Tail wagging cats: Veterinary implications of AI‐generated video

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.

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Publication Details

Journal
Veterinary Record
Published
2026-07-16
DOI
https://doi.org/10.1002/vetr.70973
Primary Topic
Human-Animal Interaction Studies
Type
article
Field-Weighted Citation Impact
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article

Tail wagging cats: Veterinary implications of AI‐generated video

Jill R D MacKay, Louise Connelly
Veterinary Record
Human-Animal Interaction Studies
article

Tail wagging cats: Veterinary implications of AI‐generated video

Jill R D MacKay, Louise Connelly
article en

Abstract

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.

Veterinary Record
Roslin Institute (GB)
Openalex Percentile: Top 99%
Human-Animal Interaction Studies
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