Ethiek van AI

This course aims to learn to argue about moral, social, and epistemic values that students involved with AI (computer scientists, engineers) will encounter in their professional practice. The course focuses on contemporary pressing topics such as:

• Theories of normative ethics: utilitarianism, deontology, virtue ethics. The distinction between descriptive and normative claims, epistemology and ethics, values, norms, and virtues.

• Ethical and epistemological issues in AI: identification of diverse sources of ethical and epistemological concerns in AI.

• Bias in AI: Automated-decision-making systems are polluted with different forms of bias that can be found at different levels. Here we address the different forms of bias and what can be done about it.

• Trustworthy AI: What does it mean to trust an AI system? Is there more than one way to trustworthy AI? Can we design trust? In this unit, we will address questions such as these. We will also present and discuss the two major approaches to trustworthy AI: transparency and computational reliabilism. Lights and shadows of both.

• Privacy in AI and doxing: in which various ways do we have privacy? Why is privacy so important? In what respect is privacy different from other values, such as explainability, accuracy, bias, and fairness?

Students taking the course will develop the following academic skills: reading philosophical texts, critical analysis, oral presentation, and discussion.