Computer Science Teachers, Postsecondary: daily tasks & AI impact
This page breaks Computer Science Teachers, Postsecondary into the top 15 daily O*NET tasks and scores each for Generative AI automation probability. Those task scores roll up to an overall vulnerability index of 55/100 (Moderate automation risk). Struck-through rows are ≥80% automatable; highlighted safer rows are under 30% or primarily physical.
High-automation exposure
No task in this set currently exceeds the 80% threshold, so risk is spread across moderate probabilities rather than a few catastrophic duties.
Durable human work
This profile has little “safe” task mass under our thresholds. Workers should treat AI fluency as mandatory and actively map transferable skills into lower-risk roles.
Importance comes from O*NET incumbent ratings. Automation probability is model-generated for current Generative AI capability (not speculative AGI). Digital / physical / mixed labels describe the modality of the work, which strongly correlates with near-term automation potential.
| Task | Importance | AI probability | Nature |
|---|---|---|---|
| Prepare course materials, such as syllabi, homework assignments, and handouts. Core | 4.59 | — | — |
| Compile, administer, and grade examinations or assign this work to others. Core | 4.58 | — | — |
| Prepare and deliver lectures to undergraduate or graduate students on topics such as programming, data structures, and software design. Core | 4.49 | — | — |
| Evaluate and grade students' class work, laboratory work, assignments, and papers. Core | 4.39 | — | — |
| Maintain student attendance records, grades, and other required records. Core | 4.21 | — | — |
| Keep abreast of developments in the field by reading current literature, talking with colleagues, and participating in professional conferences. Core | 4.16 | — | — |
| Plan, evaluate, and revise curricula, course content, and course materials and methods of instruction. Core | 4.15 | — | — |
| Maintain regularly scheduled office hours to advise and assist students. Core | 4.07 | — | — |
| Advise students on academic and vocational curricula and on career issues. Core | 4.04 | — | — |
| Initiate, facilitate, and moderate classroom discussions. Core | 3.94 | — | — |
| Develop and maintain Web sites for online courses. Core | 3.93 | — | — |
| Participate in student recruitment, registration, and placement activities. Core | 3.83 | — | — |
| Collaborate with colleagues to address teaching and research issues. Core | 3.69 | — | — |
| Select and obtain materials and supplies, such as textbooks and laboratory equipment. Core | 3.61 | — | — |
| Serve on academic or administrative committees that deal with institutional policies, departmental matters, and academic issues. Core | 3.38 | — | — |
What remains human
No tasks currently fall under the safe threshold for this occupation.
FAQ
Which Computer Science Teachers, Postsecondary tasks are most exposed to AI?
No task in this set currently exceeds the 80% threshold, so risk is spread across moderate probabilities rather than a few catastrophic duties.
Which Computer Science Teachers, Postsecondary tasks are safest from Generative AI?
This profile has little “safe” task mass under our thresholds. Workers should treat AI fluency as mandatory and actively map transferable skills into lower-risk roles.
How should I read the Computer Science Teachers, Postsecondary task table?
Importance comes from O*NET incumbent ratings. Automation probability is model-generated for current Generative AI capability (not speculative AGI). Digital / physical / mixed labels describe the modality of the work, which strongly correlates with near-term automation potential.