A new breed of prophets – intermediaries and pastoral bros of an AI industry with metaphysical aspirations – has surfaced on the global stage during troubled times. They make great promises, offer predictions and warnings, and stake out directions for humanity. This article argues that they do so by invoking the implicit collective memory of the apocalyptic imaginary known from ancient Jewish apocalyptic writings and, more specifically, by reenacting what we call prophetic memory. Through close readings in the tradition of biblical exegesis coupled with philosophical and critical hermeneutics, we trace strong AI narratives of doom and salvation to a range of media forms such as Twitter/X postings, books, interviews, journalistic feature articles, and reporting. Through these media, AI prophets speak of the end times while simultaneously offering a new beginning for humankind, not unlike the ancient prophets of the Hebrew Bible. Prophetic memory, we submit, is furthermore a mode of ‘collective future thought’ and an instantiation of the ‘remembering-imagining-system’. While its purpose is to create stability for a particular vision for the future, there is also a productive ambivalence of order and disorder at work within the apocalyptic AI imaginary. To question this ambiguous yet extremely powerful fixture on the human horizon, there is a need, we argue, for bothering the political-religious dimensions of the hegemonic AI imaginary and for scrutinizing how the AI industry founds its power base on the clout of prophetic memory – in a time of crisis in which many look for guidance and direction.

Using the fields of memory studies and digital humanities, this article argues that there has been a shift from more collective and social memory to more personalised and individual memory. This shift, it is argued here, can be conceptualised through the psychoanalytic concept of ‘psychosis’. While the causes of the changes in our patterns of memory have been located in capitalist and neoliberal principles, the effects of the changes in our memory habits might be found in psychosis. From falling in love with machinic AI replicas to indulging in conspiracy theories to acting as if we are social media influencers or backing ourselves to win out in impossible job markets, we are inclined towards personal fantasy, often at the expense of participating in social life. But why do we do this? Why is it easier to believe a farfetched conspiracy theory or wild personal dream than it is to participate socially and collectively in the world we live in? Part of the reason, at least, is found in our increasing habitual reliance on new and emergent technologies. Often presented to us as a brand-new form of Artificial Intelligence, these generative tools are the latest update to a longer pattern in our digital world: the trend of developing ‘relationships’ with algorithms that, to larger and smaller degrees, we come to rely on for habits of cognition and recognition. By affecting our patterns of memory, these technologies produce a kind of isolation that lends itself to individual and fantastical – rather than shared and realist – thinking.

Advances in generative artificial intelligence (AI) have driven a growing effort to create digital duplicates. These semi-autonomous recreations of living and dead people can be used for many purposes. Some of these purposes include tutoring, coping with grief, and attending business meetings. However, the normative implications of digital duplicates remain obscure, particularly considering the possibility of them being applied to genocide memory and education. To address this gap, we examine normative possibilities and risks associated with the use of more advanced forms of generative AI-enhanced duplicates for transmitting Holocaust survivor testimonies. We first review the historical and contemporary uses of survivor testimonies. Then, we scrutinize the possible benefits of using digital duplicates in this context and apply the Minimally Viable Permissibility Principle (MVPP). The MVPP is an analytical framework for evaluating the risks of digital duplicates. It includes five core components: the need for authentic presence, consent, positive value, transparency, and harm-risk mitigation. Using MVPP, we identify potential harms digital duplicates might pose to different actors, including survivors, users, and developers. We also propose technical and socio-technical mitigation strategies to address these harms.

The nexus of artificial intelligence (AI) and memory is typically theorized as a ‘hybrid’ or ‘symbiosis’ between humans and machines. The dangers related to this nexus are subsequently imagined as tilting the power balance between its two components, such that humanity loses control over its perception of the past to the machines. In this article, I propose a new interpretation: AI, I posit, is not merely a non-human agency that changes mnemonic processes, but rather a window through which the past itself gains agency and extends into the present. This interpretation holds two advantages. First, it reveals the full scope of the AI–memory nexus. If AI is an interactive extension of the past, rather than a technology acting upon it, every application of it constitutes an act of memory. Second, rather than locating AI’s power along familiar axes – between humans and machines, or among competing social groups – it reveals a temporal axis of power: between the present and the past. In the article’s final section, I illustrate the utility of this approach by applying it to the legal system’s increasing dependence on machines, which, I claim, represents not just a technical but a mnemonic shift, where the present is increasingly falling under the dominion of the past – embodied by AI.

The assumption that deleted digital information is irretrievably lost remains widespread, yet this belief obscures the continued existence of residual traces within archives, backups, and systems that implement only partial or ‘soft’ deletion. Such remnants, though frequently overlooked, may persist in shaping the operation of artificial intelligence (AI) and therefore warrant critical examination. This article addresses three interrelated questions. First, through what mechanisms do obsolete or concealed data fragments re-enter AI systems and exert influence that manifests as bias or distortion? Second, in what ways might the trajectory of digital information be conceptualised through reference to ecological processes such as decomposition, renewal, and systemic adaptation? Third, what forms of regulatory or procedural innovation – here articulated as a model of ‘digital composting’ – could facilitate the identification, evaluation, and responsible management of residual data? The analysis demonstrates that outdated data frequently function as ‘ghost inputs’. Despite their invisibility, these elements shape the generative capacity of AI, modify the narratives it produces, and subtly recalibrate public discourse as well as shared cultural memory. Their persistence underscores the communicative and social significance of digital traces once presumed to be obsolete. To advance this discussion, the article introduces the concept of a ‘Data Decay Pathway’. This framework offers a novel means of addressing accountability and transparency in digital systems, emphasising that processes of digital decay, much like those observed in natural ecosystems, may serve either to sustain the vitality of collective memory or to propagate forms of distortion and systemic vulnerability.

This study addresses how AI-generated images of war are changing the making of memory. Instead of asking how AI-generated images affect individual recall, we focus on how they communicate specific representations, recognising that such portrayals can cultivate particular assumptions and beliefs. Drawing on memory of the multitude, visual social semiotics, and cultivation/desensitisation theories, we analyse how visual generative AI mediates the representation of the Russia-Ukraine war. Our corpus includes 200 images of the Russia-Ukraine war generated from 23 prompts across proprietary and open-source visual generative AI systems. The findings indicate that visual generative AI tends to present a sanitised view of the war. Critical aspects, such as death, injury, and suffering of children and refugees are often excluded. Furthermore, a disproportional focus on urban areas misrepresents the full scope of the war. Visual generative AI, we argue, introduces a new dimension to memory making in that it blends documentation with speculative fiction by synthesising the multitude embedded within the visual memory of war archives, historical biases, representational limitations, and commercial risk aversion. By foregrounding the socio-technical and discursive dimensions of synthetic war content, this study contributes to an interdisciplinary dialogue on collective memory at the intersection of visual communication studies, media studies, and memory studies by providing empirical insights into how generative AI mediates the visual representation of war through human-archival-mechanistic entanglements.

This article explores the transformational potential of artificial intelligence (AI), particularly generative AI (genAI) – large language models (LLMs), chatbots, and AI-driven smart assistants yet to emerge – to reshape human cognition, memory, and creativity. First, the paper investigates the potential of genAI tools to enable a new form of human-computer co-remembering, based on prompting rather than traditional recollection. Second, it examines the individual, cultural, and social implications of co-creating with genAI for human creativity. These phenomena are explored through the concept of Homo Promptus, a figure whose cognitive processes are shaped by engagement with AI. Two speculative scenarios illustrate these dynamics. The first, ‘prompting to remember’, analyses genAI tools as cognitive extensions that offload memory work to machines. The second scenario, ‘prompting to create’, explores changes in creativity when performing together with genAI tools as co-creators. By mobilising concepts from cognitive psychology, media and memory studies, together with Huizinga’s exploration of play, and Rancière’s intellectual emancipation, this study argues that genAI tools are not only reshaping how humans remember and create but also redefining cultural and social norms. It concludes by calling for ‘critical’ engagement with the societal and intellectual implications of AI, advocating for research that fosters adaptive and independent (meta)cognitive practices to reconcile digital innovation with human agency.

This short research article interrogates the rise of digital platforms that enable ‘synthetic afterlives’, with a focus on how deathbots – AI-driven avatar interactions grounded in personal data and recordings – reshape memory practices. Drawing on socio-technical walkthroughs of four platforms – Almaya, HereAfter, Séance AI, and You, Only Virtual – we analyse how they frame, archive, and algorithmically regenerate memories. Our findings reveal a central tension: between preserving the past as a fixed archive and continually reanimating it through generative AI. Our walkthroughs demonstrate how these services commodify remembrance, reducing memory to consumer-driven interactions designed for affective engagement while obscuring the ethical, epistemological and emotional complexities of digital commemoration. In doing so, they enact reductive forms of memory that are embedded within platform economies and algorithmic imaginaries.

This article argues that the environmental contexts of memory are vulnerable to Artificial Intelligence (AI)-generated distortions. By addressing the broader ecological implications for AI’s integration into society, this article looks beyond a sociotechnical dimension to explore the potential for AI to complicate environmental memory and its role in shaping human–environment relations. First, I address how the manipulation and falsification of memory risks undermining intergenerational transmission of environmental knowledge. Second, I examine how AI-generated blurring of boundaries between real and unreal can lead to collective inaction on environmental challenges. By identifying memory’s central role in addressing environmental crisis, this article places emerging debates on memory in the AI era in direct conversation with environmental discourse and scholarship.

This paper is written at a tipping point in the development of generative AI and related technologies and services, which heralds a new battleground between humans and computers in the shaping of reality. Large language models (LLMs) scrape vast amounts of data from the so called ‘publicly available' internet, enabling new ways for the past to be represented and reimagined at scale, for individuals and societies. Moreover, generative AI changes what memory is and what memory does, pushing it beyond the realm of individual, human influence, and control, yet at the same time offering new modes of expression, conversation, creativity, and ways of overcoming forgetting. I argue here for a ‘third way of memory’, to recognise how the entanglements between humans and machines both enable and endanger human agency in the making and the remixing of individual and collective memory. This includes the growth of AI agents, with increasing autonomy and infinite potential to make, remake, and repurpose individual and collective pasts, beyond human consent and control. This paper outlines two key developments of generative AI-driven services: firstly, they untether the human past from the present, producing a past that was never actually remembered in the first place, and, secondly, they usher in a new ‘conversational’ past through the dialogical construction of memory in the present. Ultimately, developments in generative AI are making it more difficult for us to recognise the human influence on, and pathways from, the past, and that human agency over remembering and forgetting is increasingly challenged.

Artificial Intelligence (AI) has reached memory studies in earnest. This partly reflects the hype around recent developments in generative AI (genAI), machine learning, and large language models (LLMs). But how can memory studies scholars handle this hype? Focusing on genAI applications, in particular so-called ‘chatbots’ (transformer-based instruction-tuned text generators), this commentary highlights five areas of critique that can help memory scholars to critically interrogate AI’s implications for their field. These are: (1) historical critiques that complicate AI’s common historical narrative and historicize genAI; (2) technical critiques that highlight how genAI applications are designed and function; (3) praxis critiques that centre on how people use genAI; (4) geopolitical critiques that recognize how international power dynamics shape the uneven global distribution of genAI and its consequences; and (5) environmental critiques that foreground genAI’s ecological impact. For each area, we highlight debates and themes that we argue should be central to the ongoing study of genAI and memory. We do this from an interdisciplinary perspective that combines our knowledge of digital sociology, media studies, literary and cultural studies, cognitive psychology, and communication and computer science. We conclude with a methodological provocation and by reflecting on our own role in the hype we are seeking to dispel.

This article is a commentary on the relationship between artificial intelligence (AI), capitalism, and memory. The political policies of neoliberalism have reduced the capacity of individuals and groups to reflect on and change the social world, meanwhile applications of AI and algorithmic technologies, rooted in the profit-seeking objectives of global capitalism, deepen this deficit. In these conditions, memory in individuals and across society is at risk of becoming myopic. In this article, I develop the concept of myopic memory with two core claims. Firstly, I argue that AI is a technological development that cannot be divorced from the capitalist conditions from which it comes from and is implemented in service of. To this end, I reveal capitalism and colonialism's historical and contemporary use of surveillance as a way to control the populations it oppresses, imagining their pasts to determine their futures, disempowering them in the process. My second core claim emphasises that this process of disempowerment is undergoing an acute realisation four decades into the period of neoliberalism. Neoliberal policies have restructured society on the basis of being an individual consumer, leaving little time, space, and institutional capacity for citizens to reflect on their impact or challenge their dominance. As a result, with the growing role of AI and algorithmic technologies in shaping our engagement with society along similar lines of individualism, it is my conclusion that the scope of memory is being reduced and constrained within the prism of capitalism, reducing its potential, and rendering it myopic.

Given the potential of generative artificial intelligence (GenAI) to create human clones, it is not surprising that chatbots have been implemented in politics. In a turbulent political context, these AI-driven bots are likely to be used to spread biased information, amplify polarisation, and distort our memories. Large language models (LLMs) lack ‘political memory’ and cannot accurately process political discourses that draw from collective political memory. We refer to research concerning collective political memory and AI to present our observations of a chatbot experiment undertaken during the Presidential Elections in Finland in early 2024. This election took place at a historically crucial moment, as Finland, traditionally an advocate of neutrality and peacefulness, had become a vocal supporter of Ukraine and a new member state of NATO. Our research team developed LLM-driven chatbots for all presidential candidates, and Finnish citizens were afforded the chance to engage with these chatbot–politicians. In our study, human–chatbot discussions related to foreign and security politics were especially interesting. While rhetorically very typical and believable in light of real political speech, chatbots reorganised prevailing discourses generating responses that distorted the collective political memory. In actuality, Russia’s full-scale invasion of Ukraine had drastically changed Finland’s political positioning. Our AI-driven chatbots, or ‘electobots’, continued to promote constructive dialogue with Russia, thus earning our moniker ‘Finlandised Bots’. Our experiment highlights that training AI for political purposes requires familiarity with the prevailing discourses and attunement to the nuances of the context, showcasing the importance of studying human–machine interactions beyond the typical viewpoint of disinformation.