The use of artificial intelligence in expert evidence

The use of artificial intelligence in expert evidence

Artificial intelligence (AI) has become a highly influential tool across many professional fields, and expert evidence is no exception. Its ability to analyze large volumes of data, identify patterns, and optimize processes has opened up new opportunities in the preparation of expert reports and opinions. However, its application also raises significant technical, ethical and legal challenges that must be carefully addressed.

Use of AI in expert reports and opinions

In the field of expert evidence, AI can be used as a support tool to enhance the efficiency and accuracy of expert work. One of its most common applications is the automated analysis of documents, images, audio files, or financial data, allowing experts to detect inconsistencies, anomalies, or correlations that might go unnoticed during manual review.

AI-based systems can also streamline the data collection and classification stages, reducing time and improving the organization of evidence. In some cases, they are used to simulate scenarios, perform complex calculations or generate predictive models that help experts substantiate their conclusions.

It is important to emphasize that AI does not replace the professional judgment of the expert. Instead, it acts as a complementary tool. The final responsibility for the content of the report and the conclusions presented before a court remains with the human expert, who must interpret and validate the results produced by these technologies.

Warnings regarding the use of AI algorithms

The use of AI algorithms in expert evidence requires a number of precautions. One of the main risks is the lack of transparency associated with certain systems, particularly those based on complex or “black box” models whose internal logic is not easily explainable. This opacity can make it difficult to defend an expert opinion in court, where methodological clarity and traceability are essential.

Another critical issue is the quality of the data used to train AI algorithms. If the data is incomplete, biased, or inaccurate, the results generated by AI may be flawed or lead to incorrect conclusions. For this reason, it is essential that experts understand the technical limitations of the tools they use and verify the reliability of the input data.

From a legal and ethical perspective, considerations such as data protection, confidentiality of the analyzed information, and compliance with applicable regulations must also be taken into account. The indiscriminate use of AI without an appropriate control framework may compromise the validity of expert evidence.

Examples of AI support in expert investigations

There are numerous examples in which AI can add value to expert investigations. In the field of digital forensics, AI is used to analyze large volumes of digital logs, identify suspicious behavior patterns or detect unauthorized access to computer systems.

In financial and accounting expertise, AI can assist in fraud detection by analyzing financial transactions and identifying unusual operations or accounting inconsistencies. Similarly, in image and video examinations, algorithms make it possible to enhance file quality, compare faces or objects, and verify potential manipulations.

These examples demonstrate that, when used responsibly, AI can become a strategic ally for experts, strengthening the technical rigor of their investigations and adding greater robustness to their conclusions.

The integration of artificial intelligence into expert evidence represents a natural evolution of the field, offering significant benefits in terms of efficiency and analytical capacity. However, its use must be accompanied by a thorough understanding of its limitations and a firm commitment to transparency, ethics, and the legal framework. Only under these conditions can AI be consolidated as a reliable tool in support of justice and expert practice.