The Impact of Explainable AI on User Trust and Ethical AI Adoption in Indonesia
Article Sidebar
Main Article Content
Abstract
Explainable Artificial Intelligence (XAI) is increasingly recognized as a critical enabler of trust and ethical AI adoption. This study explores the impact of XAI on user trust and ethical AI adoption within Indonesian academia through a qualitative analysis of five informants, including AI researchers, university administrators, and policymakers. The findings reveal that XAI enhances transparency and ethical awareness while fostering trust among academic stakeholders. However, technical complexity, resource limitations, and resistance to change pose significant barriers to implementation. The study also identifies opportunities for fostering XAI adoption, such as collaborative initiatives, government support, and tailored training programs. These insights contribute to the growing discourse on leveraging XAI for promoting ethical and trustworthy AI practices in academia.
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
A. Harry, “Role of AI in Education.,” Interdiciplinary J. Hummanity, vol. 2, no. 3, 2023.
B. B. Khatri and P. D. Karki, “Artificial intelligence (AI) in higher education: Growing academic integrity and ethical concerns,” Nepal. J. Dev. Rural Stud., vol. 20, no. 01, pp. 1–7, 2023.
M. O. Syaidina, R. Fahrudin, and I. A. Mutiara, “Implementation of Ethics of Using Artificial Intelligence in the Education System in Indonesia,” Blockchain Front. Technol., vol. 4, no. 1, pp. 63–71, 2024.
F. M. Leta and D. P. C. Vancea, “Ethics in education: Exploring the ethical implications of artificial intelligence implementation,” Ovidius Univ. Ann. Econ. Sci. Ser., vol. 23, no. 1, pp. 413–421, 2023.
Z. Slimi and B. V. Carballido, “Navigating the Ethical Challenges of Artificial Intelligence in Higher Education: An Analysis of Seven Global AI Ethics Policies.,” Tem J., vol. 12, no. 2, 2023.
D. Patil, “Explainable Artificial Intelligence (XAI): Enhancing Transparency And Trust In Machine Learning Models,” Available SSRN 5057400, 2024.
P. Linardatos, V. Papastefanopoulos, and S. Kotsiantis, “Explainable ai: A review of machine learning interpretability methods,” Entropy, vol. 23, no. 1, p. 18, 2020.
M. SureshKumar, S. I. Vishwa Raviraaj, and R. Sukhresswarun, “Inclusion of XAI in artificial intelligence and deep learning technologies,” IET, 2023.
M. R. Contreras and J. O. P. Jaimes, “AI Ethics in the Fields of Education and Research: A Systematic Literature Review,” in 2024 International Symposium on Accreditation of Engineering and Computing Education (ICACIT), 2024, pp. 1–6.
N. Curtis, “To ChatGPT or not to ChatGPT? The impact of artificial intelligence on academic publishing,” Pediatr. Infect. Dis. J., vol. 42, no. 4, p. 275, 2023.
E. Muwagunzi, R. Kabuye, C. Ddamulira, and S. Kizza, “Artificial Intelligence in Academic Research at Bugema University: Transforming Methodologies and Ethical Considerations,” East African J. Interdiscip. Stud., vol. 7, no. 1, pp. 489–503, 2024.
M. Fauziddin et al., “The Impact of AI on the Future of Education in Indonesia,” Educ. J. Ilm. Pendidik., vol. 3, no. 1, pp. 11–16, 2025.
G. Malik, D. K. Tayal, and S. Vij, “An analysis of the role of artificial intelligence in education and teaching,” in Recent Findings in Intelligent Computing Techniques: Proceedings of the 5th ICACNI 2017, Volume 1, 2019, pp. 407–417.
Z. H. Sain, S. H. Sain, and R. Serban, “Implementing Artificial Intelligence in Educational Management Systems: A Comprehensive Study of Opportunities and Challenges,” Asian J. Manag. Sci., vol. 13, no. 1, pp. 23–31, 2024.
N. B. Trivedi, “AI in education-A transformative force,” in 2023 1st DMIHER International Conference on Artificial Intelligence in Education and Industry 4.0 (IDICAIEI), 2023, vol. 1, pp. 1–4.
D. Gunning, M. Stefik, J. Choi, T. Miller, S. Stumpf, and G.-Z. Yang, “XAI—Explainable artificial intelligence,” Sci. Robot., vol. 4, no. 37, p. eaay7120, 2019.
A. K. Das, M. F. Hossain, B. U. Khan, M. M. Rahman, M. A. Z. Asad, and M. Akter, “Circular economy: A sustainable model for waste reduction and wealth creation in the textile supply chain,” SPE Polym., vol. 6, no. 1, p. e10171, 2025.
A. Das and P. Rad, “Opportunities and challenges in explainable artificial intelligence (xai): A survey,” arXiv Prepr. arXiv2006.11371, 2020.
R. Yang and S. Wibowo, “User trust in artificial intelligence: A comprehensive conceptual framework,” Electron. Mark., vol. 32, no. 4, pp. 2053–2077, 2022.
S. A. Salloum, “Trustworthiness of the AI,” in Artificial intelligence in education: The power and dangers of ChatGPT in the classroom, Springer, 2024, pp. 643–650.
R. Duarte, F. Correia, P. Arriaga, and A. Paiva, “AI trust: Can explainable AI enhance warranted trust?,” 2023.
S. Sultana and S. S. Hasan, “Impact of micro-credit on economic empowerment of rural women,” Agric., vol. 8, no. 2, pp. 43–49, 2010.
C. Manresa-Yee, S. Ramis, F. X. Gaya-Morey, and J. M. Buades, “Impact of explanations for trustworthy and transparent artificial intelligence,” in Proceedings of the XXIII International Conference on Human Computer Interaction, 2023, pp. 1–8.
S. Tatineni, “Ethical considerations in AI and data science: Bias, fairness, and accountability,” Int. J. Inf. Technol. Manag. Inf. Syst., vol. 10, no. 1, pp. 11–21, 2019.
S. Shukla, “Principles governing ethical development and deployment of AI,” J. Artif. Intell. Ethics, vol. 7, no. 1, pp. 45–60, 2024.
B. S. Ayinla, O. O. Amoo, A. Atadoga, T. O. Abrahams, F. Osasona, and O. A. Farayola, “Ethical AI in practice: Balancing technological advancements with human values,” Int. J. Sci. Res. Arch., vol. 11, no. 1, pp. 1311–1326, 2024.
G. L. Moratinos, “Análisis de la propuesta de reglamento sobre los principios éticos para el desarrollo, el despliegue y el uso de la inteligencia artificial, la robótica y las tecnologías conexas,” Ius Sci., vol. 6, no. 2, pp. 26–41, 2020.
Y. Zhu, “Behavioral Finance: Bridging Psychology and Economics for Rational Financial Decisions,” J. Appl. Econ. Policy Stud., vol. 14, pp. 73–76, 2024.
P. P. Thulasiram, “Explainable Artificial Intelligence (Xai): Enhancing Transparency And Trust In Machine Learning Models,” 2025.