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An “A-eye” to the future of arbitration: a new world or a better world?

Rania Alnaber

International Journal of Law and Information Technology2025https://doi.org/10.1093/ijlit/eaaf006article
ABDC A
Weight
0.37

Abstract

Taking a holistic approach, this paper offers an in-depth examination of artificial intelligence’s (AI) impact on arbitration both from practitioners and clients’ perspective. Without purporting to have a crystal ball to foresee the future, a realistic assessment of AI’s current state of art indicates that AI integration can enhance the arbitration practice but not completely revolutionize the whole landscape to become fully autonomous. To fully leverage its benefits, practitioners need to recognize AI’s limitations such as black-box issues, hallucination, and AI’s hunger for data for functionality. This paper further assesses the need for change of confidentiality concepts in arbitration in support of AI while taking into consideration the interest of all stakeholders. With all the benefits AI may bring to the arbitration practice, it is important to recognize the risks that AI may impose on the integrity of proceedings, confidentiality, and due process. This paper advocates for a hybrid regulatory framework that combines soft and hard law, emphasizing that maintaining a responsible and ethical use of AI is key at all times. The paper also stresses an important point, that no matter how far advanced AI can be, the wisher (i.e. arbitrators and counsel) needs to have the appropriate skills for the genie to work well.

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https://doi.org/https://doi.org/10.1093/ijlit/eaaf006

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@article{rania2025,
  title        = {{An “A-eye” to the future of arbitration: a new world or a better world?}},
  author       = {Rania Alnaber},
  journal      = {International Journal of Law and Information Technology},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1093/ijlit/eaaf006},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.