Module manager: Kal Kalewold
Email: k.kalewold@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2026/27
This module is not approved as a discovery module
This module explores the history of artificial intelligence and philosophical ideas related to thinking machines. The module covers the history of the development of computing and philosophical reflection on the capacities and nature of what came to be known as artificial intelligence. You will engage with a diverse range of theoretical philosophical issues that arise because of the development of AI, including: the nature of machine consciousness, whether AI can be creative, what distinguishes human from AI understanding, among others. By the end, you will have the capacity to situate AI within its deeper lineage, assess claims about progress and novelty using historical methods, and articulate defensible philosophical positions on what it means for artificial systems to reason, learn, and know. Please note this is an optional module and runs subject to enrolments. If a low number of students choose this module, then the module may not run and you may be asked to choose another module.
In studying this module, you will explore historical and philosophical issues related to Artificial Intelligence. By engaging with these ideas, you will:
- Attain a solid grasp of central concepts, arguments, and theories in theoretical philosophy of artificial intelligence.
- Engage with key historical sources on the development of artificial intelligence and its precursor technologies.
- Gain crucial skills in interpreting and evaluating key historical and philosophical texts representing diverse views in the study of artificial intelligence.
Lectures will guide students through the topics. Seminars are an opportunity for students to discuss their own views on the concepts, theories, and arguments explored in the module in depth.
On successful completion of the module, students will be able to:
LO1. Critically analyse concepts and arguments in the philosophy of artificial intelligence.
LO2. Critically analyse relevant historical texts and hypotheses in history of technology
LO3. Construct insightful and cogent arguments in defence of your own position on some of the topics studied.
Skills Learning Outcomes
On successful completion of the module, students will be able to:
LO4. Communicate ideas and understanding clearly and concisely, using appropriate academic language (Academic and Work Ready skill)
LO5. Use appropriate primary and secondary source material to support knowledge and analysis of topics (Academic, Work Ready, Digital skill).
LO6. Search for, synthesise and critically evaluate source material to support knowledge and analysis of topics (Academic, Work Ready and Digital skill)
This module will cover a variety of topics in history and philosophy of artificial intelligence. Topics may vary each year. Typical topics covered may include:
What is an Artificial Intelligence?
Human Computers
Turing Machines and the Turing Test
Searle’s Chinese Room
What is Intelligence?
History of Artificial Intelligence
AI and Consciousness
Is Everything AI?
AI and Explainability
Can AI Understand Science?
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lectures | 10 | 1 | 10 |
| Seminars | 9 | 1 | 9 |
| Private study hours | 181 | ||
| Total Contact hours | 19 | ||
| Total hours (100hr per 10 credits) | 200 | ||
Students can complete one piece of formative work which will receive written feedback. Either:
1) Essay plan
2) Annotated Concept Genealogy with AI Assistance
Students will also be provided with short weekly quizzes to test their grasp of module material.
An essay plan facilitates feedback on an outline and proposal for the summative assessment. The annotated concept genealogy involves use of AI tools to trace how a key concept (e.g., “intelligence,” “alignment”) shifted over time.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Essay | Essay | 100 |
| Total percentage (Assessment Coursework) | 100 | |
Resit will be by the same methodology as the original attempt. Students must select a different essay topic from the list provided for the original attempt.
Check the module area in Minerva for your reading list
Last updated: 30/04/2026
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