EXPOSED
The paper-and-screen half of this job — writing lecture slides, generating problem sets, autograding code, drafting syllabi, answering routine 'why won't my loop compile' questions — is exactly what LLMs do well, and CS is the one discipline where students already have a free tutor better at explaining pointers than most TAs. What survives is embodied classroom presence, research supervision, capstone and thesis advising, curriculum design under accreditation pressure, and the degree-granting institution's monopoly on credentials. The modal worker here is a teaching-heavy lecturer or community-college instructor, not a tenured R1 researcher; the lecturer tier is more exposed than the research tier.
Mixed — a routine tier and a judgment tier. Grading autogradable programming assignments, refreshing lecture decks on recursion, and fielding office-hour debugging questions are all now one prompt away, but running a live 200-seat lecture where you read confusion off faces, sitting on an ABET curriculum committee, and supervising a two-semester capstone team through scope collapse are not, which is why this sits at the middle of the mixed band rather than in the automatable floor.
Some physical or field component. You are physically in a room — proctoring closed-book exams so students can't prompt their way through, staffing hardware and networking labs with real switches and embedded boards, and holding scheduled in-person office hours — but none of it is uncontrolled or physically demanding, so it lands at the low end of the partial-physical band rather than up with clinical or field work.
Certification preferred, not legally required. No state licence gates who teaches CS 101; a master's or PhD plus departmental hiring and regional accreditation standards for faculty credentials is the whole barrier, and no statute makes you personally answerable for a graduate who ships insecure code — which is credential preference, not legal protection.
The human relationship is the product. Recommendation letters, PhD and thesis advising, and being the named person a student cites when a hiring manager asks who vouches for them are non-transferable relationships an institution cannot reassign mid-dissertation; the 14 rather than 18 reflects that the large intro-service courses most of these instructors actually teach are interchangeable to the student.
Meaningful discretion. You decide academic-integrity cases where the student swears the AI-flagged submission is theirs, set the curve that determines who stays in the major, and choose whether a language or framework enters the curriculum for the next four cohorts — real discretion with appeals processes and department chairs above you, which keeps it out of the top band.
Has AI actually changed your work?