Justice By Algorithm

Learning objectives
The course aims to provide an initial overview of the impact of AI technologies on different trial systems. Starting by familiarizing students with the methodology of judicial evaluation- as differently applied in criminal and civil trials (e.g., standard of proof, rule of judgment)- the course will focus on the rules of evidence (admission, taking, evaluation) and on the issue of judicial problem solving. This analysis will pave the way for the central part of the course, which will focus on the impact of AI on the relationship between trial, evidence and judicial decision-making, providing the legislative framework established primarily by the European law on AI. In this context, it will analyze the role that AI will play with regard to the criteria to be adopted in the evaluation of the evidence gathered to affirm the so-called "judicial truth" (i.e., the test of quaestio facti) and the interpretation of legislative provisions as true (i.e., right) to resolve the quaestio iuris.
The ultimate goal, then, will be to test whether new technologies based on deep learning systems can replace human intelligence in judicial decision-making.

Expected learning outcomes
Students will gain to acquire a full understanding of the theoretical notions presented and master basic knowledge of the following topics:
- scope and methodology of judicial assessment;
- rules of evidence;
- quaestio facti and quaestio iuris (inductive and deductive methods);
- data analysis and judicial evaluation.