Regulations of Autonomous Systems

Data is displayed for academic year: 2023./2024.

Lecturers

Asst. Prof.
Fausto Miguel Pascoal Ferreira

Course Description

The main goal of this course is to provide an overview of the current regulatory issues and efforts related to autonomous systems (robotics and Artificial Intelligence) through a technology-informed viewpoint. Course objectives are for the students to learn about the need for regulations and the existing regulations, discuss their limitations, understand non-legal approaches such as codes of conduct and guidelines and to get an unique technology-informed perspective. Students will be able to understand how to devise/adapt regulations based on both existing laws/regulations and the technological state of the art.

Study Programmes

University graduate
[FER3-EN] Control Systems and Robotics - profile
Transversal Courses (2. semester)
[FER3-EN] Data Science - profile
Transversal Courses (2. semester)
[FER3-EN] Electrical Power Engineering - profile
Transversal Courses (2. semester)

Learning Outcomes

  1. Summarize the novel regulatory issues raised by autonomous systems
  2. Analyze specific applications of robots and Artificial Intelligence, and identify any regulatory concerns they may raise including liability and safety issues
  3. Assemble in-depth knowledge of the state of the art in regulating robot technology and Artificial Intelligence and feel confident to suggest improvements and revisions
  4. Identify the scope and limits of legal regulation of autonomous systems, and appreciate the non-legal approaches such as industrial standards, self-regulation and insurance regimes
  5. Develop a technology-informed perspective on regulation of robotics

Forms of Teaching

Lectures

Lectures are held every week (2h per week)

Seminars and workshops

Students will be divided into groups to analyze case studies, propose solutions and present them to other groups of students through a public presentation.

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Seminar/Project 50 % 30 % 50 % 30 %
Mid Term Exam: Written 0 % 35 % 0 %
Final Exam: Written 0 % 35 %
Exam: Written 50 % 70 %

Week by Week Schedule

  1. Introduction, overview of the course and motivation
  2. Three Laws of Asimov, early efforts and overview of regulatory approaches
  3. Regulatory issues raised by autonomous systems: responsibility, liability, safety, security
  4. International and EU efforts on regulation of robotics and Artificial Intelligence
  5. Industrial robots: regulation and standardization, new issues with co-bots
  6. Service/personal robots: regulation and issues
  7. Seminar presentations of case studies by students
  8. Mid-term exam
  9. Autonomous cars regulation issues and current efforts
  10. Maritime robotics regulations and maritime law
  11. Aerial drones regulations
  12. Artificial Intelligence regulations
  13. Future of regulation: technology-informed approaches
  14. Seminar presentations of case studies by students
  15. Final exam

Literature

Ryan Calo, A Michael Froomkin, Ian Kerr (2016.), Robot Law (selected chapters), Edward Elgar Publishing
Jacob Turner (2019.), Robot Rules (selected chapters), Palgrave Macmillan Cham
European Parliament (2017.), European Parliament resolution of 16 February 2017 with recommendations to the Commission on Civil Law Rules on Robotics (2015/2103(INL)),
European Commission (2021.), Proposal for a Regulation laying down harmonized rules on artificial intelligence,
Palmerini, E., Bertolini, A., Battaglia, F., Koops, BJ, Carnevale, A., & Salvini, P. (2016.), RoboLaw: Towards a European framework for robotics regulation. Robotics and Autonomous Systems, Elsevier
Salvini, P. (2015.), On Ethical, Legal and Social Issues of Care Robots, Springer, Cham
Asaro, P. (2007.), Robots and responsibility from a legal perspective, IEEE

For students

General

ID 255022
  Summer semester
2 ECTS
L3 English Level
L1 e-Learning
30 Lectures
0 Seminar
0 Exercises
0 Laboratory exercises
0 Project laboratory
0 Physical education excercises

Grading System

90 Excellent
75 Very Good
60 Good
50 Sufficient

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