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At the recent Constitutional Courts and Supreme Courts Summit ("J20 Summit"), the Chief Justice of the of South Africa, Madam Justice Mandisa Maya, together with heads of judiciaries, chief justices and court presidents, shared their insights on artificial intelligence ("AI") in legal practice.
The J20 Summit, hosted in South Africa in September 2025, brought together judicial leaders from G20 nations and across Africa under the theme, "Justice in a time of change: Independence, innovation and cooperation". Central discussions focused on the transformative role of AI and legal technology in strengthening judicial independence, improving access to justice and addressing cross-border challenges such as climate change and cybercrime.
This article explores the topic raised during the J20 summit that:
"AI, when designed for local contexts, can transform linguistic exclusion into linguistic inclusion, an advancement of enormous significance for justice in Africa".
Is ChatGPT linguistically inclusive for legal matters?
When used responsibly, AI can make court proceedings more accessible. It can deliver near real-time speech-to-text transcription, translate documents into multiple languages and enable multilingual searches across court judgements, enabling litigants to read court documents in their home language and legal teams to find precedents faster.
However, as with the well-publicised issue of AI hallucinations in legal research, AI transcription and translation require a strict "human-in-the-loop" approach. Lawyers must remain alert to hallucinations, omissions and confidently presented inaccuracies.
To improve access to justice, it is essential to address limitations, risks and potential biases in AI outputs that can compromise fairness. Cultural and technical subtleties, including dialects, idiomatic usage and specialised legal terminology – are often misunderstood by AI models (and by non-expert human translators). Inadequate or skewed training data can further disadvantage speakers of indigenous languages. Unregulated use may also lead to inadvertent disclosure of privileged or personal information, raising significant confidentiality and intellectual property concerns.
Large language mishaps
When asked which AI translation method is best, the lawyer's answer applies: "It depends".
Do you prioritise readability or reliability?
While large language models ("LLMs") can accelerate translation, improve fluency, and cover broad topics, they are not a replacement for purpose-built machine translation ("MT"), particularly where scale, completeness, accuracy and consistency are required. A human-machine hybrid remains best practice.
- AI-generative (e.g., ChatGPT) vs Cognitive MT
It is critical to benchmark tools on the relevant languages and dialects before deployment. For example:
- Generative AI (LLM-based) excels at summarising and creating content. It predicts likely word sequences and tends to produce more readable translations. Whilst user-friendly, this can create a false sense of security in legal work.
- Cognitive/MT tools rely on predefined linguistic rules or statistical correlations from parallel corpora (datasets of aligned source texts and their translations). They are often more predictable and transparent, and easier to audit and control for legal use.
According to this article, generative AI is better suited to creating and localising content for specific languages, whereas MT is better suited for specialised documents, (such as legal contracts) and instant translation (such as, contemporaneous interpretation of court proceedings).
- AI - ChatGPT vs Human
A Finish study, in the social and health care sector found that GPT-4 demonstrated promising productivity in translation, but confirmed the need for a dual-pass process; AI generates a draft and a human reviewer edits the output. In legal contexts, the reviewer should be a professional translator with subject-matter expertise, supplemented by back-translation (translating back into the source language to detect any changes in meaning.
Another comparing human and ChatGPT-generated translations of Arabic legal documents, (including contracts) found human translators more accurate on legal terminology, complex constructs and cultural nuance. The tools are not "inherently flawed" but take a different approach; the study concluded that AI translations are not "inherently flawed" but take a different approach; the study concluded that AI translations are not yet suitable for official use in legal contexts.
- Validating generative AI output
To mitigate risks in generative AI translation:
- Be aware of the "lost in the middle" effect (bias towards the beginning and end of documents) and context-window limits, which can cause omissions.
- Expect hallucinations, (plausible but incorrect names, citations, or legal terms), formatting errors, and inconsistent terminology.
Call to action: Setting legal standards for linguistic inclusion
AI is reshaping legal work, from court transcription to document review. AI-powered translation and transcription – often integrated as co-pilots – are now commonplace. As these tools become embedded in court systems, and legal workflows, the profession stands at a critical juncture.
Designed for local contexts and deployed responsibly, AI can convert linguistic barriers into opportunities for inclusion, promoting more equitable legal outcomes.
To achieve sustainable linguistic inclusion, lawyers must develop and maintain AI literacy, backed by investment in local-language datasets, domain expertise, and fine-tuned models for low resource languages.
Legal professionals should set the tone: embrace innovation, insist on equality.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
