Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Beyond Deepfake Technology Fear: On its Positive Uses for Livestock Farming

Version 1 : Received: 14 July 2021 / Approved: 14 July 2021 / Online: 14 July 2021 (11:49:38 CEST)

How to cite: Neethirajan, S. Beyond Deepfake Technology Fear: On its Positive Uses for Livestock Farming. Preprints 2021, 2021070326. https://doi.org/10.20944/preprints202107.0326.v1 Neethirajan, S. Beyond Deepfake Technology Fear: On its Positive Uses for Livestock Farming. Preprints 2021, 2021070326. https://doi.org/10.20944/preprints202107.0326.v1

Abstract

Deepfake technologies are known for the creation of forged celebrity pornography, face and voice swaps, and other fake media content. Despite the negative connotations the technology bears, the underlying machine learning algorithms have a huge potential that could be applied to not just digital media, but also to medicine, biology, affective science, and agriculture, just to name a few. Due to the ability to generate big datasets based on real data distributions, deepfake could also be used to positively impact non-human animals such as livestock. Generated data using Generative Adversarial Networks, one of the algorithms that deepfake is based on, could be used to train models to accurately identify and monitor animal health and emotions. Through data augmentation, using digital twins, and maybe even displaying digital conspecifics where social interactions are enhanced, deepfake technologies have the potential to increase animal health, emotionality, sociality, animal-human and animal-computer interactions and thereby animal welfare, productivity, and sustainability of the farming industry.

Keywords

Deepfake; Animal Welfare; Animal Emotions; Artificial Intelligence; Digital Farming; Animal Based Measures; Emotion Modeling; Livestock Health

Subject

Biology and Life Sciences, Biochemistry and Molecular Biology

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