A better understanding of the issues related to the use of AI within companies and organisations, as well as to the structuring of AI projects.
Knowledge of the main legal rules applicable to the creation of AI-based tools and to the use of AI tools.
A methodical approach to analysing and managing the legal risks associated with AI projects.
Subject-specific skills:
– identify the relevant legal and other (organisational, ethical) issues arising in the development of an AI-based project, depending on the nature of the project and the tools envisaged;
– understand the challenges and impacts of a technological project on the functioning and processes of an organisation and integrate these aspects into the legal analysis;
– combine the available instruments in order to optimise legal risk management;
– revisit legal issues by fully taking into account their transformation in the digital world;
– apply theoretical knowledge to practical situations in a digital context.
Soft skills:
– work independently by engaging in a flipped-classroom approach based on practical cases;
– develop investigative skills in the field, using any available tool (including AI) to better identify issues and inform legal analysis;
– work and reflect as a group, and collectively endorse responsibility for performed work and taken positions ;
– establish links between legal reasoning and non-legal reasoning;
– develop personal reflections on specific practical situations in light of known legal principles;
– present personal opinions and argue in support of one’s point of view;
The course is divided into five three-hour modules, following a similar teaching format:
– Brief presentation of the scenario under consideration
– Group work (depending on the number of students), with each group assigned a defined role (one of the stakeholders involved or one of the issues under consideration)
– Presentation by each group of its analysis + Q&A
– Synthesis/restructuring presentation
The selected topics may vary depending on current developments, in order to reflect practice and recent developments in AI as closely as possible.
Proposed topics (to be confirmed)
AI governance within organisations/companies:
From an organisation’s perspective, the discussion will focus on the questions “why use AI?” and “how should AI be used?”. These questions are essential preliminary steps, whether the objective is to use AI deliberately or simply to monitor how it is used by employees (and avoid “shadow AI”).
Groups will analyse these questions from the perspective of the various stakeholders involved: management, employees and service recipients.
The purpose of the exercise will be to familiarise students with the necessary coordination of viewpoints in order to reach a governance consensus within the organisation.
Issues involved in selecting or designing an AI solution:
The decision to implement AI solutions within an organisation or to place AI solutions on the market raises a range of questions with significant legal implications.
Based on an AI project scenario, the exercise will involve analysing the risks raised by the project, considering the different roles involved in this type of project. Comparing these viewpoints will highlight the importance of a comprehensive analysis of the project’s risks and challenges. The exercise will also highlight legal and organisational risk-management strategies.
Compliance with the AI Regulation (AI Act)
Following an introduction to the main features and underlying logic of the AI Act, students will be divided into groups, each focusing on a specific issue concerning the application of the AI Act (methodological approach).
The exercise aims to focus on the implementation methodology, since the risk-based approach advocated by the AI Act effectively places a significant part of the legal analysis on each entity developing an AI project, depending on its role and the nature of the project.
Assessment of legal compliance: practical implementation tools
Whether directly (through explicit obligations) or indirectly (through its risk-based approach, which requires every actor to be able to justify its choices and the measures taken), the AI Act imposes specific documentation requirements on organisations depending on their role in the contractual chain relating to the AI system.
Preparing appropriate documentation may require, in some cases, specific skills and knowledge concerning the tools used and, in others, a sound understanding of the environment in which those tools are used. This distribution of the knowledge and expertise required leads, in practice, to a distribution of roles. The legal texts merely outline this allocation.
The exercise will aim to identify, for each stakeholder involved, the points requiring attention in order to ensure that they are able to comply with the applicable legal obligations, and to develop strategies for allocating risks and responsibilities within the AI project chain.
Partners in an AI project
Implementing an AI solution requires the involvement of various actors and partners, both internal and external to the organisation, who will provide the skills and resources necessary to ensure that the AI solution is aligned with the organisation’s objectives.
For example, AI project practice shows the emergence of the role of the integrator. The exercise will aim to identify the key issues in the contractual relationship between the different actors in an AI project (developer, user, external service provider, integrator, etc.). Based on the risks identified in the scenario under consideration, the objective will be to propose risk-management approaches acceptable to all stakeholders concerned.
The course requires active participation from students.
It will be delivered in person. It might be delivered remotely in case of need.
A flipped-classroom approach may be used. On such occasions, students will be invited to independently review the sources identified by the lecturers.
Wherever possible, this work will be carried out during class sessions. However, preparatory work may be required for certain sessions in order to enable students to participate actively in discussions that may take place during the class.
In addition, the course may involve case presentations or exercises by students.
More generally, the course will lend itself to independent investigation by students.
Subject to changes depending on the circumstances, the assessment will be based solely on the quality of students’ participation in the various sessions (participation in discussions, presentations and assignments submitted at the end of the sessions), with no separate examination.
In order to place students within the context of a project within an organisation, collective dynamics will be prioritised. Each group will therefore receive a single grade. However, the lecturer may make adjustments where certain members of a group have distinguished themselves. The main emphasis will nevertheless remain on the collective dynamic (students work together and collectively assume responsibility for the outcome produced, independently from the individual inputs to the result).
During the sessions, students will be able to access any resources they consider useful for solving the cases submitted to them. The use of AI tools is naturally permitted.
| Training | Block | Credits | Mandatory |
|---|---|---|---|
| Advanced Master in Digital Law | 1 | 2 | Yes |