Undergraduate Course: Media, AI and Memory (SCIL10100)
Course Outline
| School | School of Social and Political Science |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course addresses the tensions and relationships between emergent technologies and media and the nature and function of individual and social remembering and forgetting. It enables students to use interdisciplinary social science insights to explore the changing relationships between media, the past and the future. This includes the ways in which the past is made relevant in the present, to effect relations of power, identity, and inequality. |
| Course description |
Digital media and AI-driven apps, services and platforms have infinitely expanded the capacity of individuals and societies to hold on to the past, to capture, store, keep, but also remake it, through discarding, erasure, and challenging it anew. At the same time, through outsourcing memory to digital tools and mechanisms, and the processes through which we make sense of the world, we have also loosened our individual human grasp and sense of collective agency over what the past is, how it is seen, not seen, and used, and by whom.
This course enables students to use interdisciplinary social science insights to explore the changing relationships between media, the past and the future. This includes the ways in which the past is made relevant in the present, to effect relations of power, identity, and inequality. It addresses how media and technologies in the AI era shape (and are used to shape) individual, group, collective, and societal remembering and forgetting. Key course themes include: identity, rights, nostalgia, forgetting, ethics, nostalgia, art, journalism, archives, records, testimony, museums, activism, generations, war and conflict, commemoration, memorialisation, autobiography, digital afterlife, erasure and obsolescence.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2025/26, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 10,
Seminar/Tutorial Hours 20,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
166 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
100% Final long essay (4500 words). |
| Feedback |
All students will be provided with written feedback from the course organiser on a formative essay/case study plan at least four weeks before the final submission date.
All students will attend a tutorial dedicated to assessment guidance as well as being offered additional help by the course organiser in office hours. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Demonstrate interdisciplinary knowledge and a critical understanding of the key theories, concepts and approaches to the study of media, AI and memory.
- Engage with ideas, concepts, theories, debates, and approaches as to the distinctiveness of the characteristics and consequences of remembering and forgetting in the digital and AI era.
- Apply knowledge, skills and understanding in applying a range of techniques of enquiry to the study of media, AI and memory.
- Draw systematically on a range of resources and materials, including academic, journalistic, and other media texts, to inform interdisciplinary understanding, argument and analysis.
- Exercise autonomy and initiative in written work.
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Reading List
Hollanek, T and Nowaczyk-Basinska, K (2024) Griefbots, deadbots, postmortem avatars: on responsible applications of generative AI in the digital afterlife industry.Philos. Technol.37, 63. https://doi.org/10.1007/s13347-024-00744-w.
Hoskins A. (2024) AI and memory.Memory, Mind & Media, https://doi.org/10.1017/mem.2024.16
Öhman, C (2024) The afterlife of data. What happens to your information when you die and why you should care. Chicago: The University of Chicago Press.
Rieff, D. (2016) In Praise of Forgetting: Historical Memory and Its Ironies. Yale: Yale University Press.
Wang, Q. and Hoskins, A. (Eds.) (2024) The Remaking of Memory in the Age of the Internet and Social Media. Oxford: Oxford University Press. |
Additional Information
| Graduate Attributes and Skills |
Individual skills and ability in planning and executing a larger piece of individual work.
Making effective use of oral and written means to critique, negotiate, create and communicate understanding
Ability to work in an interdisciplinary manner and to engage with traditions and approaches, and to deploy analytical skill sets deriving from sociology, digital media and AI studies, memory studies, and cognitive science.
Capacity to engage sensitively and critically with ethical issues arising from the uses of rapidly changing technologies to augment, contest and erase individual and collective memory.
Being adaptive and proactively responsive to changing social and technological contexts |
| Keywords | Not entered |
Contacts
| Course organiser | |
Course secretary | |
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