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Managing the legal risks of AI systems
An AI project must incorporate obligations and risks from the design stage. Identify legal and ethical issues, clarify responsibilities and structure your compliance approach. Strengthen dialogue between business teams, legal advisers and technical specialists around better-governed AI.
- Duration
- 2 days 14 hours
- Code
- IA012FR Code
Presentation
Artificial intelligence (AI) is now almost everywhere, but it raises a number of legal questions. Civil liability, data protection, algorithmic discrimination and intellectual property are all concerns when using an AI system.
This 2-day AI course provides an overview of the issues surrounding artificial intelligence, focusing on legal, ethical and strategic aspects. The first module explores AI foundations and applications across sectors. Subsequent modules develop your understanding of the legal risks of using AI, covering legal risk management, policy implementation and AI strategy development.
Finally, you will explore AI ethics and the establishment of robust governance. You will develop the skills to build a sound AI strategy aligned with your organisation's objectives. Concrete case studies and practical workshops will enable you to apply your knowledge directly to AI projects.
Objectives
By the end of this AI course, you will achieve the following learning objectives:
- Anticipate and manage risks: identify professional AI use cases, assess associated legal risks and implement a risk analysis methodology.
- Understand the regulatory and ethical framework: master AI's legal, ethical and regulatory aspects (GDPR, AI Act, etc.), drawing on the fundamental principles of transparency, non-discrimination and accountability.
- Establish effective governance: acquire best practices for robust AI governance, including algorithm registers, regular audits and employee training, and embed an ethical, responsible organisational culture.
- Develop a successful AI strategy: design an AI tools governance policy integrated into the overall business strategy, identifying opportunities for innovation and value creation while encouraging stakeholder collaboration.
- Prepare for tomorrow's challenges: identify future AI trends, including new technologies, regulations and ethical questions, and develop adaptability to maximise opportunities while minimising risks.
Program
1. AI fundamentals and challenges
- Introduction to AI: basic concepts and history.
- AI issues: opportunities, challenges and societal impacts, particularly legal, ethical and regulatory risks.
- Business applications of AI: an overview of AI in key sectors, focusing on use cases.
2. Managing AI's legal risks
- Risk identification: analysing professional AI use cases and identifying specific risks: discrimination, bias, data protection, intellectual property, liability and cybersecurity.
- Regulatory framework: overview of national and international regulations, including GDPR and the AI Act, guiding principles and best practices.
- Personal data protection: concrete measures to ensure compliance with applicable laws.
- Civil and criminal liability: analysing liability issues associated with AI use.
3. Establishing AI ethics and governance
- AI ethics: fundamental principles and issues of transparency, non-discrimination and accountability.
- Developing an AI policy: creating a tailored governance policy integrating risk management, ethics and regulatory compliance.
- Establishing a responsible organisation: roles and responsibilities, control and evaluation mechanisms.
4. Building a robust AI strategy
- Risk and opportunity analysis: a methodology for assessing the risks specific to each AI project and identifying innovation opportunities.
- Alignment with business strategy: integrating AI into the overall business strategy.
- Interdisciplinary collaboration: the importance of cooperation between legal, technical, sales and other teams.
5. Practical work
- Case studies: analysing real companies that have implemented AI strategies across sectors, with assessment of legal and regulatory risks.
- Practical workshops: developing personalised action plans to apply the learning from the course.
Audience
This course is intended for:
- legal professionals who need to understand AI's legal implications to advise clients, draft contracts and ensure regulatory compliance;
- managers who must integrate AI systems into decision-making and ensure AI projects align with business strategy;
- strategic decision-makers with a key role in defining the company's AI strategy and assessing the risks and opportunities associated with this technology;
- any professional wishing to integrate AI systems.
Prerequisites
This course requires the following prerequisites:
- an introductory understanding of artificial intelligence (AI);
- basic knowledge of civil law, contract law, intellectual property and civil liability principles;
- an introductory understanding of data protection rules and principles (GDPR).
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Quiz / multiple-choice questions
- Practical exercises
- Case study
Course highlights
• Interactive, engaging lessons.
• Legal documents suited to your context.
• Sector-specific case studies.
• Introduction to tools for assessing and implementing an AI system.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.