How forensic science is tackling the challenge of artificial intelligence
A meeting at the Campus Biomedico to bring together experts, universities, the technology sector and developers ahead of the conference at the Cattolica
Artificial Intelligence is rapidly making its way into all sectors of healthcare. The question is no longer whether to use it, but how to design tools that are truly capable of meeting the needs of the various disciplines. It was this realisation that prompted the “AI & Forensic Medicine” workshop, which will take place on 17 June at theCampus Bio-Medico University of Rome, marking the opening of the 47th National Congress of the Italian Society of Forensic Medicine, dedicated to scientific innovation in the discipline, which will be held from 18 to 20 June at the Catholic University of the Sacred Heart in Rome.
The aim of the meeting is clear: to bring together forensic medicine, academia, the technology sector and artificial intelligence developers to launch a process of ongoing collaboration. Not simply to build new applications for professionals, but to tackle a more ambitious challenge: designing AI systems that incorporate the methodological criteria of forensic reasoning right from the outset of their architecture. This is why we have involved an exceptional player such as IBM in the discussion.
This reflection stems from a conviction that is rooted in the finest tradition of forensic medicine: the quality of the tools must always serve the quality of judgement. The Ethics of Work Well Done, a key ethical framework, requires a continuous commitment to critical thinking, the ability to evaluate evidence, interpret complexity and make responsible decisions that affect people’s lives and the functioning of institutions.
From this perspective, Artificial Intelligence is not a shortcut to replacing professionals, but an opportunity to strengthen their critical thinking skills: artificial intelligence offers immense computational power to support human interpretative abilities.
The workshop was designed to present an initial theoretical perspective. New technologies do not alter the fundamentals of the discipline, but they can help to manage levels of complexity that often exceed traditional human analytical capabilities. From this perspective, the causal link is not abandoned, but can be interpreted, within a systemic framework, through models better able to capture the interactions between biological, clinical, organisational and social factors. Artificial Intelligence can become a tool for better understanding the complexity of reality, definitively moving away from any form of naive reductionism.
