Mathematicians
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Conduct research in fundamental mathematics or in application of mathematical techniques to science, management, and other fields. Solve problems in various fields using mathematical methods.
The occupation of mathematicians has an automation risk of 44.5%, slightly lower than the base risk of 45.5%. This moderate risk level reflects both the highly structured and routinized aspects of mathematical work as well as the significant creative and problem-solving components. Many tasks performed by mathematicians involve activities that machines can increasingly automate, but a substantial portion of the role relies on skills that are still challenging for AI and automation technologies to replicate fully. The top three most automatable tasks for mathematicians underscore why automation is a tangible risk. For example, addressing the relationships of quantities, magnitudes, and forms using numbers and symbols is a task well suited to algorithmic automation, as computers can efficiently process and manipulate symbolic mathematics. Similarly, disseminating research by writing reports, publishing papers, or presenting can be partially automated through AI systems capable of generating natural language summaries and presentations. Maintaining knowledge in the field by reading professional journals or attending conferences is also susceptible to automation, as AI tools can scan literature, synthesize findings, and provide professional updates with growing sophistication. However, the most resistant tasks demand a depth of creativity and abstract thinking that current technologies struggle to match. Designing, analyzing, and deciphering encryption systems for sensitive information requires a blend of theoretical understanding, innovation, and real-world context that exceeds the capability of automated systems. Likewise, developing computational methods to solve problems in science, engineering, or industry, and formulating new mathematical principles or relationships, are tasks that hinge on originality and conceptual breakthrough. The importance of bottleneck skills like originality—rated at 3.5% and 4.9% levels—further illustrates that while certain repetitive or information-processing tasks may be automated, the inventive and pioneering aspects of a mathematician's work remain difficult for automation to replace.