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The use of Artificial Intelligence (AI) technology is growing across different spheres of our everyday life. While the technology is rapidly shifting how we choose to function, communicate and evolve as a society, it brings a whole host of legal and ethical questions surrounding its use into fore. Ultimately, like every other technology, it is the use and implementation that determines whether it becomes a force for good or presents significant dangers to our society.
This course seeks to make students aware of the critical ethical and societal questions posed by AI and the regulatory responses that are emerging within and outside the EU. It will delve into issues surrounding data privacy and surveillance to discrimination and justice. By appreciating perspectives of the different stakeholders in application and regulation of AI, the students will be able to understand relevant nuances to the current contemporary debates concerning deployment of this technology. Through case studies of the AI-led innovations and the ethical dilemmas, it will set the foundations for developing an insight into different biases and risks these technologies present. Students will be able to evaluate the principles of responsible AI and their practical implications to what the technology is and can be in the future.
Participants will have:
an insight into theoretical and regulatory foundations of artificial intelligence, with specific emphasis on EU AI regulation.
ability to evaluate the unique opportunities and challenges associated with deployment of AI systems in multiple domains of the society.
understanding of different biases and risks associated with the use of AI and the ability to analyse the strengths and weaknesses of possible mitigation strategies.
understanding of the discourse concerning principles of responsible AI such as fairness, transparency, accountability, inclusivity and what they mean in practice.
case studies highlighting uses and misuses of AI, their implications on the society and for the field of human rights.
On the right-hand side of the programme front page of the E-Prospectus you will find a link to the online timetables.
Mode of Instruction
Lectures, seminars, exercises, class discussion
The grade of this assignment is composed of four elements:
a. identification of a societal or sectoral problem associated with the use of AI (10% proposal + 10% presentation)
b. case analysis or short paper developing a potential mitigation strategy for addressing the selected problem (50% report + 30% presentation)
Only assessments with the weight of 30% and lower are compensable. This means that one does not have to pass an assessment if it weighs 30% or less in order to pass the course, if the average of all assessments combined is at least a 5.50. In addition, assignments weighing up to and including 30% cannot be re-taken, meaning that if one failed an assessment of 30% or less one is not allowed to redo it and that assessment must be compensated by the other assessment(s).
The re-sit will take the same form.
Compulsory literature and literature for further consultation will be announced via Brighstpace
No registration is required for lectures and exams.
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