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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.
Background:
Generative artificial intelligence (genAI) has the capacity to create realistic and convincing animal videos; however, it must simplify and reduce behavioural variation to do so, possibly leading to misinformation.
Methods:
We categorised 29 videos in the press release for a specific video genAI engine. Twelve featured animals. We mapped each video to the five domains of animal welfare (nutrition, physical environment, health, behavioural interactions and mental state) and categorised behaviour and welfare accordingly.
Results:
Negative welfare was rarely seen, ranging from 8% (n = 1) for nutrition to 42% (n = 5) for behavioural interactions. By contrast, mental state, environment and behavioural interactions appeared positive in 42% (n = 5) of the videos featured. However, videos were often misleading or did not represent accurate animal behaviour.
Limitations:
This work was limited to a press release of data and did not explore user experience.
Conclusions:
genAI videos pose a new route for client confusion, and veterinarians need to incorporate the combatting of genAI misinformation in their practice.
