examining the potential challenges | 10.1163/22131035-14020001 29 As a result of ai’s ability to process large volumes of data at a pace that surpasses human capabilities, ai algorithms can support human decisionmakers in speeding up the statelessness determination process in a number of ways. Since machine learning can identify hidden anomalies, this makes it very useful. ai algorithm can speedily detect the lack of any form of documentation regarding an individual’s personal circumstances. It can be used to generate a simple binary indicator to show whether specific documents such as passport, id, birth certificates are present or missing. By learning from previous computations and extracting regularities from massive databases, ai algorithms can help produce reliable and repeatable decisions in routine task. For example, ai algorithms can be used to automatically cross-check the application fields to detect missing or incomplete submissions. Flagging these issues early can reduce processing and decision-making times and better manage application loads. Since the process of statelessness determination can take a long time, addressing these challenges early on can prevent applicants from spending extended periods in an insecure position.166 ai algorithms can be used specifically to identify contradictory information or discrepancies in an application form. In addition, ai algorithm can sift through a vast database of case laws, providing decision makers with relevant information in a fraction of time it will take manual processing.167 4.2.2 Challenges with Partial use of ai In these partial tasks, bias worries and procedural fairness issues are a less concern. However, privacy concerns remains. If ai algorithms are employed to cross-check application fields for missing or incomplete information and to detect the absence of documentation, the data may still be vulnerable to privacy risks, as previously discussed under privacy. Reliability concerns may arise in situations relating to citations. ai systems employing machine learning can produce fabricated references; for instance, ChatGPT has been noted for generating fictitious citations and non-existent cases.168 166 167 168 Ibid. ‘ai in legal research’ 5 May 2025 <https://www.sdlaw.co.za/articles/ai-in-legal-research/> accessed 30 September 2025. Roberto Marta v Avianca, Inc Case 1:22-cv-01461-pkc (S.D.N.Y June 22, 2023) <https://s3 .documentcloud.org/documents/23826753/judgeaskingtheotherlawyerwhyhe submittedafilingwithfakecases.pdf> accessed 3 June 2025; Mavundla v mec: Department of Co-Operative Government and Traditional Affairs KwaZulu-Natal and Others 2025 (3) sa 534 (kzp) (8 January 2025). International Human Rights Law Review (2025) 1–31