mlsanityData to 7 Oct 2026

Generative Ghosts: Anticipating Benefits and Risks of AI Afterlives

arXiv 2402.01662 ↗First posted 14 Jan 2024cs.CY cs.AIcited by 15

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Abstract (arXiv)

As AI systems quickly improve in both breadth and depth of performance, they lend themselves to creating increasingly powerful and realistic agents, including the possibility of agents modeled on specific people. We anticipate that within our lifetimes it may become common practice for people to create custom AI agents to interact with loved ones and/or the broader world after death; indeed, the past year has seen a boom in startups purporting to offer such services. We call these generative ghosts, since such agents will be capable of generating novel content rather than merely parroting content produced by their creator while living. In this paper, we reflect on the history of technologies for AI afterlives, including current early attempts by individual enthusiasts and startup companies to create generative ghosts. We then introduce a novel design space detailing potential implementations of generative ghosts, and use this analytic framework to ground discussion of the practical and ethical implications of various approaches to designing generative ghosts, including potential positive and negative impacts on individuals and society. Based on these considerations, we lay out a research agenda for the AI and HCI research communities to better understand the risk/benefit landscape of this novel technology so as to ultimately empower people who wish to create and interact with AI afterlives to do so in a beneficial manner.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 16 of its 130 references that are in the map. First posted on arXiv 14 Jan 2024.

Builds on

16 of 130 references.

References · 16

  1. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  2. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
  3. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 2,950
  4. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
  5. 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,725
  6. 2023The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)cited by 677
  7. 2022AudioLM: a Language Modeling Approach to Audio Generationcited by 611
  8. 2023Scalable Extraction of Training Data from (Production) Language Modelscited by 415
  9. 2023Sociotechnical Safety Evaluation of Generative AI Systemscited by 154
  10. 2023GenAI Against Humanity: Nefarious Applications of Generative Artificial Intelligence and Large Language Modelscited by 40
  11. 2023Mirages: On Anthropomorphism in Dialogue Systemscited by 30
  12. 2023Scientists' Perspectives on the Potential for Generative AI in their Fieldscited by 22
4 more
  1. 2022Mimetic Models: Ethical Implications of AI that Acts Like Youcited by 11
  2. 2021Archives and AI: An Overview of Current Debates and Future Perspectivescited by 9
  3. 2019Tending Unmarked Graves: Classification of Post-mortem Content on Social Mediacited by 2
  4. 2021From Personal Data to Digital Legacy: Exploring Conflicts in the Sharing, Security and Privacy of Post-mortem Datacited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 6; 2026: 6.

15 papers.

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