- Understand the main regulatory strategies and instruments concerning enhancement of technological innovation, particularly in early/experimental stages and regarding the development of robotics and AI.
- Critically evaluate the mutual dependencies between law, R&D and business in robotics/AI use cases and in specific institutional architectures (NL, EU, US, global).
- Apply key regulatory strategies and legal compliance tools in the design of technological innovations in robotics and AI.
- Analyse how non-legal regulations and principles—in the context of governance—can foster responsible innovation.
This course is about how governance and regulation, especially regulatory and legal tools, strategies and regimes, can foster (design, experimentation and implementation of) technological innovation, particularly in the development and use of AI and robotics – while at the same time addressing possible risks. The iterative relationship between technology development and regulatory development will be key to the course. Specific topics will be:
- design of legal/regulatory regimes for experimenting with new AI and robotics developments and uses (such as in sequentially up-scaling).
- design of ‘future proof regulation’, that allows more liberties to innovation in AI and robotics (such as a go-ahead without ex ante permissions and the use of private regulation).
- possibilities for ‘designing-in’ regulation or techno-regulation.
- possibilities for developing a tool to link robotics/drones/AI impact assessment to regulatory impact assessment.
- robots regulating humans and other robots.
The regulatory and legal implications of different subcategories of robotic systems will be explicitly addressed, while also considering the wider context of artificial intelligence. Automated vehicles, care-robots, drones, swarms, as well as AI components embedded in larger high-tech systems will be included in the discussion. Lastly, we aim to raise deeper issues of human-machine interaction, particularly along the continuum of ethics, governance, law, and regulation.
Assessment is performed via two assignments with equal weight. Firstly, an individual report that serves as the exploratory ground for the student to develop a critical and operational understanding of how legal and governance problems and stances relate to the R&D as well as societal deployment of AI and robotic systems. Secondly, a group assignment that aims to apply a concrete legal or regulatory tool into the redesign of a chosen robotic or AI technology.