AI exposure: Mathematicians
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.
Reading this score
computedMathematicians sits in the top 3% of every occupation measured. 63.1% of what this job consists of, weighted by how important each task is to the role, is work current AI systems can produce with little standing in the way. Very few occupations score this high. The ones that do tend to share a trait: the output is a document, a calculation or a message, and nobody has to be in a particular room for it to count.
No single friction dominates this occupation. The strongest is context at 1.50 out of 3 and the weakest is embodiment at 0.08, which is a narrow spread. Where nothing structural stands in the way, exposure tracks capability almost directly, and capability is the thing that changes every quarter.
The most exposed thing this job does is Assemble sets of assumptions, and explore the consequences of each set, at 86.7%. The least is Mentor others on mathematical techniques, at 35.4%. A gap of 51.2% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within computer and mathematical occupations, this one is more exposed than most. The median across the 36 roles in the group is 56.7%, and only 10 of them score higher than this. Occupational families are not uniform, and the spread inside them is often wider than the gap between them.
What would move this score. Of 12 tasks, 12 are currently banded exposed, 0 assisted and 0 untouched. For that distribution to shift materially would take cheaper ways to verify output, since the cost of checking is currently doing more to hold this work in place than the cost of producing it. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Task by task
12 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Assemble sets of assumptions, and explore the consequences of each set. | 86.7% | 13.3% | 0.0% | 4.00 | exposed |
| Perform computations and apply methods of numerical analysis to data. | 86.7% | 13.3% | 0.0% | 3.94 | exposed |
| Address the relationships of quantities, magnitudes, and forms through the use of numbers and symbols. | 86.7% | 13.3% | 0.0% | 3.89 | exposed |
| Apply mathematical theories and techniques to the solution of practical problems in business, engineering, the sciences, or other fields. | 80.0% | 20.0% | 0.0% | 3.67 | exposed |
| Develop computational methods for solving problems that occur in areas of science and engineering or that come from applications in business or industry. | 66.7% | 33.3% | 0.0% | 3.22 | exposed |
| Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences. | 65.0% | 10.0% | 25.0% | 4.25 | exposed |
| Conduct research to extend mathematical knowledge in traditional areas, such as algebra, geometry, probability, and logic. | 57.5% | 17.5% | 25.0% | 3.79 | exposed |
| Develop new principles and new relationships between existing mathematical principles to advance mathematical science. | 50.0% | 25.0% | 25.0% | 4.11 | exposed |
| Develop mathematical or statistical models of phenomena to be used for analysis or for computational simulation. | 50.0% | 25.0% | 25.0% | 3.67 | exposed |
| Disseminate research by writing reports, publishing papers, or presenting at professional conferences. | 47.5% | 27.5% | 25.0% | 4.10 | exposed |
| Design, analyze, and decipher encryption systems designed to transmit military, political, financial, or law-enforcement-related information in code. | 45.0% | 30.0% | 25.0% | 2.77 | exposed |
| Mentor others on mathematical techniques. | 35.4% | 27.1% | 37.5% | 4.25 | exposed |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 3.38 | 0-4 |
| Embodiment | 0.08 | 0-3 |
| Presence | 0.25 | 0-3 |
| Accountability | 0.62 | 0-3 |
| Context | 1.50 | 0-3 |
| Verification cost | 1.50 | 0-3 |
What this means in practice
Where most of a role's weighted task load is exposed, the work that survives is usually the part of the job nobody wrote into the job description: deciding what should be produced rather than producing it, and being answerable for the result. The tasks lowest on this page are a better guide to where to spend your time than any general advice about the future of work.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.