URL study guide
https://tue.osiris-student.nl/onderwijscatalogus/extern/cursus?cursuscode=JBL110&collegejaar=2026&taal=enDescription
The course will run from April to June, with two hour sessions being held every Tuesday and Thursday(except during public holidays & vacation days). Each week students attend a lecture and go through the assigned reading material, which will be followed by a two hour active case discussion (ACD) session. Students will discuss the material covered in lecture and apply the material to practical case studies during these ACD sessions. Please note that the readings are mandatory.For the specific dates, times and location of the lectures, please refer to the Syllabus in Canvas.
The instructional modes of this course are:
Lectures: in-person
Active case discussions
The course consists of 5 modules with 7 lectures and 6 ACDs in total. The modules are divided as follows:
Module 1: Introduction: How social, economic and ethical considerations impact innovation regulation and the choice of regulatory strategies, including risk-based strategies (lecture 1 and 2 /ACD 1 and 2)
Module 2: Intellectual property rights and data(base) protection (lecture 3/ACD 3)
Module 3: Data and regulation of competition (lecture 4/ACD 4)
Module 4: AI and data regulation(lecture 5/ACD 5)
Module 5: Health data sharing regulation(lecture 6/ACD 6)
Module 6: Innovation and regulation in the area of finance and sustainability (lecture 7/ACD 7)
Recap (lecture 8)
Each module consists of a lecture and an ACD. ACDs are intended to discuss the study material of that lecture in a more collective and "hands-on" manner, which is why you will most likely be divided into groups. The working groups will cover specific elements of the module topic, especially with regards to real-life examples and occurrences.
The final lecture serves as a recap of the entire course and provides students with an opportunity to ask questions on the covered topics.
Lecture topics:
The course will discuss the following topics:
What is innovation?
What is responsible innovation?
What is regulation and why is it necessary?
What is data driven innovation?
The role of regulation in stimulating or facilitating innovation.
The role of regulation in limiting or steering innovation to protect core social values, such as privacy and sustainability
Regulatory strategies, including risk-based strategies.
The regulatory challenges created by data-driven innovations.
Examination
There will be a graded assignment after each of the six modules. The highest four grades received by the student will be taken be calculate the overall Assignment Grade, which amounts to 40% of the overall Final Grade. Please note that means that each assignment will count for 1/4th of the overall Assignment Grade.
At the end of the course there will be a written exam. The Exam Grade will account for the remaining 60% of the Final Grade. This written exam will consist of open-ended questions from all of the modules.
In order to be eligible to sit for the written exam, students must have submitted at least three assignments. Blank submissions will not be accepted as an attempt. If a student has only submitted three assignments, the Assignment Grade will be calculated as a sume of the grades for the three submitted assignments divided by four.
A resit opportunity is available for the written exam. The resit will amount to 60% of the Final Grade. The remaining 40% will consist of the assignment grades.
Objectives
Course descriptionThis course explores the interaction between innovation and regulation in the field of data science. It draws mainly on economics theories of regulation and innovation and focuses on data driven innovation. It discusses theories of regulation and innovation in general and applies them in specific fields, such as agriculture and energy.
This course builds on the introductory course on Law and Data Science, and it assumes that students have basic knowledge of the legal concepts introduced in that course.
Course objectives
Upon completion of this course, students will have obtained a basic understanding of the fundamental theories and principles underpinning the regulation of innovation, and the interplay between regulation and innovation in general, and innovation driven by (big) data in particular. They will be able to:
1) identify real-life examples of (data driven) innovation and evaluate the potential social and economic impact of such innovation;
2) identify and understand the role of social,economic and ethical considerations as grounds for regulation of innovative technologies;
3) identify different types of regulatory strategies and regimes applicable to innovation regulation, including risk-based strategies;
4) rely on their knowledge of regulatory regimes to inform decisions in engineering design;
5) recognize the importance of regulatory regimes for innovation and engineering design more generally;
6) apply principles of responsible innovation in engineering design.