Module manager: Dr. Dibyadyuti Roy
Email: d.roy1@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2026/27
This module is not approved as an Elective
What does human creativity mean in the age of modern AI? Will neural-network-based deep learning systems challenge or enhance our cultural landscapes? How can cultural policymakers and creative practitioners interface with technologists and industry professionals to shape the futures of human and computational creativity? Through examining academic scholarship, creative artifacts, and policy papers on generative AI, authorship, IP rights, artistic labour, and widening access to tools in cultural production—across both Global North and Global South/Global Majority contexts—you will learn to critically evaluate how algorithmic outputs intersect with human culture and understand the ethical, political, and social ramifications of deploying algorithmic processes within the creative industries.
1. Introduce you to debates about creativity, authorship, and cultural production in the age of AI, enabling you to understand how generative systems challenge traditional notions of human creative practice and artistic labour.
2. Enable you to critically examine pressing issues at the intersection of modern AI systems and culture, including intellectual property and authorship, labour conditions in creative industries, algorithmic representation and bias, and unequal access to creative AI tools across global contexts.
3. Develop your capacity for cultural policymaking through critically evaluating AI creativity while understanding the ethical, political, and social implications of algorithmic processes in cultural production and policy.
We will achieve these objectives through interactive workshops. In these workshops you will engage with a range of learning materials such as academic scholarship, creative artifacts, and policy papers where the intersection of AI and cultural creativity are at issue. You will also engage with fellow students on discussing, exploring and analysing these issues.
On successful completion of the module you will be able to:
1. Critically evaluate the ethical, political, and social implications of deploying AI in creative industries by applying ethical frameworks to real-world case studies;
2. Develop evidence-based recommendations for cultural policymakers and creative practitioners on the responsible governance and implementation of AI;
3. Communicate complex technical and ethical issues to diverse stakeholders across sectors.
4. Translate complex ideas about AI, creativity, and ethics, tailoring arguments and evidence for audiences such as policymakers. (Academic, Work Ready, Enterprise, Digital skills);
5. Search for, critically evaluate, and synthesize diverse information sources—including academic scholarship, policy papers, and creative artifacts—to strengthen research quality and support evidence-based analysis of AI in the cultural sector. (Sustainability, Enterprise, Academic);
6. Assess multiple perspectives and competing arguments, integrating evidence from various sources to develop well-reasoned positions, analytical frameworks, and original ideas for academic and workplace application. (Work Ready, Enterprise and Academic Skills).
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Seminar | 2 | 1 | 2 |
| Seminar | 9 | 2 | 18 |
| Private study hours | 130 | ||
| Total Contact hours | 20 | ||
| Total hours (100hr per 10 credits) | 150 | ||
130
A 500 word policy brief developing actionable policy ideas on innovative practices/possibilities/threats to cultural ecosystems that have emerged with the advent of AI and algorithmic creativity. This piece will be reviewed mid semester with short feedback provided. The policy brief formal assessment is intended as scaffolding for the summative podcast assessment; students will be able to use the feedback they receive on it to inform the way they construct the podcast.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Coursework | Coursework | 100 |
| 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