Ethical, Legal, Societal and Economical Aspects of AI, 3 credits

This is a brief overview of the content of the course Ethical, Legal, Societal and Economical Aspects of AI. Further information will be given later on.

Module 1 – Responsible Design of Intelligent Systems: understand Responsible AI as part of complex socio-technical systems.

Methods to take into account societal values, moral and ethical considerations, weigh the respective priorities of values held by different stakeholders in different multicultural contexts, explain its reasoning and guarantee transparency. Concrete challenges and opportunities in different application areas:

  •  Societal challenges of AI: ethical, legal, political, economical. Including also reflection on the practical and philosophical objections to ethical deliberation by machines.
  •  Introduction to Philosophical Ethics
  • Design for Values engineering method (values – norms – requirements)
  • Ethics in Practice: ethical issues (fairness, transparency, accountability, responsibility, privacy…) in healthcare, transportation, decision-making, military applications (or other concrete examples)
  • Evaluation and verification formalisms for RAI

Module 2 – Ethical Machines

Ethical Machines is about understanding, developing and evaluating ethical agency and reasoning abilities as part of the behaviour of artificial autonomous systems (such as artificial agents and robots). Understanding and applying different computational options that ensure that ethical principles are observed ‘by design’.

  • Ethics by Design: computational reasoning models for ethical deliberation
  • Explainable AI: mathematical principles and computational approaches

Module 3 – Human-agent interaction

Understand human-agent interaction as an element of dynamic activity systems based on theories about human activity (including norms and values), and how this translates into computational models useful for human-agent interaction and collaboration (e.g. intention recognition, automated understanding of human behaviour, learning based on how humans develop knowledge and skills by conducting activity).

  • Theoretical base for understanding human activity and the software agent’s roles
  • Design principles and modelling of actors, norms and activity
  • Analysis and modelling of Interaction constraints (linking to user values and preferences) and norms (linking to social, cultural, legal and physical requirements)