Module manager: Dr. Matthew Abbey
Email: m.w.abbey@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 links between artificial intelligence (AI) and social justice. You will learn about the key concepts, discourses, and technologies relevant to the emergence of AI. During the course of the module, you will apply this knowledge to understand the ethical dilemmas that have arisen since governments began incorporating AI into their various operations. Moving away from both the utopic and dystopic claims being made about AI, you will critically analyse the possibilities and limitations of what AI can do. Relying on a case study approach—with indicative case studies on geopolitics, surveillance, policing, border control, the platform economy, and social media—you will develop the skills to critically evaluate how AI has reproduced and amplified injustice, while also exploring how this technological encroachment onto space and society has been contested.
Introduce students to various key concepts, discourses, and technologies relevant to AI and social justice, focusing on their relevance to critical human geography.
Allow students to interrogate topical issues on AI and social justice relevant to critical human geography, including indicative case studies on geopolitics, surveillance, policing, border control, the platform economy, and social media.
Encourage students to critically reflect on what AI means for the governance of space and society, addressing how critical human geography approaches can develop nuanced insights into social justice concerns amidst technological change.
1. Demonstrate a critical understanding of AI and social justice from a critical human geography perspective.
2. Apply knowledge of critical human geography to analyse how AI has been deployed by governments while also assessing what social justice concerns have arisen in response.
3. Analyse the relevance of concepts, discourses, and technologies related to AI for approaching critical human geography.
4. Formulate own arguments and reflexive insights into what AI means for governance of space and society, with a specific focus on social justice.
On successful completion of the module students will:
1. Develop knowledge base by analysing information from multiple sources (Academic skills: critical thinking, reflection, information sharing; Work ready skills: research skills, IT skills).
2 Apply problem solving and analytical skills to identify solutions, explore alternatives, and design practical strategies (Academic skills: Critical thinking; Work ready skills: problem solving and analytical skills).
3. Communicate evidence clearly and effectively in written formats (Academic skills: Academic writing; Work ready skills: Communication)
4. Collaborate productively in groups to design and deliver a project (Academic skills: Time management; Work ready skills: Teamwork/collaboration, creativity)
5. Locate, evaluate, and effectively use relevant information and sources to support academic inquiry. (Academic skills: referencing; Work place skills: research skills)
6. Reflect on decisions, challenges, and lessons learned, connecting own project work to wider academic contexts. (Academic skills: reflection; Work ready skills: problem solving & analytical skills; adaptability/flexibility)
7 Analyse and compare different arguments and perspectives, using evidence to form own well-reasoned insights (Academic skills: critical thinking, academic writing, academic language, academic integrity; Work place skills: communication)
Details of the syllabus will be provided on the Minerva organisation (or equivalent) for the module.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Workshop | 1 | 1 | 1 |
| Film Screenings | 1 | 3 | 3 |
| Group Project | 3 | 2 | 6 |
| Lecture | 10 | 1 | 10 |
| Seminar | 10 | 1 | 10 |
| Private study hours | 270 | ||
| Total Contact hours | 30 | ||
| Total hours (100hr per 10 credits) | 300 | ||
Seminar discussions for both assignments
Group feedback available during group work sessions dedicated to Assignment 1
Post-group work sessions generic feedback on Assignment 1
Weekly office hours for both assignments
Feedback on Assignment 1 provided before Assignment 2 due.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Coursework | Coursework | 50 |
| Coursework | Coursework | 50 |
| Total percentage (Assessment Coursework) | 100 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Check the module area in Minerva for your reading list
Last updated: 30/04/2026
Errors, omissions, failed links etc should be notified to the Catalogue Team