← 목록으로

A Taxonomy of Omnicidal Futures Involving Artificial Intelligence

A Taxonomy of Omnicidal Futures Involving Artificial Intelligence

요약

This report presents a taxonomy and examples of potential omnicidal events resulting from AI: scenarios where all or almost all humans are killed. These events are not presented as inevitable, but as possibilities that we can work to avoid. Insofar as large i…

본문

Computer Science > Artificial Intelligence arXiv:2507.09369 (cs) [Submitted on 12 Jul 2025] Title:A Taxonomy of Omnicidal Futures Involving Artificial Intelligence Authors:Andrew Critch, Jacob Tsimerman View a PDF of the paper titled A Taxonomy of Omnicidal Futures Involving Artificial Intelligence, by Andrew Critch and 1 other authors View PDF HTML (experimental)
Abstract:This report presents a taxonomy and examples of potential omnicidal events resulting from AI: scenarios where all or almost all humans are killed. These events are not presented as inevitable, but as possibilities that we can work to avoid. Insofar as large institutions require a degree of public support in order to take certain actions, we hope that by presenting these possibilities in public, we can help to support preventive measures against catastrophic risks from AI.
Subjects: Artificial Intelligence (cs.AI)
MSC classes: 68T01
ACM classes: I.2.0
Cite as: arXiv:2507.09369 [cs.AI]
  (or arXiv:2507.09369v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2507.09369 arXiv-issued DOI via DataCite

Submission history

From: Andrew Critch PhD [view email]
[v1] Sat, 12 Jul 2025 18:23:36 UTC (420 KB)
Full-text links:

Access Paper:

license icon view license

Current browse context:

cs.AI < prev   |   next >
new | recent | 2025-07 Change to browse by: cs

References & Citations

Loading...

BibTeX formatted citation

loading... Data provided by:

Bookmark

BibSonomy Reddit Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) About arXivLabs arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
← 목록으로