Agha, R. A., Mathew, G., Rashid, R., Kerwan, A., Al-Jabir, A., Sohrabi, C., Franchi, T., Nicola, M., Agha, M., & TITAN Group. (2025). Transparency in the reporting of artificial intelligence – the TITAN guideline. Premier Journal of Science, 10, Article 100082. https://doi.org/10.70389/PJS.100082
Akinrinola, O., Okoye, C. C., Ofodile, O. C., & Ugochukwu, C. E. (2024). Navi-gating and reviewing ethical dilemmas in AI development: Strategies for transparency, fairness, and accountability. GSC Advanced Research and Re-views, 18(3), 50–58. https://doi.org/10.30574/gscarr.2024.18.3.0088
Busuioc, M. (2021). Accountable artificial intelligence: Holding algorithms to account. Public Administration Review, 81(5), 825–836. https://doi.org/10.1111/ puar.13293
Camilleri, M. A. (2024). Artificial intelligence governance: Ethical consider-ations and implications for social responsibility. Expert Systems, 41(7), Article e13406. https://doi.org/ 10.1111/exsy.13406
Carneiro, D., & Veloso, P. (2021). Ethics, transparency, fairness and the re-sponsibility of artificial intelligence. In International Conference on Disruptive Technologies, Tech Ethics and Artificial Intelligence (pp. 109–120). Springer In-ternational Publishing.
Cheong, B. C. (2024). Transparency and accountability in AI systems: Safeguard-ing wellbeing in the age of algorithmic decision-making. Frontiers in Human Dynamics, 6, Article 1421273. https://doi.org/10.3389/fhumd.2024.1421273
Chowdhury, S., Joel-Edgar, S., Dey, P. K., Bhattacharya, S., & Kharlamov, A. (2023). Embedding transparency in artificial intelligence machine learning models: Managerial implications on predicting and explaining employee turnover. The International Journal of Human Resource Management, 34(14), 2732–2764. https://doi.org/ 10.1080/09585192.2022.2066981
Elliott, K., Price, R., Shaw, P., Spiliotopoulos, T., Ng, M., Coopamootoo, K., & Van Moorsel, A. (2021). Towards an equitable digital society: artificial intelligence (AI) and corporate digital responsibility (CDR). Society, 58(3), 179–188. https://doi.org/10.1007/s12115-021-00594-8
Fisher, S., & Rosella, L. C. (2022). Priorities for successful use of artificial intelli-gence by public health organizations: A literature review. BMC Public Health, 22(1), Article 2146. https://doi.org/10.1186/s12889-022-14422-z
Habbal, A., Ali, M. K., & Abuzaraida, M. A. (2024). Artificial Intelligence Trust, risk and security management (AI trism): Frameworks, applications, chal-lenges and future research directions. Expert Systems with Applications, 240, Article 122442. https://dl.acm.org/doi/10.1016/j.eswa.2023.122442
Hosseini Tabaghdehi, S. A., & Ayaz, Ö. (2025). AI ethics in action: A circular model for transparency, accountability and inclusivity. Journal of Managerial Psychology. https://doi.org/ 10.1108/jmp-03-2024-0177
Hussain, A., & Hussain, A. (2025). Transparency and accountability: Unpack-ing the real problems of explainable AI. AI & SOCIETY, 1–2. https://doi. org/10.1007/s00146-025-02302-0
Illia, L., Colleoni, E., & Zyglidopoulos, S. (2023). Ethical implications of text generation in the age of artificial intelligence. Business Ethics, the Environment & Responsibility, 32(1), 201–210. https://doi.org/10.1111/beer.12479
Kamila, M. K., & Jasrotia, S. S. (2025). Ethical issues in the development of ar-tificial intelligence: recognizing the risks. International Journal of Ethics and Systems, 41(1), 45–63. https://doi.org/10.1108/IJOES-05-2023-0107
Karalis, V. D. (2024). The integration of artificial intelligence into clinical practice. Applied Biosciences, 3(1), 14–44. https://doi.org/10.3390/applbiosci3010002 Khalifa, M., & Albadawy, M. (2024). Using artificial intelligence in academic writing and research: An essential productivity tool. Computer Methods and Programs in Biomedicine Update, 5, Article 100145. https://doi.org/10.1016/j. cmpbup.2024.100145
Kharitonova, Y. S. (2023). Legal means of providing the principle of transpar-ency of the artificial intelligence. Journal of Digital Technologies and Law, 1(2). https://doi.org/10.21202/jdtl.2023.14
Kiseleva, A., Kotzinos, D., & De Hert, P. (2022). Transparency of AI in healthcare as a multilayered system of accountabilities: Between legal requirements and technical limitations. Frontiers in Artificial Intelligence, 5, Article 879603. https://doi.org/10.3389/frai.2022.879603
Lehner, O. M., Ittonen, K., Silvola, H., Ström, E., & Wührleitner, A. (2022). Arti-ficial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking. Accounting, Auditing & Accountability Journal, 35(9), 109–135. https://doi.org/10.1108/AAAJ-09-2020-4934
Loi, M., & Spielkamp, M. (2021). Towards accountability in the use of arti-ficial intelligence for public administrations. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (pp. 757–766). https://doi. org/10.1145/3461702.3462631
Memarian, B., & Doleck, T. (2023). Fairness, accountability, transparency, and ethics (FATE) in artificial intelligence (AI) and higher education: A system-atic review. Computers and Education: Artificial Intelligence, 5, Article 100152. https://doi.org/10.1016/j.caeai.2023.100152
Mensah, G. B. (2023, November). Artificial intelligence and ethics: A compre-hensive review of bias mitigation, transparency, and accountability in AI systems [Preprint]. https://doi.org/10.13140/RG.2.2.23381.19685/1
Modi, T. B. (2023). Artificial intelligence ethics and fairness: A study to address bias and fairness issues in AI systems, and the ethical implications of AI applications. Revista Review Index Journal of Multidisciplinary, 3(2), 24–35. https://doi.org/10.31305/rrijm2023.v03.n02.004
Mohammad Amini, M., Jesus, M., Fanaei Sheikholeslami, D., Alves, P., Has-sanzadeh Benam, A., & Hariri, F. (2023). Artificial intelligence ethics and challenges in healthcare applications: a comprehensive review in the context of the European GDPR mandate. Machine Learning and Knowledge Extraction, 5(3), Article 1023–1035. https://orcid.org/10.3390/make5030053
Naik, N., Hameed, B. M., Shetty, D. K., Swain, D., Shah, M., Paul, R., … & So-mani, B. K. (2022). Legal and ethical consideration in artificial intelligence in healthcare: Who takes responsibility? Frontiers in Surgery, 9, Article 862322. https://doi.org/10.3389/fsurg.2022.862322
Oniani, D., Hilsman, J., Peng, Y., Poropatich, R. K., Pamplin, J. C., Legault, G. L., & Wang, Y. (2023). Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare. NPJ Digital Medicine, 6(1), 225. https://doi.org/10.1038/s41746-023-00965-x
Potwora, M., Vdovichena, O., Semchuk, D., Lipych, L., & Saienko, V. (2024). The use of artificial intelligence in marketing strategies: Automation, per-sonalization and forecasting. Journal of Management World, 2, 41–49. https:// doi.org/10.53935/jomw.v2024i2.275
Rachmad, Y. E. (2022). The role of artificial intelligence and human collaboration in Management 5.0: A global perspective. UN Global Compact. https://doi. org/10.17605/OSF.IO/VFMKR
Santoni de Sio, F., & Mecacci, G. (2021). Four responsibility gaps with artificial intelligence: Why they matter and how to address them. Philosophy & technol-ogy, 34(4), 1057–1084. https://doi.org/10.1007/s13347-021-00450-x
Slimi, Z., & Carballido, B. V. (2023). Navigating the ethical challenges of artificial intelligence in higher education: An analysis of seven global ai ethics policies. TEM Journal, 12(2). https://doi.org/10.18421/TEM122-02
Smith, H. (2021). Clinical AI: Opacity, accountability, responsibility and liability. AI & Society, 36(2), 535–545. https://doi.org/doi/10.1007/s00146-020-01019-6
Tang, A., Li, K. K., Kwok, K. O., Cao, L., Luong, S., & Tam, W. (2024). The impor-tance of transparency: Declaring the use of generative artificial intelligence (AI) in academic writing. Journal of Nursing Scholarship, 56(2), 314-318. https://doi.org/10.1111/jnu.12938
Usmani, U. A., Happonen, A., & Watada, J. (2023). Human-centered artificial intelligence: Designing for user empowerment and ethical considerations. In 2023 5th international congress on human-computer interaction, optimization and robotic applications (HORA). IEEE. https://doi.org/10.1109/HORA58378.2023.10156761
Von Eschenbach, W. J. (2021). Transparency and the black box problem: Why we do not trust AI. Philosophy & Technology, 34(4), 1607–1622. https://doi.org/10.1007/s13347-021-00477-0
Walmsley, J. (2021). Artificial intelligence and the value of transparency. AI & Society, 36(2), 585–595. https://dl.acm.org/doi/10.1007/s00146-020-01066-z
Zerilli, J., Bhatt, U., & Weller, A. (2022). How transparency modulates trust in artificial intelligence. Patterns, 3(4). https://dl.acm.org/doi/10.1007/s00146-020-01066-z
Zhang, C., Zhu, W., Dai, J., Wu, Y., & Chen, X. (2023). Ethical impact of artificial intelligence in managerial accounting. International Journal of Accounting Infor-mation Systems, 49, Article 100619. https://doi.org/10.1016/j.accinf.2023.100619
Zhang, J., & Zhang, Z. M. (2023). Ethics and governance of trustworthy medical artificial intelligence. BMC Medical Informatics and Decision Making, 23(1), 7. https://doi.org/10.1186/s12911-023-02103-9