NAVIGATING THE ALGORITHMIC WITNESS: AI AND CASE EVIDENCE CHALLENGES FOR LAW PRACTITIONERS IN THE UAE

Abstract

This research study investigates the use of AI-based evidence in the UAE's legal system, prompted by ambitious efforts such as the National AI Strategy 2031 and the "Court of the Future." It asks if the built-in complexity and uniqueness of AI-generated evidence can produce an "accountability gap" that at first compromises fundamental legal standards, such as having the right to confront witnesses, in a way similar to a judicial shutdown. The primary goal is to understand the unique, practical challenges that UAE attorneys, judicial officials, and prosecutors face, as well as to examine the system's adaptive reaction. A mixed-methods study strategy was used, combining a detailed theoretical examination of UAE central and free-zones laws with in-depth qualitative interviews with legal professionals who have direct experience with algorithmic evidence. The findings indicate three crises: an evident complexity caused by AI's "black box" character, a dual visibility and cultural verification crisis including trade secret disagreements and discrimination in foreign-trained systems, and a systemic and lack of expertise . The paper identifies new changes, such as legal "conditional admissibility" concepts and procedural advances in highly specialised courts like the DIFC’s Digital Economy Court. The UAE's rapid technological advancement has led to context-based suppression of normal legal safeguards. This "functional legal gap" can be rectified. The report believes that the country's technological objectives must be matched by a corresponding evolution in procedural legislation, professional education, and governance structures. Proposals include establishing Legal Practice Regulations on AI Evidence, requiring "AI Litigation Literacy" certification, and making legal changes to ensure that algorithmic evidence upholds justice, transparency, and human dignity.

Keywords: UAE Law, Digital Evidence, Artificial Intelligence, Algorithmic Bias, Legal Technology, Legal Ethics, Judicial Reform, DIFC’s courts, Federal Law No. 34 of 2021, Machine Learning Model, Deepfake.