ArtificiaI Intelligence in Society

Content

The main objectives of this minor are for you to:
1. understand the technological side of AI
2. familiarise yourself with different viewpoints on AI
3. develop a critical attitude to AI in relation to society

Artificial Intelligence is seen as potentially both beneficial and detrimental to society. Behind the hype and hopes for these technologies is a recognition that AI is transforming the world we live in. The reliance on AI raises a number of possible opportunities and concerns in relation to society, which will be explored in this minor.

While AI's applications are technical, they are also profoundly social. As such the broadening of perspectives from the engineering of AI to a holistic approach is crucial to understanding both AI and our changing society. This minor therefore incorporates discussions from multiple disciplines, touching on for example ethics, law, communication and culture. It will give you the vocabulary, knowledge and various perspectives needed to grasp and analyse AI in relation to society.

Learning objectives

After completing the minor, you should have a critical comprehension of:

• basic AI principles (in the context of society)
• current AI technological development
• multidisciplinary perspectives on AI in society
• the integration of the role of AI in your own disciplinary field

These outcomes will be realised via an educational approach that focuses on personal development, space for academic growth and lectures from academics active in various disciplines.

You will be confronted with the variety of disciplinary perspectives on AI by activating lectures, exposure to the basic building blocks of AI development and self-study materials. This learning process will be continued and reinforced by the group work that is embedded in the programme of the minor. The groups will by definition show a multidisciplinary composition. You will be coached particularly in the discovery of unfamiliar perspectives and the final assessment will be scored on the level of discipline combination/integration. Moreover, you will be expected to reach a foundational level of insight into AI deployment in areas within your field of study, but also basic level of insight into other areas.

Special aspects

Prior knowledge on and experience in the field of AI is not required, but a critical and creative outlook on the subject and on one’s own discipline is encouraged.

Group work represents an important component of this minor. You will be interacting with your peers on a continuous basis throughout.

Attendance is mandatory.

Overview content per week

Week 0: Introduction to the course

• How will this course work: timeline, expectations, case-based learning, skills needed to be successful in this course, importance of diverse perspectives and different knowledge acquisition processes.

Week 1:

• Overview / intro on AI
• Exposure and Training in AI modular building blocks
• Project-group meeting: Exploration of AI-related questions

Week 2 & 3:

• Case study from experts
• Exposure and Training in AI modular building blocks
• Project-group meeting: Intro to your own question / map relevant stakeholders
• Coaching

Week 4 & 5:

• Case study from experts
• Project-group meeting: Research and Define problem / question
• Coaching

Week 6 & 7:

• Student groups bring forward their own case
• Project-group meeting: Analysis and reformulate problem / question
• Coaching

Week 8 & 9:

• Seminar: Student groups bring forward their own case
• Project-group meeting: Redefine / answer the problem
• Coaching

Week 10:

• Present your inquiry to the group
• Complete your assessment

This is a provisional outline. A more detailed schedule will be provided prior to the start of the minor.

Teaching methods

To be determined

Teaching materials 

• Learning materials for example include plug and play games, case studies, literature and videos.

Examination

Method of examination

To be determined

Composition of final grade

The final grade consists of two parts. 30% Of the grade will revolve around the group work and group performance. The remaining 70% of the grade will be an individual grade. It will revolve around an essay whereby students will describe their disciplinary and multidisciplinary understanding of the influence of AI in society.

 Feedback method

In addition to feedback on graded assignments you will receive feedback from peers and coaches throughout the course.

Contact information

Michele Murgia

michele.murgia@eur.nl

T +31640937786