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AI in Magnetic Resonance: Tool, Teammate, or Trap ?
Your answers are anonymous.
Your role
*
Undergraduate / Master student
PhD student
Postdoc
Faculty / PI
Staff scientist / Engineer
Industry
Your primary MR field (choose all that apply)
*
NMR
EPR / ESR
MRI
Hyperpolarization
Quantum Information / Sensing (e.g. NV)
Other
How often do you use AI tools for MR-related work ?
*
Select
Never
Rarely
Sometimes
Frequently
Which tasks do you use AI for most ?
*
(choose all that apply)
Paper writing (phrasing, editing)
Literature summarization
Idea generation / Brainstorming
Grant writing
Simulation Code help (MATLAB / Python / …)
Data analysis / Fitting
Pulse sequence
Experimental troubleshooting
Slide preparation
Teaching / Learning concepts
Other
Do you cross check information from AI ?
*
Always
Sometimes
50 % of the time
Only if the information is surprising to me
Never
Did AI change your research productivity ?
*
(Scale 1–5: decreased→ improved)
Which area could benefit from the use of AI?
*
Writing papers
Coding & debugging
Learning of new concepts or summarizing papers
Experimental design
Spectra Interpretation
No opinion
Other
Should AI use be declared in papers/theses ?
*
Select
Yes
No
Maybe
Should AI be implemented in research software ?
*
(e.g. data acquisition, processing, interpretation)
Select
Needed
Doesn’t matter
Not required
If you think so, which software(s) and for what purpose(s) ?
In your opinion, AI will mostly:
*
Increase scientific rigor
Decrease scientific rigor
Both equally
Unsure
Has AI changed the way you think scientifically ?
*
Select
Yes
No
Maybe
Would you attend workshops on “AI for Magnetic Resonance" (if there is one) ?
*
Select
Yes
No
Maybe
What should be included in such training ?
Submit
Please do not fill in this field.
