Animal Scientists
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Conduct research in the genetics, nutrition, reproduction, growth, and development of domestic farm animals.
The occupation of "Animal Scientists" has an automation risk of 49.1%, which closely aligns with its base risk of 50.0%. This moderate level of automation risk is due to the mixed nature of tasks performed in this role—some tasks are highly automatable, while others require specialized human expertise. For example, tasks such as studying the nutritional requirements of animals and the nutritive values of animal feed materials are increasingly supported by advancements in data analytics and laboratory automation, reducing the need for direct human involvement. Communicating research findings, whether written or oral, can also be partially automated with current technology, as natural language processing systems become more sophisticated in generating reports and presentations. Similarly, developing improved practices in areas like feeding, housing, sanitation, and disease control often relies on data-driven analytics, which are well-suited to automation tools. However, the automation risk is tempered by tasks that demand a greater level of human ingenuity and judgment, making these aspects of the job more resistant to automation. Crossbreeding animals with existing or new strains to achieve desirable characteristics is a complex process that often relies on intuition, experience, and creative problem-solving that algorithms struggle to replicate. Determining the genetic composition of animal populations and understanding the heritability of traits involve nuanced genetic analysis and interpretation that currently exceed the full capabilities of automation. The control and improvement of animal selection and breeding practices to boost efficiency and quality also require adaptive thinking, ethical judgment, and the ability to respond to unpredictable biological variations—all factors that limit the potential for full automation. A key bottleneck in automating the work of animal scientists lies in the skill of originality, with reported levels of 3.3% and 3.9% as critical barriers. Original thought is essential for designing novel experiments, innovating new breeding techniques, and crafting solutions to unforeseen problems. These creative abilities enable animal scientists to intuitively connect disparate pieces of biological data, generate hypotheses, and make decisions in complex, variable environments. As current artificial intelligence systems struggle with tasks demanding high originality and adaptive reasoning, these skills serve as significant roadblocks to automation. Thus, while substantial portions of the work can be automated, the occupation retains a moderate risk due to the ongoing necessity for originality and creativity.