Course Catalogue

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In this course, students will evaluate existing frameworks and propose new interventions in the Philosophy of A.I. Representative issues explored will be in ethics, epistemology, and language. On the ethical front, students will investigate, for example, algorithmic bias, the moral alignment problem for AI, the functions and norms of AI, etc. On the epistemological front, students will investigate, for example, whether and how we can gain knowledge by relying on artificial neural networks, and to what extent outsourcing cognitive tasks to AI is epistemologically advantageous. The course may also discuss different theories of language production by certain types of AI such as Large Language Models. The course will investigate whether the tools used to explain human linguistic behaviour can also be applied to these systems. The results of this research will help students investigate questions about whether and how the AI's work is explainable.

16x1hr lectures; 4x1hr seminars over 10 weeks.

Standard entry to Masters at College Level

None.

None.

The standard assessments for this course are:

■ 2 x Essay (2500 words) - 100%

If required, for instance where a disability prevents a student from undertaking a specific method of assessment, the following alternatives are available:

■ There is no alternative to the essays, but flexible deadlines can be offered as reasonable adjustments (students should follow the usual process for extensions)

Further reasonable adjustments may be provided where necessary. Students are encouraged to consult with the course convenor.

This course aims to:

■ Provide students with the opportunity to develop their own argumentative interventions in core debates in philosophy of AI.

■ Critically explore the place of new technologies in our cognitive lives, and the ethical and epistemological ramifications of these technologies, and their connection with human language.

■ Empower students to exercise and improve their critical and analytical skills in synthesising philosophical and empirical research in the philosophy of AI.

By the end of this course students will be able to:

■ Explain in detail the key concepts that feature in contemporary debates about the philosophy of AI, and demonstrate active engagement with these concepts through argument mapping.

■ Explain in detail and critically evaluate the reasoning behind arguments for and against ethical and epistemological stances related to AI.

■ Create new examples that develop these positions.

■ Explain and critically evaluate challenges that face particular approaches and viewpoints in debates about Large Language Models, as well as to formulate hypotheses about future challenges that will face LLMs.

■ Construct new, and evaluate existing, arguments for and against specific theses in the philosophy of AI