Are Life Science Taxonomists at Risk Due to AI?

All life scientists not listed separately.

The occupation "Life Scientists, All Other" has a base automation risk of 0.0%, reflecting the extremely low likelihood of replacement by current or foreseeable automation technologies. This group comprises life science professionals not classified under traditional specialties such as microbiology, zoology, or botany, and their work often addresses unique, complex, and novel biological questions. While automation can assist with very repetitive or standardized research tasks, the core of this profession—designing experimental protocols, interpreting ambiguous data, and conceptualizing new biological theories—relies fundamentally on human reasoning and creativity. Furthermore, many life scientists operate in fields where new discoveries continuously reshape research questions, demanding adaptability and nuanced judgment that machines currently lack. Thus, the nuanced and exploratory nature of their work underpins their immunity to automation-driven job displacement. Despite the overall resistance to automation, there are some tasks within this occupation that are more automatable. The top three most automatable tasks include high-throughput data collection (such as using robots to pipette samples in a laboratory), basic statistical analysis of large datasets, and routine laboratory maintenance or monitoring (such as temperature checks or equipment calibration). Automation can achieve efficiency improvements in these areas, freeing up human researchers for higher-level tasks. However, these tasks are typically supportive rather than central to the profession, and the automation of such duties often enhances, rather than replaces, the scientist’s role. Thus, these automatable aspects do not substantially affect the overall automation risk. Conversely, the most resistant tasks are those requiring advanced critical thinking, creative problem-solving, and expert synthesis of diverse information. The top three most automation-resistant tasks are: designing novel experiments to test unproven concepts, interpreting unprecedented or ambiguous research findings, and mentoring or collaborating with interdisciplinary teams to advance complex research agendas. The key bottleneck skills for this occupation include advanced scientific reasoning (expert level), creative hypothesis generation (expert level), and effective interdisciplinary communication (advanced to expert level). These skills resist codification and replication by algorithms or robots, maintaining a strong human-centric component in these roles. As such, the intellectual, innovative, and collaborative demands of "Life Scientists, All Other" solidify their occupation’s continued resistance to automation.