Introduction to Responsible AI Engineering

Introduction to AI and Responsible AI Engineering (hereafter Responsible AI for short) introduces students to the history of AI development and how it got entrenched in society, as well as to the range of ethical issues that tend to arise during the development, design and application of AI in society. The course does not require any prior knowledge in philosophy or ethics of technology. All the required reading material will be provided on Brightspace prior to the course.

Upon completion of the course, you will be able to:

• explain the main philosophical differences between strong and weak AI;

• discuss briefly the historical development of AI;

• explain a range of views on the relationship between AI developments and society;

• identify ethical features of specific AI-based technologies;

• apply philosophical concepts and approaches to the current debate surrounding responsible AI;

• formulate a position on the ethical issues at stake in current AI applications regarding responsible design ideas;

• write an academic paper with a concise research question, a clear structure, a justified choice of a theoretical framework, reference to academic literature and a consistent line of argumentation;

• reflect on the structure and academic quality of the work of own peers in a deep and specific manner.

Weekly quizzes:

To pass on to the next weeks material on Brightspace, students will need to complete a multiple-choice quiz. They will be quizzed on the topic for that week based on the mandatory readings and the lecture material for that week. The quiz has an unlimited number of attempts and is not timed, with immediate results. Students need to get all of the answers correct to be able to access the materials for the next week (e.g., lecture and readings). To be able to access the materials of Week 1, students will need to read the Course manual (to be uploaded on Brigtspace at least one week before the course start date) and answer several questions on its content.

Lectures:

• Lectures will be available in a pre-recorded format on Brightspace, released in a timed weekly manner. Students are expected to watch the lecture materials before the lecture discussions.

• Lectures discussions will take place weekly, in-person on campus, where the lecturer answers student questions about the lecture material and readings, and where students conduct in-depth case study analysis based on the lecture materials.

• Students are expected to attend one session from each tutorial on campus in person (i.e. five sessions to attend in total). Each tutorial will have a different AI-related case study to analyze in the form of debate, workshop, stakeholder group, etc. on broad spectrum of ethical issues.

Tutorials:

Students must attend 4 on-campus tutorials (A, B, C, and D) during the course to complete the course. During each tutorial, students will complete a reflective exercise (e.g. a debate) and produce an analytic piece (e.g. a presentation) on a specific case of implementing AI systems in society. A tutorial session is for max. 20 students, so one tutorial is repeated 6 times across two weeks to make sure students can have meaningful discussions in class. To recap, students are expected to attend 4 unique tutorial sessions on campus in person, and attendance is mandatory to successfully pass the course.

Final paper

Students will reflect in a written form on any societal application of the AI technology (3500-4000 words), in groups of 4 people. In the paper, students are asked to identify a specific ethical issue raised by that technology, evaluate it, and make responsible engineering recommendations on how to develop or apply their technology in an ethical way. The final submission will be preceded by several checkpoints (e.g., paper proposal, draft, and peer-review). In this way, the students get feedback on the assignment throughout the course. Guidelines for the Proposal, Full Draft, and Peer Reviews will be posted on Brightspace, as well as information about writing papers on ethics topics in general. In addition, students will have an Academic Writing workshop. The group paper will count for 85% of the overall course grade, and the Peer Review assignment will count for the individual 15% of the grade. The final paper will be submitted in Week 10.

Grade calculation:

• Mandatory attendance in tutorials and short formative assignments (quizzes and reflective tutorial posts),

• Final paper (100%): 15% individual peer review assignment + 85% group Final paper. Students have to pass each of these assignments with a minimum grade of 6.0. Grades will be rounded to 0.5. So failing a peer review but passing a group essay, or vice versa, will mean a student would need to do a repair for that grade component in the next quarter.

Disclaimer: information may change depending on unforeseen circumstances or measures (see: TER Art 29, sub 4)