on the rise. Author collaboration networks reveal the multidisciplinary nature of the field and the existence of diverse research groups. Differences in coverage between databases suggest that Scopus better represents health sciences and current technological developments, while WoS better represents ethics. This study emphasizes that the research agenda in the field of AI ethics should be more inclusive and based on interdisciplinary collaboration and provides recommendations for future research directions.

CITATION (APA)

Tararina, L. I., Gorshkova, K. L., Kolomiets, O. M., Kareva, E. N., Zaitseva, N. A., Sokolova, E. G., & Korobkova, O. K. (2026). Ethical and social dynamics in artificial intelligence and society: A bibliometric study. Online Journal of Communication and Media Technologies, 16(2), e202623 . https://doi.org/10.30935/ojcmt/18475

REFERENCES

  1. Achuthan, K., Ramanathan, S., Srinivas, S., & Raman, R. (2024). Advancing cybersecurity and privacy with artificial intelligence: Current trends and future research directions. Frontiers in Big Data, 7, Article 1497535. https://doi.org/10.3389/fdata.2024.1497535
  2. Adhikari, C., Das, P. K., & Biswas, S. D. (2025). AI in higher education: An analysis of ChatGPT’s impact on scholarly communication. Educational Point, 2(2), Article e137. https://doi.org/10.71176/edup/17641
  3. Alvarez, J. M., Colmenarejo, A. B., Elobaid, A., Fabbrizzi, S., Fahimi, M., Ferrara, A., Ghodsi, S., Mougan, C., Papageorgiou, I., Reyero, P., Russo, M., Scott, K. M., State, L., Zhao, X., & Ruggieri, S. (2024). Policy advice and best practices on bias and fairness in AI. Ethics and Information Technology, 26, Article 31. https://doi.org/10.1007/s10676-024-09746-w
  4. Amann, J., Blasimme, A., Vayena, E., Frey, D., & Madai, V. I. (2020). Explainability for artificial intelligence in healthcare: A multidisciplinary perspective. BMC Medical Informatics and Decision Making, 20, Article 310. https://doi.org/10.1186/s12911-020-01332-6
  5. Andrieux, P., Johnson, R. D., Sarabadani, J., & Van Slyke, C. (2024). Ethical considerations of generative AI-enabled human resource management. Organizational Dynamics, 53(1), Article 101032. https://doi.org/10.1016/j.orgdyn.2024.101032
  6. 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
  7. Baig, K., Altaf, A., & Azam, M. (2024). Impact of AI on communication relationship and social dynamics: A qualitative approach. Bulletin of Business and Economics, 13(2), 282-289. https://doi.org/10.61506/01.00283
  8. Balasubramaniam, N., Kauppinen, M., Rannisto, A., Hiekkanen, K., & Kujala, S. (2023). Transparency and explainability of AI systems: From ethical guidelines to requirements. Information and Software Technology, 159, Article 107197. https://doi.org/10.1016/j.infsof.2023.107197
  9. Bhutani, V., Bahadur, P. S., Sansaniwal, S. K., & Bais, P. (2024). Youth studes in the AI era: Navigating uncharted territory. In Z. Zaremohzzabieh (Ed.), Exploring youth studies in the age of AI (pp. 407-428). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-3350-1.ch022
  10. Brin, S., & Page, L. (1998). The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems, 30(1-7), 107-117. https://doi.org/10.1016/S0169-7552(98)00110-X
  11. Callon, M., Courtial, J.-P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191-235. https://doi.org/10.1177/053901883022002003
  12. Canali, S., De Marchi, B., & Aliverti, A. (2023). Wearable technologies and stress: Toward an ethically grounded approach. International Journal of Environmental Research and Public Health, 20(18), Article 6737. https://doi.org/10.3390/ijerph20186737
  13. Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J. F., Brañas-Garza, P., Butera, L., Douglas, K. M., Everett, J. A. C., Gigerenzer, G., Greenhow, C., Hashimoto, D. A., Holt-Lunstad, J., Jetten, J., Johnson, S., Kunz, W. H., Longoni, C., … Viale, R. (2024). The impact of generative artificial intelligence on socioeconomic inequalities and policy making. PNAS Nexus, 3(6), Article pgae191. https://doi.org/10.1093/pnasnexus/pgae191
  14. Chen, Y., Clayton, E. W., Novak, L. L., Anders, S., & Malin, B. (2023). Human-centered design to address biases in artificial intelligence. Journal of Medical Internet Research, 25, Article e43251. https://doi.org/10.2196/43251
  15. Chuang, C. W., Chang, A., Chen, M., Selvamani, M. J. P., & Shia, B. C. (2022). A worldwide bibliometric analysis of publications on artificial intelligence and ethics in the past seven decades. Sustainability, 14(18), Article 11125. https://doi.org/10.3390/su141811125
  16. Ciobanu, A. C., & Meșniță, G. (2021). AI ethics in business–A bibliometric approach. Review of Economic and Business Studies, 14(2), 169-202. https://doi.org/10.47743/rebs-2021-2-0009
  17. 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 to the fuzzy sets theory field. Journal of Informetrics, 5(1), 146-166. https://doi.org/10.1016/j.joi.2010.10.002
  18. Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228-239. https://doi.org/10.1080/14703297.2023.2190148
  19. Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24-42. https://doi.org/10.1007/s11747-019-00696-0
  20. De la Vega Hernández, I. M., Urdaneta, A. S., & Carayannis, E. (2023). Global bibliometric mapping of the frontier of knowledge in the field of artificial intelligence for the period 1990-2019. Artificial Intelligence Review, 56(2), 1699-1729. https://doi.org/10.1007/s10462-022-10206-4
  21. Dehnert, M. (2023). AI as communicative other: Critical relationality in human-AI communication. In S. Nah (Ed.), Research handbook on artificial intelligence and communication (pp. 300-314). Edward Elgar Publishing. https://doi.org/10.4337/9781803920306.00028
  22. Dogru, T., Line, N., Hanks, L., Acikgoz, F., Abbott, J., Bakir, S., Berbekova, A., Bilgihan, A., Iskender, A., Kizildag, M., Lee, M., Lee, W., McGinley, S., Mody, M., Onder, I., Ozdemir, O., & Suess, C. (2024). The implications of generative artificial intelligence in academic research and higher education in tourism and hospitality. Tourism Economics, 30(5), 1083–1094. https://doi.org/10.1177/13548166231204065
  23. Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, Article 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
  24. Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, Article 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
  25. Eleftheriou, M., Ahmer, M., & Fredrick, D. (2025). Balancing ethics and support: Peer tutors’ experiences with AI tools in student writing. Contemporary Educational Technology, 17(3), Article ep587. https://doi.org/10.30935/cedtech/16554
  26. Evans, W. D., Bardus, M., & French, J. (2024). A vision of the future: Harnessing artificial intelligence for strategic social marketing. Businesses, 4(2), 196-210. https://doi.org/10.3390/businesses4020013
  27. Falvo, F. R., & Cannataro, M. (2024). Ethics of artificial intelligence: Challenges, opportunities and future prospects. In Proceedings of the 2024 IEEE International Conference on Bioinformatics and Biomedicine (pp. 5860-5867). IEEE. https://doi.org/10.1109/BIBM62325.2024.10822112
  28. Ferrara, E. (2024). Fairness and bias in artificial intelligence: A brief survey of sources, impacts, and mitigation strategies. Sci, 6(1), Article 3. https://doi.org/10.3390/sci6010003
  29. Floridi, L. (2020). Artificial intelligence as a public service: Learning from Amsterdam and Helsinki. Philosophy & Technology, 33(4), 541-546. https://doi.org/10.1007/s13347-020-00434-3
  30. Fosso Wamba, S., & Queiroz, M. M. (2023). Responsible artificial intelligence as a secret ingredient for digital health: Bibliometric analysis, insights, and research directions. Information Systems Frontiers, 25(6), 2123-2138. https://doi.org/10.1007/s10796-021-10142-8
  31. Franzke, A. S., Muis, I., & Schäfer, M. T. (2021). Data ethics decision aid (DEDA): A dialogical framework for ethical inquiry of AI and data projects in the Netherlands. Ethics and Information Technology, 23(3), 551-567. https://doi.org/10.1007/s10676-020-09577-5
  32. Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35-41. https://doi.org/10.2307/3033543
  33. Gao, D. K., Haverly, A., Mittal, S., Wu, J., & Chen, J. (2024). A bibliometric analysis, critical issues, and key gaps. International Journal of Business Analytics, 11(1), 1-19. https://doi.org/10.4018/IJBAN.338367
  34. Ge, R. (2024). From pseudo-intimacy to cyber romance: A study of human and AI companions emotion shaping and engagement practices. Communications in Humanities Research, 52(1), 211-221. https://doi.org/10.54254/2753-7064/2024.19122
  35. Glänzel, W., & Schubert, A. (2004). Analysing scientific networks through co-authorship. In H. F. Moed, W. Glänzel, & U. Schmoch (Eds.), Handbook of quantitative science and technology research: The use of publication and patent statistics in studies of S&T systems (pp. 257-276). Springer. https://doi.org/10.1007/1-4020-2755-9_12
  36. Griffin, T. A., Green, B. P., & Welie, J. V. M. (2025). The ethical wisdom of AI developers. AI and Ethics, 5, 1087-1097. https://doi.org/10.1007/s43681-024-00458-x
  37. Gursoy, D., Başer, G., & Chi, C. G. (2025). Corporate digital responsibility: navigating ethical, societal, and environmental challenges in the digital age and exploring future research directions. Journal of Hospitality Marketing & Management, 34(3), 305–324. https://doi.org/10.1080/19368623.2025.2465634
  38. Hagendorff, T. (2020). The ethics of AI ethics: An evaluation of guidelines. Minds and Machines, 30(1), 99-120. https://doi.org/10.1007/s11023-020-09517-8
  39. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. PNAS, 102(46), 16569-16572. https://doi.org/10.1073/pnas.0507655102
  40. Hohenstein, J., Kizilcec, R. F., DiFranzo, D., Aghajari, Z., Mieczkowski, H., Levy, K., Naaman, M., Hancock, J., & Jung, M. F. (2023). Artificial intelligence in communication impacts language and social relationships. Scientific Reports, 13, Article 5487. https://doi.org/10.1038/s41598-023-30938-9
  41. Hwang, J. Y. (2024). Ethics of artificial intelligence: Examining moral accountability in autonomous decision-making systems. World Journal of Advanced Research and Reviews, 23(3), 3192-3198. https://doi.org/10.30574/wjarr.2024.23.3.2884
  42. Ionescu, Ș., Delcea, C., Chiriță, N., & Nica, I. (2024). Exploring the use of artificial intelligence in agent-based modeling applications: A bibliometric study. Algorithms, 17(1), Article 21. https://doi.org/10.3390/a17010021
  43. Jarrah, A. M., Wardat, Y., & Fidalgo, P. (2023). Using ChatGPT in academic writing is (not) a form of plagiarism: What does the literature say. Online Journal of Communication and Media Technologies, 13(4), Article e202346. https://doi.org/10.30935/ojcmt/13572
  44. Jawad, M., Talreja, K., Bhutto, S. A., & Faizan, K. (2024). Investigating how AI personalization algorithms influence self-perception, group identity, and social interactions online. Review of Applied Management and Social Sciences, 7(4), 533-550. https://doi.org/10.47067/ramss.v7i4.397
  45. Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389-399. https://doi.org/10.1038/s42256-019-0088-2
  46. Kamila, M. K., & Jasrotia, S. S. (2023). Ethical issues in the development of artificial intelligence: Recognizing the risks. International Journal of Ethics and Systems, 41(1), 45-63. https://doi.org/10.1108/IJOES-05-2023-0107
  47. Kasun, G. S., Liao, Y. C., Margulieux, L. E., & Woodall, M. (2024). Unexpected outcomes from an AI education course among education faculty: Toward making AI accessible with marginalized youth in urban Mexico. Frontiers in Education, 9, Article 1368604. https://doi.org/10.3389/feduc.2024.1368604
  48. Khan, R. (2024). Role of AI in enhancing accessibility for people with disabilities. Journal of Artificial Intelligence General Science, 3(1), 125-142. https://doi.org/10.60087/jaigs.vol03.issue01.p142
  49. Kim, H. Y., & McGill, A. L. (2024). AI-induced dehumanization. Journal of Consumer Psychology, 35(3), 363-381. https://doi.org/10.1002/jcpy.1441
  50. Kouros, T., & Papa, V. (2024). Digital mirrors: AI companions and the self. Societies, 14(10), Article 200. https://doi.org/10.3390/soc14100200
  51. Li, H., & Zhang, R. (2024). Finding love in algorithms: Deciphering the emotional contexts of close encounters with AI chatbots. Journal of Computer-Mediated Communication, 29(5), Article zmae015. https://doi.org/10.1093/jcmc/zmae015
  52. Liu, Y., Zhang, Z., & Wu, Y. (2024). Will generative AI create a new social divide? Investigating the impacts of generative AI use on social capital in China. International Journal of Human-Computer Interaction, 41(18), 11324-11340. https://doi.org/10.1080/10447318.2024.2443242
  53. Margetis, G., Ntoa, S., Antona, M., & Stephanidis, C. (2021). Human-centered design of artificial intelligence. In G. Salvendy (Ed.), Handbook of human factors and ergonomics (pp.1085-1106). John Wiley & Sons. https://doi.org/10.1002/9781119636113.ch42
  54. Marko, J. G. O., Neagu, C. D., & Anand, P. B. (2025). Examining inclusivity: The use of AI and diverse populations in health and social care: A systematic review. BMC Medical Informatics and Decision Making, 25, Article 57. https://doi.org/10.1186/s12911-025-02884-1
  55. Martin, K. D., & Zimmermann, J. (2024). Artificial intelligence and its implications for data privacy. Current Opinion in Psychology, 58, Article 101829. https://doi.org/10.1016/j.copsyc.2024.101829
  56. Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2021). A survey on bias and fairness in machine learning. ACM Computing Surveys, 54(6), 1-35. https://doi.org/10.1145/3457607
  57. Mittelstadt, B. (2019). Principles alone cannot guarantee ethical AI. Nature Machine Intelligence, 1(11), 501-507. https://doi.org/10.1038/s42256-019-0114-4
  58. Nakao, Y., Strappelli, L., Stumpf, S., Naseer, A., Regoli, D., & Gamba, G. Del. (2023). Towards responsible AI: A design space exploration of human-centered artificial intelligence user interfaces to investigate fairness. International Journal of Human-Computer Interaction, 39(9), 1762-1788. https://doi.org/10.1080/10447318.
  59. 2022.2067936
  60. Nasir, S., Khan, R. A., & Bai, S. (2024). Ethical framework for harnessing the power of AI in healthcare and beyond. IEEE Access, 12, 31014-31035. https://doi.org/10.1109/ACCESS.2024.3369912
  61. Nazeer, M. Y. (2024). Algorithmic conscience: An in-depth inquiry into ethical dilemmas in artificial intelligence. International Journal of Research and Innovation in Social Science, 8(5), 725-732. https://doi.org/10.47772/IJRISS.2024.805052
  62. 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
  63. Rezaev, A. V. (2021). Twelve theses on artificial intelligence and artificial sociality. Monitoring Public Opinion: Economic and Social Changes, 1, 20-30. https://doi.org/10.14515/MONITORING.2021.1.1894
  64. Rokhshad, R., Ducret, M., Chaurasia, A., Karteva, T., Radenkovic, M., Roganovic, J., Hamdan, M., Mohammad-Rahimi, H., Krois, J., Lahoud, P., & Schwendicke, F. (2023). Ethical considerations on artificial intelligence in dentistry: A framework and checklist. Journal of Dentistry, 135, Article 104593. https://doi.org/10.1016/j.jdent.2023.104593
  65. Rosenbaum, H., Gumusel, E., Sanfilippo, M. R., Sweeney, M., Sawyer, S., & Zhou, K. Z. (2024). Exploring some impacts of advances in artificial intelligence: A social informatics approach. Proceedings of the Association for Information Science and Technology, 61(1), 818-821. https://doi.org/10.1002/pra2.1109
  66. Savic, M. (2024). Artificial companions, real connections? Examining AI’s role in social connection. M/C Journal, 27(6). https://doi.org/10.5204/mcj.3111
  67. Serpa, S., Micic, L., Štilić, A., & Mastilo, Z. (2025). Sociology of artificial intelligence for social sustainability in the digital age. Academic Journal of Interdisciplinary Studies, 14(1), Article 37. https://doi.org/10.36941/ajis-2025-0003
  68. Vainio-Pekka, H., Agbese, M. O. O., Jantunen, M., Vakkuri, V., Mikkonen, T., Rousi, R., & Abrahamsson, P. (2023). The role of explainable AI in the research field of AI ethics. ACM Transactions on Interactive Intelligent Systems, 13(4), 1-39. https://doi.org/10.1145/3599974
  69. Wu, J. (2024). Social and ethical impact of emotional AI advancement: The rise of pseudo-intimacy relationships and challenges in human interactions. Frontiers in Psychology, 15, Article 1410462. https://doi.org/10.3389/fpsyg.2024.1410462
  70. Zhang, Y., Wu, M., Tian, G. Y., Zhang, G., & Lu, J. (2021). Ethics and privacy of artificial intelligence: Understandings from bibliometrics. Knowledge-Based Systems, 222, Article 106994. https://doi.org/10.1016/j.knosys.2021.106994
  71. Zulfiqar, N., Shaikh, B. A., Shah, S. A., & Awan, A. (2024). Investigating how AI technologies influence changing social norms and behaviors on social media, particularly in areas like communication and self-presentation. Review of Education, Administration & Law, 7(4), 167-183. https://doi.org/10.47067/real.v7i4.371