Module manager: Dr Yen Nee Wong
Email: y.wong@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2025/26
This module is not approved as an Elective
The module offers students a grounding in debates on the social, cultural, economic and political implications of AI and emerging digital technologies on the realms of creative arts, media and communications, work and everyday life. Placing people, rather than technology at the centre of AI and digital technologies, practical case studies are used to encourage students to delve into theories around datafication, data justice, algorithmic decision-making, data literacies and artificial intelligence. The opportunities, risks and ethical implications involved in the use of emerging digital technologies and AI in society will be discussed in this module.
The module aims to furnish students with the theories and approaches from digital sociology, critical data studies and communications studies to evaluate and critique debates and research around datafication and the suitability of AI technologies in the production and progression of society. Embedding the use of generative AI tools in teaching and learning, one of the key objectives is to equip students with digital capabilities to communicate knowledge to a diverse range of stakeholders and sectors through visual, oral and written means. The module engages an experiential learning approach, with the goal to motivate students to adopt a critical lens, applying theories taught in the module to critique their adoption of AI technologies in their coursework. Students will create their own visual and textual outputs based on an in-depth exploration of one of the practical case studies covered in the module, which they will organise into an exhibition at the annual PGT conference organised by the School of Sociology and Social Policy. Students’ critical analysis of their generative AI technology adoption is achieved through both the exhibition and reflective review components of the assessment, which require students to curate the exhibition and reflect on the production processes of the artistic work and exhibition respectively.
On successful completion of the module students will have demonstrated the following skills learning outcomes:
(1) Develop key digital skills and be able to use Generative AI tools for digital creation and communication of ideas in both visual and written formats.
(2) Develop academic skills in the oral and visual presentations of key ideas to a variety of audience, academic writing skills using academic language, information searching and referencing skills.
(3) Host an exhibition demonstrating ability to work collaboratively in teams, acquire time management, planning and organising, leadership, creativity, active learning, relationship development, decision-making and negotiation skills through the organising and hosting of an exhibition.
(4) Demonstrate enterprise skills of self-awareness and the application of digital literacy skills to assess social issues relating to digital platforms.
On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:
LO1: Explain the role of AI in society
LO2: Recognise and articulate societal implications of datafication and new digital technologies
LO3: Apply relevant theories and concepts to an evaluation of the risks and opportunities that emerging technologies and data bring to society, media and work
LO4: Effectively use AI tools in collaborative group work to create visual outputs for an exhibition
LO5: Reflect on specific topics in the groupwork and the collaborative process
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Fieldwork | 1 | 7 | 7 |
| Lecture | 11 | 1 | 11 |
| Practical | 10 | 2 | 20 |
| Private study hours | 262 | ||
| Total Contact hours | 38 | ||
| Total hours (100hr per 10 credits) | 300 | ||
Formative feedback is provided through workshop sessions in which students will be working in teams for their summative assignments, and challenged to demonstrate their understanding, critical and knowledge in relation to the module’s objectives and learning outcomes. Students will also be encouraged to consult with module staff during open door sessions for formative feedback. The weekly lectures will also build in moments of formative feedback focused on students’ preparation for their summative assignments.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Assignment | Coursework | 50 |
| Assignment | Coursework | 50 |
| Total percentage (Assessment Coursework) | 100 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
The reading list is available from the Library website
Last updated: 11/06/2025
Errors, omissions, failed links etc should be notified to the Catalogue Team