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Bring in the algorithm! The biases of predictive models under scrutiny

Dates:
  • Wed 16 Dec 2020 16.00 - 17.30
  Add to Calendar 2020-12-16 16:00 2020-12-16 17:30 Europe/Paris Bring in the algorithm! The biases of predictive models under scrutiny

While applications resulting from AI techniques continue to diversify, the law could not escape the trend of automating decision-making. This is manifested in particular by the proposition of using predictive models issued from machine learning (ML) techniques to drive future decisions in judiciary contexts. If the use of these techniques in the courts is legitimately debated, they are on the other hand already used in law firms and, more broadly, in legal branches of private companies in order to establish or support their litigation strategies.

Described in broad terms, the ML approach consists of the analysis of a corpus of legal decisions seeking to identify what are the main characteristics that have been taken into account by the judges in settling the cases. This knowledge is then presented, in a second step, as a useful way to inform forthcoming decisions on new cases.

This talk will be the opportunity to present the concepts at the core of ML techniques before discussing how their efficiency and, more importantly, their potential biases are formally assessed by computer scientists. This will address the question of a possible discrimination in algorithmic recommendations and we will see that different formulations of what could be fair recommendations lead in fact to different biases that are irreconcilable. This will raise the question of how to regulate the use of AI approaches in such a context.

 

The event will take place via zoom and registration is mandatory.

 

Outside EUI premises - DD/MM/YYYY
  Outside EUI premises -

While applications resulting from AI techniques continue to diversify, the law could not escape the trend of automating decision-making. This is manifested in particular by the proposition of using predictive models issued from machine learning (ML) techniques to drive future decisions in judiciary contexts. If the use of these techniques in the courts is legitimately debated, they are on the other hand already used in law firms and, more broadly, in legal branches of private companies in order to establish or support their litigation strategies.

Described in broad terms, the ML approach consists of the analysis of a corpus of legal decisions seeking to identify what are the main characteristics that have been taken into account by the judges in settling the cases. This knowledge is then presented, in a second step, as a useful way to inform forthcoming decisions on new cases.

This talk will be the opportunity to present the concepts at the core of ML techniques before discussing how their efficiency and, more importantly, their potential biases are formally assessed by computer scientists. This will address the question of a possible discrimination in algorithmic recommendations and we will see that different formulations of what could be fair recommendations lead in fact to different biases that are irreconcilable. This will raise the question of how to regulate the use of AI approaches in such a context.

 

The event will take place via zoom and registration is mandatory.

 


Location:
Outside EUI premises -

Affiliation:
Department of Law

Type:
Online Debate

Contact:
Claudia de Concini (EUI - Law) - Send a mail

Organiser:
Prof. Urska Sadl (EUI - Law Department)
Prof. Giovanni Sartor (EUI - Law Department)
Prof. Henrik Palmer Olsen (University of Copenhagen)

Speaker:
Prof. Fabien Tarissan (CNRS, Paris, Computer Science)

Discussant:
Dr. Raphaële Mathilde V Xenidis (iCourts, Copenhagen)
Dr. Francesca Lagioia (Department of Law, EUI)
 

Page last updated on 18 August 2017