Handbook

In this course we will explore ethical issues for computer science, widely conceived. We will examine in detail the nature of ethical claims/moral judgements themselves, and how it is that our beliefs about their nature can affect our understanding of the ethical issues relating to computer science that we have examined so far. We will learn about ethical arguments, and how to construct and evaluate them.

We will cover normative ethics, and run test cases past real-world computer science cases. We will learn to engage critically with research ethics, as well as the relationship between ethical responsibility and AI frameworks and innovation. There will be considerable discussion of "ethics washing" - the pretence of ethical reasoning by those in positions of power for the purpose of avoiding regulation, as well as explore the related issues of trust, accountability, and privacy in our current online, informationalised world.

We will explore equity, bias and fairness in algorithmic and dataset design, as well as the ethics of AI more broadly. We will also explore the ethical ramifications of transparency and explainability - along with their attendant relationships with power, as they relate to computer science in general.