The Influence of Artificial Intelligence in the Resolution of Family Law Disputes: Prospects and Challenges
DOI:
https://doi.org/10.58740/jmcr.v1i2.370Keywords:
Artificial Intelligence, Dispute Resolution, Family LawAbstract
This research aims to explore the prospects and challenges of applying Artificial Intelligence (AI) in family law dispute resolution. The method used in this research is a qualitative approach with literature study and normative juridical analysis, as well as interviews with legal practitioners and academics. The results show that AI has great potential in improving legal efficiency and accessibility by accelerating the mediation process and providing initial legal consultation for the community. However, the research also identified several key challenges, including AI's limitations in understanding the emotional and psychological aspects of family disputes, the risk of algorithm bias, and the legal validity of the resulting decisions. The implications of this research confirm that AI can be a useful support tool in the legal process, but it cannot completely replace the role of humans. Therefore, strict regulations as well as human involvement in the verification process and final decision-making are needed to ensure that justice is maintained.
References
Anwar, Y., Zarzani, T., Halawa, F., & Fauzi, T. (2021). Enhance of Legal Protection the Health Outsourcing Workers in Health Law Number 36 of 2009. , 4, 4685-4696. https://doi.org/10.33258/BIRCI.V4I3.2251.
Alarie, B., Niblett, A., & Yoon, A. (2018). How artificial intelligence will affect the practice of law. University of Toronto Law Journal, 68, 106 - 124. https://doi.org/10.2139/SSRN.3066816.
Armour, J., & Sako, M. (2020). AI-enabled business models in legal services: from traditional law firms to next-generation law companies?. Journal of Professions and Organization. https://doi.org/10.2139/SSRN.3418810.
Barnett, J., & Treleaven, P. (2018). Algorithmic Dispute Resolution - The Automation of Professional Dispute Resolution Using AI and Blockchain Technologies. Comput. J., 61, 399-408. https://doi.org/10.1093/COMJNL/BXX103.
Branting, K., Pfeifer, C., Brown, B., Ferro, L., Aberdeen, J., Weiss, B., Pfaff, M., & Liao, B. (2020). Scalable and explainable legal prediction. Artificial Intelligence and Law, 29, 213 - 238. https://doi.org/10.1007/s10506-020-09273-1.
Brooks, C., Gherhes, C., & Vorley, T. (2020). Artificial intelligence in the legal sector: pressures and challenges of transformation. Cambridge Journal of Regions, Economy and Society. https://doi.org/10.1093/cjres/rsz026.
Chornopyska, V., & Chornopyska, K. (2024). Family mediation as a mode of dispute resolution in family legal relations. Visnik Nacional’nogo universitetu «Lvivska politehnika». Seria: Uridicni nauki. https://doi.org/10.23939/law2024.41.391.
Collini, E., Nesi, P., Raffaelli, C., & Scandiffio, F. (2024). Explainable Artificial Intelligence for Agile Mediation Propensity Assessment. IEEE Access, 12, 37782-37798. https://doi.org/10.1109/ACCESS.2024.3375766.
De Jesus Candeias, T. (2023). Artificial Intelligence's Role in Enhancing Conflict Resolution within the Online Dispute Resolution (ODR) System. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4559439.
Fatima, N. (2023). From Courtrooms to Algorithms: The Evolution of Dispute Resolution with AI. Revista Brasileira de Alternative Dispute Resolution. https://doi.org/10.52028/rbadr.v5i10.art13.in.
Mowbray, A., Chung, P., & Greenleaf, G. (2020). Utilising AI in the legal assistance sector - Testing a role for legal information institutes. Comput. Law Secur. Rev., 38, 105407. https://doi.org/10.1016/J.CLSR.2020.105407.
Neiroukh, S., Emeagwali, O., & Aljuhmani, H. (2024). Artificial intelligence capability and organizational performance: unraveling the mediating mechanisms of decision-making processes. Management Decision. https://doi.org/10.1108/md-10-2023-1946.
Rabets, A., & Khvatova, M. (2023). Mediation in the system of ways of alternative settlement of family disputes. Vestnik Tomskogo gosudarstvennogo universiteta. Pravo. https://doi.org/10.17223/22253513/46/13.
Singh, S. (2024). Use of AI-driven support system to help courts in predicting child custody outcomes in India. World Journal of Advanced Research and Reviews. https://doi.org/10.30574/wjarr.2024.23.1.2108.
Thiebes, S., Lins, S., & Sunyaev, A. (2020). Trustworthy artificial intelligence. Electronic Markets, 31, 447 - 464. https://doi.org/10.1007/s12525-020-00441-4.
Van Der Haegen, M. (2023). Quantitative legal prediction as a dispute resolution mechanism. European Review of Private Law. https://doi.org/10.54648/erpl2023028.
Winter, C., Hollman, N., & Manheim, D. (2023). Value Alignment for Advanced Artificial Judicial Intelligence. American Philosophical Quarterly. https://doi.org/10.5406/21521123.60.2.06.
Zhang, X. (2024). Legal Challenges and Responses to Artificial Intelligence-Assisted Decision-Making in the International Economic Law System. Applied Mathematics and Nonlinear Sciences. https://doi.org/10.2478/amns-2024-2506.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Sri Yuliani, Syarif Firmansyah, Raynaldi Nugraha Prasetya
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Journal of Multidiscipline and Collaboration Research provides open access to anyone so that the information and findings in these articles are useful for everyone. This journal's article content can be accessed and downloaded for free, following the creative commons license used.
