E-learning
We developed a free e-learning course based on the handbooks and conference material of the JuLIA project. The course consists of four modules which will each take around 3 hours to complete.
Who is this course for?
Judges, lawyers and law-makers. No prior knowledge of Artificial Intelligence is required. For more advanced learners it can serve as a reference work. It discusses legal issues of the use of AI in the fields of civil and criminal proceedings, health care, and consumer protection. It will give learners a theoretical foundation combined with practical relevance.
We designed the course under supervision of the office for Massive Open Online Courses of the University of Groningen on the e-learning platform FutureLearn.
To access the course click on the following link:
You will be asked to provide a name, an email address and a password to set up a FutureLearn account. FutureLearn will then send an email and ask you to confirm the email address. No other actions are required.
Topics and learning outcomes
Course scope and objectives
The course covers the following topics:
- Overview of AI in decision-making
- Risks and challenges
- Regulatory frameworks
- Artificial Intelligence in justice systems
- Fair trial and transparency
- AI applications in health
- Regulations and liability in the health sector
- Consumer rights and Automated Decision Making
- Legal remedies
- Ethical concerns
After completing this course, learners should be able to:
- interpret different definitions of AI and AI systems
- describe the relevant EU legal documents, provisions on AI in the Medical Device Regulation
- explain the recurring risks and challenges of the use of AI
- assess the expected advantages and disadvantages of the use of AI in legal decision making, including transparency and due process
- assess the impact of AI in medicine on the principle of informed consent and liability for medical errors
- describe examples of practical applications and existing case law
- analyse cases
We address these topics and provide the materials needed for learners to achieve the learning outcomes in four different modules.
The four modules
Structure of the course
Each of the four modules will take approximately 3 hours to complete. Here are short descriptions of the modules provided to the learners in the course introduction.
Module 1
Crash course in Artificial Intelligence and Automated Decision Making
You will familiarise yourself with definitions of AI, develop a basic understanding of how AI works, reflect on the examples of AI in practice, acquire an understanding of the recurring risks of the use of AI, and have a grasp of the relevant EU legal documents.
The learning outcomes for module 1 are to:
- recall and interpret different definitions of AI
- differentiate between different AI systems
- name the relevant EU legal documents
- summarise and explain the recurring risks and challenges of the use of AI
- give examples of practical applications and existing case law
- analyse and solve hypothetical cases
Module 2
Automated decision making in civil and criminal proceedings
Module two deals with Automated Decision Making in Civil and Criminal Proceedings. We will discuss the use of AI in justice systems in general, and more specifically, its meaning for having a fair and transparent trial.
Learning outcomes of Module 2 are:
- explain what predictive justice is and how it works
- describe the limits of legal search engines and decision support systems
- describe and illustrate legal problems of predictive justice with the help of case law
- outline problems of transparency and due process
- assess the expected advantages and disadvantages of the use of AI in legal decision making
- give examples of practical applications and existing case law
- analyse and solve hypothetical cases
Module 3
Legal aspects of the use of AI in health care
Module three presents the legal aspects of the use of AI in health care. It looks at automated decision making in the health sector.
Learning outcomes of Module 3 are:
- describe and compare the use of AI in clinical decision support, diagnostics, and patient management
- identify the relevant provisions on AI in the Medical Device Regulation
- assess the impact of AI in medicine on the principle of informed consent
- analyse issues of liability for medical errors
- give examples of practical applications and existing case law
- analyse and solve hypothetical cases
Module 4
AI and automated decision making and consumer protection
Learning outcomes of Module 4 are:
- describe the role of AI in price discrimination, unfair contractual terms, and deceptive online practices
- explain the EU legal framework concerning AI and consumer protection
- analyse possibilities for legal remedies
- identify dangers of algorithmic manipulation
- outline problems of transparency
- give examples of practical applications and existing case law
- analyse and solve hypothetical cases
Elements of the e-learning course
Learning format
Each module is structured quite similarly and consists of texts, hypothetical case studies, videos, conclusions containing further material, and quizzes.
To access the course click on the following link: