INFO381-2017: Graduate course on AI Ethics
@ University of Bergen

INFO381-2017 was organised in eight, six hour long sessions. This is the standard organisation form for the Masters in Information Science courses. Each session was structured as a sequence of lectures, discussions and group work. The learning outcomes of the course and syllabus were adjusted in this regard to reflect the students' now existing knowledge in AI:
Knowledge.

  • Identify and describe the basic principles of moral philosophy, interpret, explain and extend the need for, and challenges of, automating moral reasoning.
  • Experience the entire process of research in machine ethics from the inception of an idea, analysis of research work, refining a research question, planing and executing group work and reporting on the work in the form of a scientific report.
Skills.
  • Appraise the ethical aspects of AI problems.
  • Discern different moral theories and values when considering ethical impact of AI applications.
General competence.
  • Reading and explaining scientific articles.
  • Research project management.
  • Scientific reporting.

Organisation

  • 1. Introduction to machine ethics
    Material: Chapters 1, 26, 27 from Vaughn (2014); Moor(2006); Wallach u. a. (2008), Bonnefon u. a.(2016); Winfield u. a. (2014); Chapters 1 and 2 from Russell und Norvig (2015).
  • 2. Introduction to moral philosophy
    Material: Chapters 4,6,7 and 12 from Vaughn (2014).
  • 3. Bottom-up approach with an introduction to machine learning
    Material: Anderson and Anderson (2008), Chapters 18, 19, 20, 21 from Russell und Norvig (2015)
  • 4. Top-down approach with an introduction to agent verification
    Material: Dennis u. a. (2016), Chapter 7 from Russell undNorvig (2015)
  • 5. Computers do what you ask them to, not what you want them to. Limitations of top-down and bottom-up approaches
    Material: Lecture notes
  • 6. Context and impact of machine ethics - cultural implication, military vs civilian applications, algorithms vs. embodied intelligent systems
    Material: Bolukbasi u. a. (2016), Sharkey and Sharkey (2012), Arkin (2008)
  • 7. Deliberately making unethical machines
    Material: Pistono und Yampolskiy (2016)
  • 8. Research methodology
    Material: Lecture notes
  • References