Artificial Intelligence and the Challenge of Hallucinations in Legal Practice
Recently, a law firm encountered significant difficulties after relying entirely on an artificial intelligence (AI) tool to prepare a legal complaint. The AI-generated document was not reviewed by human professionals, resulting in the submission of inaccurate and fabricated information. As a consequence, the relevant judicial authority dismissed the complaint, and the law firm now faces potential repercussions for its oversight.
This incident highlights a pressing issue regarding AI integration into the legal sector. When discussing AI 'hallucinations', the term refers to instances where AI systems generate plausible-sounding but factually incorrect or unsupported information. Such occurrences typically arise when an AI model, rather than acknowledging its knowledge limitations, produces content that may appear credible but is not grounded in actual data.
Researchers, including those from the Fraunhofer Institute, identify three primary causes for these hallucinations: the quality of the training data, the methods used during training, and the approach the model employs in generating responses (inference). In cases where non-specialized AI tools are used--such as mainstream models not tailored to legal work--access to comprehensive and current legal knowledge is often lacking. These general-purpose AI systems tend to rely on correlations within the data rather than true causal relationships, which can result in surface-level or erroneous analyses.
Given these risks, experts recommend that human oversight remains essential wherever AI is deployed, especially in fields demanding high accuracy and reliability, such as education, media, healthcare, and law. In the legal domain, specialized AI solutions have been developed to address these challenges. For example, certain publishers in Austria have introduced proprietary legal AI applications designed to operate exclusively with verified legal databases, limiting the risk of hallucination and enhancing reliability.
These legal AI products, including those developed by leading firms, implement strict standards based on international norms to ensure the integrity of their outputs. Such platforms are engineered to save time for legal professionals, with reports from the United States indicating that these tools can reduce research time by up to eleven hours per week for lawyers. Unlike general AI models connected to the broader internet, these legal-specific systems focus solely on authoritative legal sources, reducing exposure to outdated or incorrect information.
Nonetheless, maintaining up-to-date and accurate legal databases poses its own challenges. Laws are subject to frequent amendments, new case law emerges regularly, and even minor legislative changes can impact the validity of information stored within AI systems. Ensuring the currency of these systems is therefore a continuous process requiring diligent oversight.
Regulatory frameworks are also evolving to address the risks associated with AI in high-stakes environments. The latest phase of the European Union's AI Act, which came into effect this summer, classifies judicial applications of AI as 'high-risk'. As a result, legal professionals and institutions must comply with stringent requirements before deploying such solutions, with even stricter standards applied to the judiciary itself. The aim is to safeguard legal processes by ensuring that AI-generated content meets rigorous criteria for accuracy, transparency, and accountability.
The integration of AI into legal work holds significant promise for improving efficiency and access to information. However, recent incidents underscore the necessity for robust human oversight and the use of specialized, well-regulated tools to prevent errors and uphold the quality and credibility of legal proceedings.