AI as TA
Teaching With AI in Intro to Machine Learning
Shen Shen
January 30, 2026
What kind of talk this is
Not a survey. Not a prescription.
A reflection on what emerged from experiments in my own teaching,
offered as a local view, and as a lens you might test against your own context.
Where did AI leverage actually show up?
Two axes for reasoning about AI use
Student-facing
Staff-facing
Routine
Creative
syntax drills
grading, logistics
open-ended projects
course design, explanation, narrative
The arc of this talk
Start with a clear win
↓
Then look at where pressure appeared — and how we adapted
↓
End with a small surprise that emerged
I:
Staff-facing AI amplified judgment and creativity
Brainstorm for analogies
strategize for design
critique and improve (iteratively)
Generate script
to smooth out segues
Vibe-code
slides animations
inspiration from podcast
\(\theta^*=\left({X}^{\top} {X}\right)^{-1} {X}^{\top} {Y}\)
A small moment from office hours
II:
AI shifted where learning signals became visible
AI changes which learning signals we can rely on, and when
Signal inflation — advanced courses
Master's project execution quality now ≈ earlier PhD-level work before GenAI.
To assess depth → shift toward reasoning, design choices, failure recovery.
Signal delay — introductory courses
Students more fluent (on the high-level), but foundational gaps less visible early on.
To assess gap → shift how we train our staff.
Our legacy lab checkoff
(like structured OHs)
Our legacy lab checkoff
(like structured OHs)
III:
Moving judgment upstream changed who could deeply participate in teaching
Registrar Registration Data
Student Course Materials Interaction Data
Internal Who-Has-Felt-What data
Exam Stats
Exam Source
| Branches | Contributors | |
|---|---|---|
| Spring25 | 45 | 21 |
| Fall24 | 1 | 7 |
| Spring24 | 1 | 11 |
lowered barrier for contribution
- All TAs are contributing
- Lots of LAs (sophomores) are contributing
- Workflow was improved by AI
- Content edit aided by AI
What actually carried the leverage
- The biggest gains came from where judgment lived, not which tools we used
- Making execution cheap didn't remove judgment, it made its placement visible
- Once judgment was placed deliberately, small adaptations had outsized effects
"Education is what remains after one has forgotten everything one learned in school."
— often attributed to Einstein
If AI accelerates the forgetting, our job is to be more deliberate about what we want to remain.
For me, what I want to remain is not knowledge, or skills per se, but the capacity to exercise
judgment, and the motivation to want to.
expanding-horizons-talk
By Shen Shen
