The evolution of scientific evidence between artificial intelligence and legal validity

The use of AI is transforming the production and legal validity of scientific evidence in the forensic context, raising critical questions regarding admissibility in court. While traditional forms of scientific evidence rely on methodologies already validated and accepted by the scientific community, AI systems introduce unprecedented challenges in terms of explainability.

We conducted a search on PubMed using the keywords "artificial intelligence scientific proof" over the past 10 years. Applying the relevant filters, we obtained 243 results. The aim of this research is to analyze the reliability of AI in judicial proceedings and the potential admissibility of scientific evidence, by comparing major legal systems. This study examines the impact of AI with particular focus on compliance standards. For completeness, we also carried out additional hand-searching.

The investigation reveals that the use of AI in the forensic field offers undeniable advantages. However, there are still several issues to address, primarily associated with the "black box" nature of AI. In this international context, there are also regulatory gaps between the EU system and the US approach, which is already utilizing such systems with flexible but controversial criteria.

The integration of AI into legal processes requires a balance between innovation and procedural safeguards. The U.S. Daubert Standard provides a framework for assessing the scientific reliability of algorithmic evidence but needs adaptation to address the challenges posed by AI. The future challenge lies in reconciling technological advancement with the principles of procedural fairness, ensuring that AI does not become an "incontestable" form of evidence due to its complex nature.