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Updated: Jul 17, 2026

A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software
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Tail wagging cats: Veterinary implications of AI-generated video.

Jill R D MacKay1, Louise Connelly1

  • 1Veterinary Medical Education Division, Animal Welfare Centre, Royal (Dick) School of Veterinary Studies, the University of Edinburgh, Midlothian, Scotland, UK.

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|July 16, 2026
PubMed
Summary

Generative artificial intelligence (genAI) animal videos may mislead viewers by simplifying behavior. Veterinarians must address this new form of misinformation to protect animal welfare.

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Area of Science:

  • Animal Welfare Science
  • Artificial Intelligence
  • Veterinary Medicine

Background:

  • Generative artificial intelligence (genAI) can create realistic animal videos.
  • genAI simplifies animal behavior, potentially leading to misinformation.
  • This simplification may impact the accurate representation of animal welfare.

Purpose of the Study:

  • To assess the accuracy of animal behavior and welfare depicted in genAI videos.
  • To identify potential misinformation risks associated with genAI in animal content.

Main Methods:

  • Analyzed 29 videos from a genAI engine's press release; 12 featured animals.
  • Mapped videos to the five domains of animal welfare: nutrition, environment, health, behavior, and mental state.
  • Categorized depicted behaviors and welfare implications.

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Last Updated: Jul 17, 2026

A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software
08:22

A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software

Published on: August 31, 2018

Automated Interactive Video Playback for Studies of Animal Communication
07:21

Automated Interactive Video Playback for Studies of Animal Communication

Published on: February 9, 2011

Computer-Generated Animal Model Stimuli
26:43

Computer-Generated Animal Model Stimuli

Published on: July 29, 2007

Main Results:

  • Negative welfare indicators were infrequent (8-42%).
  • Positive indicators for mental state, environment, and behavior were observed in 42% of videos.
  • A significant portion of videos were misleading or inaccurately portrayed animal behavior.

Conclusions:

  • genAI-generated animal videos present a novel avenue for client confusion regarding animal welfare.
  • Veterinary professionals must proactively combat genAI-driven misinformation.
  • Further research is needed beyond press releases to understand user experience and broader impacts.