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Record W4413911617 · doi:10.32920/ifmj.v5i1-2.2427

And Yet… The Paradox of Generative AI Griefbots

2025· article· en· W4413911617 on OpenAlexaffvenue
Siobhan O’Flynn

Bibliographic record

VenueInteractive Film and Media Journal · 2025
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGenerative grammarPhilosophyEpistemologyPsychologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

“And Yet… The Paradox of Generative AI Griefbots” addresses current advances in generative artificial intelligence technologies that offer LLMs and/or chatbots that can be customized to simulate the personae of lost loved ones with the input of digitized materials (text, image, video, audio). This paper examines the benefits and the dangers of intimate interactions with personalized, always-on chatbots that can provide users with deeply immersive experiences through three distinct theoretical frameworks. The first uses the qualitative research method of autoethnography to reflect on the months-long research-creation process of remediating a single photograph of myself and my father via the AI image generator, Midjourney. This project was undertaken as an experiment in elegy and culminated in two works of e-literature, the Twine visual novels, Infinity +1 and Infinite Eddies, and an early critical essay presented at the British Library MixConference 2023. Each reflects differently on the precarity of memory and the affect I experienced in Midjourney’s capacity to identify and remediate a set of identifiable elements that emphasize an emotional relationship configured through the positioning of our bodies in the frame, while simultaneously reinventing through infinite variations in time and place. Critical references include Hiroki Azuma’s conceptualization of “moe-elements” in anime in Otaku: Japan’s Database Animals (2009), Walter Benjamin’s ““The Work of Art in the Age of Its Technological Reproducibility,” and Nettrice Gaskins’ essay, “The Aura of AI-Generated Art.” The second theoretical framework examines the phenomenon of griefbots and human grieving for the beloved, looking back to Gilgamesh mourning Enkidu and Orpheus’ attempt to recover Eurydice from the Underworld recontextualized from the contemporary vantage of new technological products offered by Replika AI, Project December, Super Brain, and Seance AI. These simulations clearly can be beneficial as (re)mediations bridge the void felt after the loss of loved ones. Notably, Replika AI launched after founder Eugenia Kudya created a chatbot from the emails and text messages of her best friend after his death and a Stanford study (2024) has documented emotional benefits for users, including a decrease in suicidal ideation. Joshua Barbeau has written movingly on his experience of interacting with his lost girlfriend Jessica via game-developer Jason Roher’s AI chatbot platform, December Project, stating that “The whole experience gave me a sense of closure I didn’t even know I still needed.” Intertexts informing this critique include Shannon Vallor’s The AI Mirror, Derrida’s reading of the phármakon as remedy and poison, and Joseph Weisenbaum's warning of the “powerful delusional thinking” in user responses to the first AI Chatbot, Eliza (1976). The third section examines existing and proposed regulatory frameworks, the ethics of AI products, or lack thereof, in the “digital afterlife industry. Of particular note is the categorization of harm from “high risk anthropomorphic behaviour” detailed in Garcia v. Character Technologies Inc., et al. The charge that technology companies intentionally design “generative AI systems with anthropomorphic qualities to obfuscate between fiction and reality.…launching their systems without adequate safety features” provides the critical framework for my analysis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.672
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.264
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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