1. The Use of AI in Judicial Systems: Threats and Possible Solutions
The example of Quantitative Legal Prediction and Judicial Independence
Prof. Serena Quattrocolo – University of Piemonte Orientale – Ital-IA,

2. On Dec. 4th 2018 the CEPEJ (body of the Council of Europe focusing on the effectiveness of justice in Europe) released the Charter
The Charter is a soft-law instrument (is not binding, neither for rulers nor for stakeholders)
The Charter is a canvas for legislation and private policies
The Charter may become a Convention in the future
The European Ethical Charter for the Use of Artificial Intelligence in Judicial Systems and their Environments
Prof. Serena Quattrocolo – University of Piemonte Orientale – Ital-IA,

3. 1 Principle of respect for fundamental rights: ensure that the design and implementation of artificial intelligence tools and services are compatible with fundamental rights.
2 Principle of non-discrimination: specifically prevent the development or intensification of any discrimination between individuals or groups of individuals.
3 Principle of quality and security: with regard to the process- ing of judicial decisions and data, use certified sources and intangible data with models elaborated in a multi-discipli- nary manner, in a secure technological environment.
4. Principle of transparency, impartiality and fairness: make data processing methods accessible and understandable, authorise external audits.
5. Principle “under user control”: preclude a prescriptive approach and ensure that users are informed actors and in control of the choices made.
5 PRINCIPLES
Prof. Serena Quattrocolo – University of Piemonte Orientale – Ital-IA,

4. 1 MAIN RULE: MULTI- DISCIPLINARITY
ALL 5 PRINCIPLES UNDERPIN MULTI- DISCIPLINARITY IN RESEARCH- AND WORKING-TEAMS
1 MAIN RULE: MULTI- DISCIPLINARITY
Prof. Serena Quattrocolo – University of Piemonte Orientale – Ital-IA,

5. CRUCIAL IMPACT ON THE BASIC PILLARS OF A JUDICIAL SYSTEM
QUANTITATIVE LEGAL PREDICTION
based on open data allowed by many jurisdictions,
Quantitative Legal Prediction is aimed to
FORESEE THE OUTCOME OF FUTURE JUDICIAL DECISIONS
This can appear a neutral or even positive outcome, for an intriguing exercise in L.A.I.:
helps law-firms in selecting cases
suggests how to focus resources in the best way
points out in which jurisdiction the applicant can have better chances
However, this can have
CRUCIAL IMPACT ON THE BASIC PILLARS OF A JUDICIAL SYSTEM
A BASIC EXAMPLE
Prof. Serena Quattrocolo – University of Piemonte Orientale – Ital-IA,

6. PREDICTION VS. INDEPENDENCE
EUROPEAN AND CIVIL-LAW JURISDICTION ARE NOT BASED ON THE RULE ‘STARE DECISIS’, I.E. THE PRECEDENT IS BINDING
QLP IS EXCLUSIVLEY BASE ON PRECEDENTS
QLP IS AIMED TO PREDICT THE OUTCOME OF A DECISION BEFORE IT IS DEIVERED BY THE COURT
FACING THE PREDICTION, WILL THE COURT BE INDEPENDENT ENOUGH TO IGNORE THE PREDICTION?
IGNORING THE PREDICTION MAY BECOME A SOURCE OF CIVIL AND DISCIPLINARY LIABILITY FOR JUDICIARY?
IS PREDICTION A VALUE OR A THREAT?
PREDICTION VS. INDEPENDENCE
Prof. Serena Quattrocolo – University of Piemonte Orientale – Ital-IA,

7. AT THE TIME BEING:
THEORETICAL FRAMEWORK FOR A LEGAL DISCUSSION ON THE USE OF AI, ESPECIALLY IN CRIMINAL JUSTICE
TRYING TO POINT OUT THE RISKS
REFLECTING UPON THE EXISTING FUNADAMENTAL RIGHTS
PROMOTING AWARENESS IN COMPUTER SCIENTISTS
ESTABLISHING MINIMUM STANDARDS OF MULTI- DISCIPLINARITY
MY RESEARCH
Prof. Serena Quattrocolo – University of Piemonte Orientale – Ital-IA,