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# AI saves the expert time. For a fellow, writing the note may be the lesson
- URL: https://nephspace.com/ai-era-fellows-cjasn/
- Published: 2026-10-02T00:23:00.000Z
- Updated: 2026-10-04T19:23:31.000Z
- Description: A CJASN trainee perspective sets out what nephrology fellows need to know, do and value in the AI era. It warns of never-skilling: skills that never form because a machine did the work.
- Author: Dr Wael Hussein
- Tags: Other, #story, #has-audio, #education-ai, #opinion, #full-story, Stories

### The argument

In Through the Looking-Glass, the Red Queen has to run just to stay in place. This short CJASN Trainees' Spotlight piece, written by a trainee and a senior mentor in Singapore, opens with her and closes with a twist: "run twice as fast, and twice as smart." The worry in between is that AI can stop a skill from forming at all. The authors call this "never-skilling." Its cousin is "mis-skilling," learning something wrong because the AI got it wrong.

### Key points

The authors sort what fellows need into knowledge, skills and attitudes.

- Knowledge: use AI to find and process information faster, but still own the physiology. There is no shortcut to clinical reasoning. Fellows should know three families of AI: predictive models (for example, hyponatremia correction or ESA dosing), generative models such as chatbots, and agentic systems that carry out tasks on their own. Data privacy belongs on the list too.
- Skills: humans still beat AI at the bedside history, the exam and reasoning under uncertainty. AI can flag inadequate dialysis and suggest a longer session. It cannot weigh hours on the machine against the life a patient wants to live. Fellows need to prompt well, appraise output, check it against other sources, and know when to drop the tool. The authors cite a study in which general practice trainees were only 55% accurate at detecting AI hallucinations.
- Attitudes: expect a culture shock with stages, from honeymoon to frustration to acceptance. Be curious and skeptical at once.

Their sharpest example is note-writing. For an experienced nephrologist, an AI draft saves time on a repetitive task. For a junior fellow, writing the note on a complex patient is how they learn to pull the case together and decide. Programs, they say, should teach fellows not to use AI as an "easy way out." AI can also be a tutor, through slide quizzes, procedure feedback and simulated patients, though the authors say this needs more study.

### Why it matters

Much of the AI talk in nephrology is about saving clinicians time. This piece asks what that time was teaching. If the safety plan is that a clinician checks every AI draft, the trainee figure the authors cite suggests that check can't be taken for granted, especially early in training.

### Caveats

This is an opinion piece of about 1,200 words with no data. It offers no curriculum, no hours and no way to assess AI competence. Most of the tutor examples come from outside nephrology and are early. It does not say who will teach the teachers.

Industry ties: none to AI companies. The authors report dialysis and pharmaceutical industry ties unrelated to this topic.

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**The source:** Fong JMN, Wang AY-M. Equipping Nephrology Fellows with the Knowledge, Skills, and Attitudes for the Artificial Intelligence Era. Clin J Am Soc Nephrol. 2026 (ahead of print). doi:10.2215/CJN.0000001239 [Read the original](https://doi.org/10.2215/CJN.0000001239?ref=nephspace.com)

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*Physician-led, AI-assisted. Dr. Wael Hussein chooses every item NephSpace covers and reviews and edits every story before it is published. The first draft was written in our own words with AI (Claude, by Anthropic) from the full text of the paper and checked against our reading notes; Dr. Hussein then reviewed and edited it. For education and information only, not medical advice. Please talk to your own physician or care team about your health. Clinicians: read the original before changing practice. See our* [*disclaimer*](https://nephspace.com/disclaimer/) *and* [*disclosures*](https://nephspace.com/disclosures/)*. Spotted an error?* [*Tell us*](mailto:hello@nephspace.com?subject=Correction)*.*