Abstract
This paper explores automated and algorithmic processes designed to change the structure and behaviour of images from the past, in-so-doing, offering them new kinds of ‘afterlife’. Specifically, it explores how (images of) our deceased ancestors are remediated and ‘resurrected’ through a number of generative AI programmes (Deep Nostalgia and HereAfter AI for example). We report findings from the Synthetic Pasts project (2022-2024), a mixed-methodology investigation into how the production of such outputs (1) affords new networked, technological, temporal, spatial and affective realities for archival images, and (2) impacts individual, collective, and cultural memory work as a consequence (Kidd and Nieto McAvoy 2023, Nieto McAvoy and Kidd 2024). In this paper we interrogate what values and cultural assumptions are embedded in the systems that produce synthetic images of our familial pasts, and unpack the myriad ethical challenges they present; for example, in relation to ‘deceptive genealogy’, the exploitation of datafied bodies, and (often posthumous) consent. Our findings are significant as they speak to human concerns reaching beyond the digital including how we grieve, how we express and understand identity, how we articulate and commemorate the past, and the impacts of disinformation. The paper sets out a nascent agenda for the study of ‘synthetic pasts’ in the coming years, exploring what future(s) for image archives our algorithmic present anticipate and pave the way for.
Presenters
Jenny KiddReader, School of Journalism, Media and Culture, Cardiff University, Cardiff [Caerdydd GB-CRD], United Kingdom Eva Nieto Mc Avoy
Lecturer in Digital Media, Department of Digital Humanities, King's College London, United Kingdom
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
2024 Special Focus—Images and Imaginaries from Artificial Intelligence
KEYWORDS
Generative AI, Afterlives, Remediation, Deceptive Genealogy, Archives
